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M. Night Shyamalan will be taking part in a review of his work at Film at Lincoln Center for the coming week. It is there that most of Shyamalan’s work is being screened ( in 35mm when possible ) and paired with some of the idiosyncratic filmmaker’s favorite touchstones. For instance, Old is a film about people who can’t physically [ …].

The article M. Night Shyamalan Displays on His’ Resurrection’ Period Following After Earth Sorrow appeared second on Den of Geek.

CGI is a significant component of contemporary blockbusters, whether we’re talking about Superman or Snow White. Trivia geeks know that CGI has been a part of films since laptops were used to help make the starting names of 1958&#8217, s Vertigo. However, the 1990s&#8212, and frequently at its worst, a la The Lawnmower Man‘s absurd virtual worlds or Spawn‘s unpleasant hellscapes, are what most people think of when they think of the beginning of CGI in movies. Nevertheless, there are a surprising number of videos that also look very great, even decades later.

The physical effects designers on these movies contributed to the creation of images that endured over time, whether it’s as a result of the first explosion of technical innovation or the realization that occasionally restraint is preferable to excess.

Terminator 2: Judgment Day ( 1991 )

James Cameron should decide how to proceed. For as much as people like to scold the obviously false head used in the restoration scene from The Terminator, every single consequence in ( the much more expensive ) Terminator 2 also holds up now. In fact, the T-1000’s shapeshifting is so amazing that it still retains its gold ( silver ) appearance. regular for music films.

Part of the success of the film &#8217, which will become a design in this list, is when Cameron knows when to use practical results and when to use computers. He used make-up and accessories whenever feasible, including creating a robotic for Robert Patrick to use as the bullet-riddled T-1000. However, that shouldn’t detract from the care Cameron and ILM took in creating the actual CG, which made the T-1000’s shifts feel like actual ( and genuinely terrifying ) regions of this world.

Beauty and the Beast ( 1991 )

The second fully-CG animated feature film, Toy Story, is the first one to come to mind when describing computer graphics and 90s video. But even the most hardcore Woody &#8217, s Summary watcher has to confess that the photos of Toy Story look very harsh today. Similar cannot be said of Beauty and the Beast and its expansive Board room set.

For most of Beauty and the Beast, managers Gary Trousdale and Kirk Wise apply hand-drawn graphics. Trousdale and Wise called upon the CG officer Jim Hillin to force the Pixar-developed Computer Animation Creation System further than it had been before for the striking ballroom dancing series, which features the lovely title ballad. The result is something great and beautiful, a second scene that totally sells the passionate change of heart for Belle and the Beast.

Death Becomes Her ( 1992 )

On one hand, Death Becomes Her is an oddity in the film of Robert Zemeckis. The relationship between two women ( Meryl Streep and Goldie Hawn ), whose bodies change as they vie for the affections of a doofy plastic surgeon ( Bruce Willis ), feels more at home on Broadway ( where there is currently a smashing musical adaptation of the movie ) than it does with Zemeckis&#8217, Boomer classics Back to the Future and Forrest Gump.

With that said, the extraordinary results in Death Becomes Her truly are the function of a tech-obsessed cinematographer. The cartoon-logic teachings that Zemeckis learned from the film Who Framed Roger Rabbit in 1988 are applied to this film. and applies them to real folks. The persona of Streep with her nose twisted around or Hawn with a hole in her abdomen should be a nightmare, but Death Becomes Her turns them into camp video secret.

Jurassic Park ( 1993 )

When stop-motion artist Phil Tippett saw the electric animals ILM was creating for Jurassic Park, he informed Dennis Muren, &#8220, We&#8217, be dead, according to behind-the-scenes traditions. &#8221, Thankfully Tippett continues to work (you may have seen his graphics in a time one instance of Poker Face ), but his concerns were justified. Jurassic Park‘s dinosaurs still look incredible, maybe even better than beasties in afterwards Jurassic World appearances. The introduction of the animals furthermore stands as one of Steven Spielberg&#8217, s most awe-inspiring events, perhaps within a film filled with wonder.

Of course, Jurassic Park succeeds in piece because Steven Spielberg heavily relies on Stan Winston&#8217, s puppetry. Not only did Winston, Tippett, and the team figure out the fat and movements of the raptors, but they also created mechanical puppets to communicate with the actors as much as possible. Judasic Park was able to demonstrate how much restraint can be, something that those who followed too frequently forgot.

Forrest Gump ( 1994 )

Forrest Gump has only lost ground in public opinion in the three decades since its triumphant Academy Award-winning run. Modern viewers may question its conservative politics and Boomer nostalgia-baiting, but no one can take exception with Forrest Gump&#8216, s special effects.

In a time of deep-fakes, the trick of putting Tom Hanks &#8216, idiot savant, Richard Nixon and John Lennon on news reels works pretty well for the modern audience. Even better is everything involving Lieutenant Dan, for which Ken Ralston and his team at ILM digitally removed Gary Sinise&#8217, s legs to make the actor appear paraplegic. Forrest Gump maintains its focus on the past without distracting viewers with futuristic razzle-dazzle thanks to their work.

The Mask ( 1994 )

The Mask uses significantly less CGI than one might anticipate, much like Jurassic Park. Unlike Jurassic Park, most of those non-CG effects are all the work of one man, Jim Carrey and his incredible face. Carrey’s rubber-faced tour de force shouldn’t, however, detract from how competent ILM animation director Wes Takahashi and his team made Carrey into a true cartoon.

Unlike so many of the entries on this list, the effects in The Mask do not look realistic, but that &#8217, s the point. The Mask still feels like we’re watching a Tex Avery cartoon invade the real world, and Carrey’s mousey Stanley Ipkiss ‘ abilities when he dons the titular mask are supposed to feel weird.

Babe ( 1995 )

It’s much easier to animate non-human objects, including animals, than it is to animate humans, according to the Pixar special effects team, because we viewers are too aware of what people should look like. But as &#8217, 90s hits such as Anaconda and Jumanji demonstrated, it can be pretty darn hard to make effective CG animals as well.

Which is just one of many reasons why George Miller co-wrote and directed Chris Noonan’s film Babe, which feels like a miracle. The animals on Hoggett Farm look like actual pigs, dogs, and sheep, even when they speak with the voices of Christine Cavanaugh, Hugo Weaving, and Miriam Flynn. Rhythm &amp, Hues Studios, Animal Logic, and ( of course ) Jim Henson’s Creature Shop is a success thanks to the work of effects houses, Hues Studios, Animal Logic, and ( of course ) Jim Henson, so that the animals are actually entertaining to watch.

Men in Black ( 1997 )

The Mask‘s greatest special effect is not at all digital, as it was in The Mask; instead, it is an actor’s performance as Vincent D&#8217 and Onofrio as a bug that resembles an Edgar farmer. That said, D&#8217, Onofrio has room to stand out precisely because he&#8217, s surrounded by absurd images that fit right in within the world. Edgar is just one more oddity, along with Tony Shalhoub regenerating his own head and squid babies and coffee-obsessed creatures.

Many of those elements stem from Rick Baker and his team, who first built puppets and maquettes based on input from director Barry Sonnenfeld and producer Steven Spielberg. Artists at ILM digitized and animated the creatures from that foundation, allowing them to interact with Agent K, Agent K, and Agent J, Agent K.

Starship Troopers ( 1997 )

In terms of alien bugs, Dutch director Paul Verhoeven could have scrimped on the effects of his Robert Heinlein adaptation, Starship Troopers, if he wanted. After all, part of the movie&#8217, s satirical anti-fascist message rests on the fact that the alien Arachnids are marked for extermination precisely because they don&#8217, t look like us.

Instead, Verhoeven gave the visual effects a lot of attention, requiring the assistance of several effects firms, including Phil Tippett, Sony Pictures Imageworks, ILM, Amalgamated Dynamics, and more. They took up half of the film’s$ 110 million budget. Today it &#8217, s clear that the money and effort was worth it. The creatures have a clear intelligence and personality that helps reinforce the film &#8217, s subversive themes, and not only are the scenes of the Arachnids decimating human soldiers appropriately upsetting.

Titanic ( 1997 )

One has a suspicion that James Cameron’s initial plan was to simply rebuild the Titanic and plunge it into an iceberg, given his Aguirre-like resolve. Since that was n&#8217, t an option, Cameron did the next best thing, creating incredible models of the ill-fated ship. The ship’s sank and split scenes look incredible, and the boat itself is the only thing that works thanks to the digital effects Cameron uses.

Like hair and fur, water is famously a difficult thing to animate well. Cameron used CG to ground the spectacle in real emotions while working with Pacific Data Images and Digital Domain to continue to advance the water effects he created for The Abyss. Cameron and his team scanned the faces of actors to create digital models, so we could get the sense of real people falling and drowning as the ship went down. Titanic is a spectacular epic and also a very human drama thanks to these efforts.

The Matrix ( 1999 )

The Matrix‘s dynamic slow motion system, bullet time, is what most people think of when they think of special effects. Believe it or not, with the exception of some computer pre-visualization, most bullet time sequences were done practically, in-camera. Yet CG was used for many of the film’s standout sequences, which are still captivating viewers.

Images of Keanu Reeves losing his mouth as Neo, or getting enveloped by a mirror, are not as flawless today as they were in 1999. They continue to be incredibly effective in signaling Neo&#8217, s recognition that the world is not what he thought it was, as do the sequences in the film &#8217, s actual reality, those of humans being turned into batteries and the menacing sentinels.

Star Wars &#8211, Episode I: The Phantom Menace ( 1999 )

Even the most ardent supporter of The Phantom Menace has trouble fully approuving the effects. So much of the lead up to the movie&#8217, s release hyped the digital worlds that George Lucas created with ILM, and so much of the movie&#8217, s wooden dialogue was blamed on those same artificial sets. Even the most hating fan of prequels must admit that, despite the film’s flaws, The Phantom Menace looks fantastic.

It&#8217, s not just the pod racing sequence or the climactic lightsaber duel that hold up —even though they both certainly do. The seascape that Obi-Wan Kenobi and Qui-Gon Jinn traverse while visiting the Gungans, as well as the palace where Amidala controls Naboo, are also the quieter elements. All of these elements still impress, even if The Phantom Menace itself remains divisive.

Little, Stuart ( 1999 )

Given all the groundbreaking, high-concept movies on this list, it might feel like a bit of a letdown to end with a gentle children&#8217, s movie about a mouse adopted by a human family. Anyone who watches Stuart Little today will find that to be exact. Like Babe, Stuart Little had to bring animals to life, namely the titular mouse and the various cats he encounters. The effects had to be good enough to stop the audience of children from being sucked out of the story, just like Babe.

Effects artist Rob Bredow and his team at ILM painstakingly found new methods to create fur and animal expressions that managed to both look realistic and convey emotions. Their efforts received an Oscar nomination for the best visual effects ( losing out to The Matrix ) and, more importantly, the joy experienced by young viewers who had never even realized they were n’#8217, weren’t actually looking at a mouse.

The post 1990s CGI Movies That Still Hold Up Today appeared first on Den of Geek.

CGI is a significant component of the present movie, whether we’re talking about Superman or Snow White. Trivia geeks know that CGI has been a part of films since laptops were used to help make the starting names of 1958’s Vertigo. However, when most individuals consider the beginning of CGI in […]

The blog 1990s CGI Movies That Also Keep Up Now appeared first on Den of Geek.

CGI is a significant component of the current movie, regardless of whether we’re talking about Superman or Snow White. Trivia geeks know that CGI has been a part of films since laptops were used to help make the starting names of 1958&#8217, s Vertigo. However, when most individuals think of the beginning of CGI in movies, they generally think of the 1990s&#8212, a la The Lawnmower Man‘s absurd virtual worlds or Spawn‘s ugly hellscapes, which is often at its worst. Nevertheless, there are a surprising number of videos that also look very wonderful, even decades later.

The visual effects artists on these movies helped produce images that stood the test of time, whether it’s just the first explosion of technological advancement or the knowing that often restraint is better than extra.

Terminator 2: Judgment Day ( 1991 )

James Cameron should decide how to do it. For as much as people like to scold the obviously false head used in the restoration scene from The Terminator, every single consequence in ( the much more expensive ) Terminator 2 also holds up now. In fact, the T-1000’s shapeshifting is so amazing that it still retains its gold ( silver ) appearance. regular for music films.

Part of the achievements of the film &#8217 comes from Cameron knowing when to use realistic outcomes and when to use computers, which will become a theme in the next section of the list. He used make-up and decorations whenever feasible, including creating a robotic for Robert Patrick to use as the bullet-riddled T-1000. However, that shouldn’t diminish the care Cameron and ILM showed in creating the actual CG, which made the T-1000’s shifts feel like actual ( and genuinely terrifying ) places in the world.

Beauty and the Beast ( 1991 )

When referring to computer graphics and the 90s video genre, the second fully-CG animated feature film released in 1995 comes to mind. But even the most hardcore Woody &#8217, s Summary watcher has to confess that the photos of Toy Story look very harsh today. Similar cannot be said of Beauty and the Beast and its expansive Governance room set.

For most of Beauty and the Beast, managers Gary Trousdale and Kirk Wise apply hand-drawn video. Trousdale and Wise requested Jim Hillin, the CG officer, to help advance the Pixar-developed Computer Animation Creation System further than it had been for the striking ballroom dancing sequence, which features the stunning name ballad. The result is something great and beautiful, a second scene that totally sells the passionate change of heart for Belle and the Beast.

Death Becomes Her ( 1992 ) )

On one hand, Death Becomes Her is an oddity in the movie of Robert Zemeckis. The relationship between two women ( Meryl Streep and Goldie Hawn ), whose bodies change as they vie for the affections of a doofy plastic surgeon ( Bruce Willis ), feels more at home on Broadway ( where there is currently a smashing musical adaptation of the movie ) than it does with Zemeckis&#8217, Boomer classics Back to the Future and Forrest Gump.

With that said, the extraordinary results in Death Becomes Her truly are the function of a tech-obsessed cinematographer. Zemeckis applies the cartoon-logic principles he learned while creating Who Framed Roger Rabbit in 1988 &#8217. and applies them to real people. Although Streep may have nightmares with her nose twisted around or Hawn with a hole in her belly, Death Becomes Her manages to make them camp movie magic.

Jurassic Park ( 1993 )

When stop-motion artist Phil Tippett saw the electric animals ILM was creating for Jurassic Park, he informed Dennis Muren, &#8220, We&#8217, be dead, according to behind-the-scenes traditions. &#8221, Thankfully Tippett continues to work (you may have seen his graphics in a time one instance of Poker Face ), but his concerns were justified. Jurassic Park‘s dinosaurs still look incredible, maybe even better than beasties in after Jurassic World appearances. The introduction of the animals furthermore stands as one of Steven Spielberg&#8217, s most awe-inspiring events, perhaps within a film filled with wonder.

Of course, Jurassic Park succeeds in piece because Steven Spielberg relies heavily on Stan Winston&#8217’s puppetry. Not only did Winston, Tippett, and the team figure out the fat and movements of the raptors, but they also created mechanical puppets to communicate with the stars as much as possible. The followers of Jurasic Park frequently forget how much restraint can exert on them.

Forrest Gump ( 1994 )

Forrest Gump has only lost support among the general public in the three decades that have followed its triumphant Academy Award-winning run. Modern viewers may question its conservative politics and Boomer nostalgia-baiting, but no one can take exception with Forrest Gump&#8216, s special effects.

In a time of deep-fakes, it is impossible to put Tom Hanks &#8216, idiot savant on news reels with Richard Nixon and John Lennon, but it still manages to fit in fairly well for the modern audience. Even better is everything involving Lieutenant Dan, for which Ken Ralston and his team at ILM digitally removed Gary Sinise&#8217, s legs to make the actor appear paraplegic. Forrest Gump maintains its focus on the past without distracting viewers with futuristic razzle-dazzle thanks to their work.

The Mask ( 1994 )

The Mask uses much less CGI than one might anticipate, much like Jurassic Park. Unlike Jurassic Park, most of those non-CG effects are all the work of one man, Jim Carrey and his incredible face. Carrey’s rubber-faced tour de force shouldn’t, however, detract from the excellent work of ILM animation director Wes Takahashi and his team.

Unlike so many of the entries on this list, the effects in The Mask do not look realistic, but that &#8217, s the point. The Mask still feels like we’re watching a Tex Avery cartoon invade the real world, and Carrey’s mousey Stanley Ipkiss ‘ abilities when he dons the titular mask are supposed to feel weird.

Babe ( 1995 )

Because we viewers are too well-versed in what people should look like, it’s much easier to animate non-human things like animals, including animals. But as &#8217, 90s hits such as Anaconda and Jumanji demonstrated, it can be pretty darn hard to make effective CG animals as well.

Which is just one of many reasons why George Miller co-wrote and directed Chris Noonan’s film Babe, which feels like a miracle. The animals on Hoggett Farm look like actual pigs, dogs, and sheep, even when they speak with the voices of Christine Cavanaugh, Hugo Weaving, and Miriam Flynn. In contrast to the modern Lion King movies, Babe manages to imbue the animals with personality thanks to the work of effects houses Rhythm &amp, Hues Studios, Animal Logic, and ( of course ) Jim Henson’s Creature Shop.

Men in Black ( 1997 )

The Mask‘s greatest special effect is not entirely digital, but it is a performance by Vincent D&#8217 and Onofrio as a bug that infects an agriculturalist by the name of Edgar. That said, D&#8217, Onofrio has room to stand out precisely because he&#8217, s surrounded by absurd images that fit right in within the world. Edgar is just one more oddity, along with Tony Shalhoub regenerating his own head and squid babies and coffee-obsessed creatures.

Many of those elements stem from Rick Baker and his team, who first built puppets and maquettes based on input from director Barry Sonnenfeld and producer Steven Spielberg. Artists at ILM digitized and animated the creatures from that foundation, allowing them to interact with Agent K, Agent K, and Agent J, Agent K.

Starship Troopers ( 1997 )

In terms of alien bugs, Paul Verhoeven‘s adaptation of Starship Troopers, based on Robert Heinlein, could have had a bad ol ‘ sizing. After all, part of the movie&#8217, s satirical anti-fascist message rests on the fact that the alien Arachnids are marked for extermination precisely because they don&#8217, t look like us.

Instead, Verhoeven gave the visual effects a lot of attention, requiring the assistance of several effects firms, including Phil Tippett, Sony Pictures Imageworks, ILM, Amalgamated Dynamics, and more. They took up half of the film’s$ 110 million budget. Today it &#8217, s clear that the money and effort was worth it. The creatures have a clear intelligence and personality that helps to reinforce the film’s subversive themes, but the scenes of the Arachnids decimating human soldiers are also appropriately upsetting.

Titanic ( 1997 )

One has a suspicion that James Cameron’s original plan was to simply rebuild the Titanic and plunge it into an iceberg given his Aguirre-esque determination. Since that was n&#8217, t an option, Cameron did the next best thing, creating incredible models of the ill-fated ship. The ship’s interior and exterior look incredible, and the boat itself gets the majority of the attention, which only works thanks to the digital effects Cameron uses.

Like hair and fur, water is famously a difficult thing to animate well. Cameron used CG to ground the spectacle in real emotions while working with Pacific Data Images and Digital Domain to continue developing the water effects he created for The Abyss. Cameron and his team scanned the faces of actors to create digital models, so we could get the sense of real people falling and drowning as the ship went down. Titanic is a stunning epic and very human drama as a result of these efforts.

The Matrix ( 1999 )

When most people think of The Matrix‘s special effects, their thoughts immediately jump to bullet time, the creative slow motion technique created by director John Gaeta for the movie. Believe it or not, with the exception of some computer pre-visualization, most bullet time sequences were done practically, in-camera. Yet CG was used for many of the film’s standout sequences, which are still captivating viewers.

Images of Keanu Reeves losing his mouth as Neo, or getting enveloped by a mirror, are not as flawless today as they were in 1999. They continue to be very effective in signaling Neo’s recognition that the world is not what he thought it was, as do the scene sequences in the movie’s actual reality, where people are being turned into batteries and the terrifying sentinels.

Star Wars &#8211, Episode I: The Phantom Menace ( 1999 )

Even the most ardent supporter of The Phantom Menace has trouble fully approuving the effects. So much of the lead up to the movie&#8217, s release hyped the digital worlds that George Lucas created with ILM, and so much of the movie&#8217, s wooden dialogue was blamed on those same artificial sets. Even the most hating fan of prequels must admit that, despite the film’s flaws, The Phantom Menace looks fantastic.

It&#8217, s not just the pod racing sequence or the climactic lightsaber duel that hold up —even though they both certainly do. The seascape that Obi-Wan Kenobi and Qui-Gon Jinn traverse while visiting the Gungans, as well as the palace where Amidala controls Naboo, are also the quieter elements. All of these elements still impress, even if The Phantom Menace itself remains divisive.

Stuart Little ( 1999) )

Given all the groundbreaking, high-concept movies on this list, it might feel like a bit of a letdown to end with a gentle children&#8217, s movie about a mouse adopted by a human family. Anyone who watches Stuart Little today will find that to be exacting. Like Babe, Stuart Little had to bring animals to life, namely the titular mouse and the various cats he encounters. The effects had to be effective enough to stop the audience from being detracted from the story, just like Babe.

Effects artist Rob Bredow and his team at ILM painstakingly found new methods to create fur and animal expressions that managed to both look realistic and convey emotions. Their efforts received an Oscar nomination for the best visual effects ( losing out to The Matrix ) and, more importantly, the joy experienced by young viewers who had never even realized they were n’#8217, weren’t actually looking at a mouse.

The blog 1990s CGI Movies That Also Keep Up Now appeared first on Den of Geek.

Clues appear in this article for Peacemaker winter 2 show 1. If 1978’s Superman made us believe that a man could travel, 2025’s Superman made us believe that generosity is rock. In time two of [ …] the fans of the message of Superman will be faced with something much closer to the conventional definition of rock.

The article Peacemaker and the Problem with James Gunn’s DCU appeared initially on Den of Geek.

CGI is a significant component of the current hit, regardless of whether we’re talking about Superman or Snow White. Trivia geeks know that CGI has been a part of films since laptops were used to help make the starting names of 1958&#8217, s Vertigo. However, the 1990s&#8212, and frequently at its worst, a la The Lawnmower Man‘s funny virtual worlds or the dirty hellscapes of Spawn, are what most folks think of when they think of the beginning of CGI in movies. Nevertheless, there are a surprising number of videos that also look very wonderful, even decades later.

The physical effects designers on these movies contributed to the creation of images that endured over time, whether it’s as a result of the first explosion of technical innovation or the realization that often restraint is preferable to excess.

Terminator 2: Judgment Day ( 1991 )

James Cameron should decide how to proceed. For as much as people like to scold the obviously false head used in the restoration scene from The Terminator, every single consequence in ( the much more expensive ) Terminator 2 also holds up now. In fact, the T-1000’s shapeshifting is so amazing that it still retains its gold ( silver ) appearance. regular for music films.

Part of the success of the film &#8217, which will become a design in this list, is when Cameron knows when to use practical outcomes and when to use computers. He used make-up and accessories whenever feasible, including creating a robotic for Robert Patrick to use as the bullet-riddled T-1000. However, that shouldn’t detract from the care Cameron and ILM took in creating the actual CG, which made the T-1000’s shifts feel like actual ( and genuinely terrifying ) regions of this world.

Beauty and the Beast ( 1991 )

Most people quickly gravitate to 1995 &#8217, the first fully-CG animated feature film, when talking about computer graphics and &#8217, 90s video. But even the most hardcore Woody &#8217, s Summary watcher has to confess that the photos of Toy Story look very harsh today. Similar cannot be said of Beauty and the Beast and its expansive Governance room set.

For most of Beauty and the Beast, managers Gary Trousdale and Kirk Wise apply hand-drawn video. Trousdale and Wise called on the CG officer Jim Hillin to force the Pixar-developed Computer Animation Creation System further than it had been for the striking ballroom dancing series, which features the lovely title ballad. The result is something great and beautiful, a second scene that totally sells the passionate change of heart for Belle and the Beast.

Death Becomes Her ( 1992 ) )

On one hand, Death Becomes Her is an aberration in the film of Robert Zemeckis. The relationship between two women ( Meryl Streep and Goldie Hawn ), whose bodies change as they vie for the affections of a doofy plastic surgeon ( Bruce Willis ), feels more at home on Broadway ( where there is currently a smashing musical adaptation of the movie ) than it does with Zemeckis&#8217, Boomer classics Back to the Future and Forrest Gump.

With that said, the extraordinary results in Death Becomes Her truly are the function of a tech-obsessed cinematographer. Zemeckis applies the cartoon-logic principles he learned while creating Who Framed Roger Rabbit in 1988 to the film. and applies them to real people. Although Streep may have nightmares with her nose twisted around or Hawn with a hole in her belly, Death Becomes Her manages to make them camp movie magic.

Jurassic Park ( 1993 )

Behind-the-scenes legends claim that Phil Tippett, a stop-motion animator, told Dennis Muren that the modern reptiles ILM was creating for Jurassic Park were extinct. &#8221, Thankfully Tippett continues to work (you may have seen his graphics in a time one instance of Poker Face ), but his concerns were justified. Jurassic Park‘s reptiles still appear incredible, occasionally even better than creatures in after Jurassic World films. The introduction of the animals furthermore stands as one of Steven Spielberg&#8217, s most awe-inspiring events, perhaps within a film filled with wonder.

Of course, Jurassic Park succeeds in piece because Steven Spielberg heavily relies on Stan Winston&#8217, s puppetry. Not only did Winston, Tippett, and the team figure out the fat and movements of the raptors, but they also created mechanical puppets to communicate with the stars as much as possible. The followers of Jurasic Park frequently forget how much restraint can exert on them.

Forrest Gump ( 1994 )

Forrest Gump has only lost ground in public opinion in the three decades since its triumphant Academy Award-winning run. Modern viewers may question its conservative politics and Boomer nostalgia-baiting, but no one can take exception with Forrest Gump&#8216, s special effects.

In a time of deep-fakes, the trick of putting Tom Hanks &#8216, idiot savant, Richard Nixon and John Lennon on news reels works pretty well for the modern audience. Even better is everything involving Lieutenant Dan, for which Ken Ralston and his team at ILM digitally removed Gary Sinise&#8217, s legs to make the actor appear paraplegic. Forrest Gump keeps its eye on the past without obstructing viewers with futuristic razzle-dazzle thanks to their work.

The Mask ( 1994 )

The Mask uses significantly less CGI than one might anticipate, much like Jurassic Park. Unlike Jurassic Park, most of those non-CG effects are all the work of one man, Jim Carrey and his incredible face. Carrey’s rubber-faced tour de force shouldn’t, however, detract from how competent ILM animation director Wes Takahashi and his team made Carrey into a true cartoon.

Unlike so many of the entries on this list, the effects in The Mask do not look realistic, but that &#8217, s the point. The Mask still feels like we’re watching a Tex Avery cartoon invade the real world, and the abilities that Carrey &#8217, s mousey Stanley Ipkiss gets when he dons the titular mask are supposed to feel weird.

Babe ( 1995 )

Because we viewers are too well-versed in what people should look like, it’s much easier to animate non-human things like animals, including animals. But as &#8217, 90s hits such as Anaconda and Jumanji demonstrated, it can be pretty darn hard to make effective CG animals as well.

Which is just one of many reasons why George Miller co-wrote and directed Chris Noonan, and why it seems like such a miracle. The animals on Hoggett Farm look like actual pigs, dogs, and sheep, even when they speak with the voices of Christine Cavanaugh, Hugo Weaving, and Miriam Flynn. In contrast to the modern Lion King movies, Babe manages to imbue the animals with personality thanks to the work of effects houses Rhythm &amp, Hues Studios, Animal Logic, and ( of course ) Jim Henson’s Creature Shop.

Men in Black ( 1997 )

The Mask‘s greatest special effect is not entirely digital, but it is a performance by Vincent D&#8217 and Onofrio as a bug that infects an agriculturalist by the name of Edgar. That said, D&#8217, Onofrio has room to stand out precisely because he&#8217, s surrounded by absurd images that fit right in within the world. Along with Tony Shalhoub regenerating his own head, squid babies, coffee-obsessed creatures, and Edgar, there is just one more oddity.

Many of those elements stem from Rick Baker and his team, who first built puppets and maquettes based on input from director Barry Sonnenfeld and producer Steven Spielberg. Artists at ILM digitized and animated the creatures to make them agents Tommy Lee Jones, Agent K, and Agent J, Agent J.

Starship Troopers ( 1997 )

In terms of alien bugs, Paul Verhoeven‘s adaptation of Starship Troopers, based on Robert Heinlein, could have had a bad ol ‘ sizing. After all, part of the movie&#8217, s satirical anti-fascist message rests on the fact that the alien Arachnids are marked for extermination precisely because they don&#8217, t look like us.

Instead, Verhoeven gave the visual effects a lot of priority, accounting for half of the film’s$ 110 million budget and enlisting the assistance of several effects firms, including Phil Tippett&#8217, Sony Pictures Imageworks, ILM, Amalgamated Dynamics, and others. Today it &#8217, s clear that the money and effort was worth it. The creatures have a clear intelligence and personality that helps reinforce the film &#8217, s subversive themes, and not only are the scenes of the Arachnids decimating human soldiers appropriately upsetting.

Titanic ( 1997 )

One has a suspicion that James Cameron&#8217, s first plan was to just rebuild the Titanic and plunge it into an iceberg given his Aguirre-esque determination. Since that was n&#8217, t an option, Cameron did the next best thing, creating incredible models of the ill-fated ship. The ship’s interior and exterior look incredible, and the boat itself gets the majority of the attention, which only works thanks to the digital effects Cameron uses.

Like hair and fur, water is famously a difficult thing to animate well. Cameron used CG to ground the spectacle in real emotions while working with Pacific Data Images and Digital Domain to continue to advance the water effects he created for The Abyss. Cameron and his team scanned the faces of actors to create digital models, so we could get the sense of real people falling and drowning as the ship went down. Titanic is a spectacular epic and also a very human drama thanks to these efforts.

The Matrix ( 1999 )

When most people think of The Matrix‘s special effects, their thoughts immediately jump to bullet time, the creative slow motion technique created by director John Gaeta for the movie. Believe it or not, with the exception of some computer pre-visualization, most bullet time sequences were done practically, in-camera. Yet CG was used for many of the film’s standout sequences, which are still captivating viewers.

Images of Keanu Reeves losing his mouth as Neo, or getting enveloped by a mirror, are not as flawless today as they were in 1999. They continue to be incredibly effective in signaling Neo&#8217, s recognition that the world is not what he thought it was, as do the sequences in the film &#8217, s actual reality, those of humans being turned into batteries and the menacing sentinels.

Star Wars &#8211, Episode I: The Phantom Menace ( 1999 )

Even the most ardent supporter of The Phantom Menace finds it difficult to fully endorse the effects. So much of the lead up to the movie&#8217, s release hyped the digital worlds that George Lucas created with ILM, and so much of the movie&#8217, s wooden dialogue was blamed on those same artificial sets. Even the most hating fan of prequels must admit that The Phantom Menace looks fantastic despite its flaws.

It&#8217, s not just the pod racing sequence or the climactic lightsaber duel that hold up —even though they both certainly do. The seascape that Obi-Wan Kenobi and Qui-Gon Jinn traverse while visiting the Gungans, as well as the palace where Amidala controls Naboo, are also the quieter elements. All of these elements still impress, even if The Phantom Menace itself remains divisive.

Stuart Little ( 1999) )

Given all the groundbreaking, high-concept movies on this list, it might feel like a bit of a letdown to end with a gentle children&#8217, s movie about a mouse adopted by a human family. Anyone who watches Stuart Little today will find that to be flawless. Like Babe, Stuart Little had to bring animals to life, namely the titular mouse and the various cats he encounters. Also, like Babe, the effects had to be effective to stop the audience’s children from being irritated by the story.

Effects artist Rob Bredow and his team at ILM painstakingly found new methods to create fur and animal expressions that managed to both look realistic and convey emotions. Their efforts received Oscar nominations for the best visual effects ( losing out to The Matrix ) and, more importantly, young viewers ‘ joy, who had no idea they were actually watching a mouse.

The post 1990s CGI Movies That Still Hold Up Today appeared first on Den of Geek.

One of the most successful soft skills we have at our disposal is opinions, in whatever form it takes, and whatever it may be called. It helps us collaborate to improve our designs while developing our own abilities and perspectives.

Feedback is also one of the most underestimated equipment, and generally by assuming that we’re already good at it, we settle, forgetting that it’s a talent that can be trained, grown, and improved. Bad feedback can cause conflict in jobs, lower motivation, and negatively impact faith and teamwork over the long term. Quality opinions can be a revolutionary force.

Practicing our knowledge is absolutely a good way to enhance, but the learning gets yet faster when it’s paired with a good base that programs and focuses the exercise. What are some fundamental components of providing effective opinions? And how can comments be adjusted for rural and distributed job settings?

We can find a long history of sequential comments on the web: code was written and discussed on mailing lists since the beginning of open source. Currently, engineers engage on pull calls, developers post in their favourite design tools, project managers and sprint masters exchange ideas on tickets, and so on.

Design analysis is often the label used for a type of input that’s provided to make our job better, jointly. It generally shares many of the concepts with comments, but it also has some differences.

The material

The content of the feedback is the bedrock of every effective analysis, so where do we need to begin? There are many designs that you can use to form your content. The one that I personally like best—because it’s obvious and actionable—is this one from Lara Hogan.

Although this formula is typically used to provide opinions to individuals, it likewise fits really well in a style criticism because it finally addresses some of the main inquiries that we work on: What? Where? Why? How? Imagine that you’re giving some comments about some pattern function that spans several screens, like an onboard movement: there are some pages shown, a stream blueprint, and an outline of the decisions made. You notice a flaw in the situation. If you keep the three components of the equation in mind, you’ll have a mental unit that can help you become more precise and effective.

Here is a reply that could be included in some feedback, and it might appear fair at first glance because it appears to partially fulfill the requirements. But does it?

Not confident about the keys ‘ patterns and hierarchy—it feels off. Does you alter them?

Observation for style feedback doesn’t really mean pointing out which part of the software your input refers to, but it also refers to offering a viewpoint that’s as specific as possible. Do you offer the user’s viewpoint? Your expert perspective? A business perspective? The perspective of the project manager A first-time user’s perspective?

I anticipate one to go forward and the other to go back when I see these two buttons.

Impact is about the why. Just pointing out a UI element might sometimes be enough if the issue may be obvious, but more often than not, you should add an explanation of what you’re pointing out.

I anticipate one to go forward and the other to go back when I see these two buttons. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow.

The question approach is meant to provide open guidance by eliciting the critical thinking in the designer receiving the feedback. Notably, in Lara’s equation she provides a second approach: request, which instead provides guidance toward a specific solution. While that’s a viable option for general feedback, in my experience, going back to the question approach typically leads to the best solutions because designers are generally more at ease with having an open space to experiment with.

The difference between the two can be exemplified with, for the question approach:

I anticipate one to go forward and the other to go back when I see these two buttons. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Would it make sense to unify them?

Or, for the request approach:

I anticipate one to go forward and the other to go back when I see these two buttons. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same pair of forward and back buttons.

At this point in some situations, it might be useful to integrate with an extra why: why you consider the given suggestion to be better.

I anticipate one to go forward and the other to go back when I see these two buttons. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.

Choosing the question approach or the request approach can also at times be a matter of personal preference. I spent a while working on improving my feedback, conducting anonymous feedback reviews and sharing feedback with others. After a few rounds of this work and a year later, I got a positive response: my feedback came across as effective and grounded. Until I changed teams. Surprise surprise, one particular person gave me a lot of negative feedback. The reason is that I had previously tried not to be prescriptive in my advice—because the people who I was previously working with preferred the open-ended question format over the request style of suggestions. However, there was a member of this other team who preferred specific guidance. So I adapted my feedback for them to include requests.

One comment that I heard come up a few times is that this kind of feedback is quite long, and it doesn’t seem very efficient. No, but also yes. Let’s explore both sides.

No, because of the length in question, this kind of feedback is effective and can provide just enough information for a sound fix. Also if we zoom out, it can reduce future back-and-forth conversations and misunderstandings, improving the overall efficiency and effectiveness of collaboration beyond the single comment. Imagine that in the example above the feedback were instead just,” Let’s make sure that all screens have the same two forward and back buttons”. Since the designer receiving this feedback wouldn’t have much to go by, they might just make the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not make sense anymore. Without explaining the why, the designer might assume that the change is one of consistency, but what if it wasn’t? So there could now be an underlying concern that changing the buttons would be perceived as a regression.

Yes, this style of feedback is not always efficient because the points in some comments don’t always need to be exhaustive, sometimes because certain changes may be obvious (” The font used doesn’t follow our guidelines” ) and sometimes because the team may have a lot of internal knowledge such that some of the whys may be implied.

Therefore, the equation above is intended to serve as a mnemonic to reflect and enhance the practice rather than a strict template for feedback. Even after years of active work on my critiques, I still from time to time go back to this formula and reflect on whether what I just wrote is effective.

The tone

Well-grounded content is the foundation of feedback, but that’s not really enough. The soft skills of the person who’s providing the critique can multiply the likelihood that the feedback will be well received and understood. It has been demonstrated that only positive feedback can lead to sustained change in people. It can be determined by tone alone whether content is rejected or welcomed.

Since our goal is to be understood and to have a positive working environment, tone is essential to work on. I’ve tried to summarize the necessary soft skills over the years using a formula that resembles that of the content receptivity equation.

Respectful feedback comes across as grounded, solid, and constructive. It’s the kind of feedback that, whether it’s positive or negative, is perceived as useful and fair.

The term “timing” describes the moment when the feedback occurs. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. When a new feature’s entire high-level information architecture is about to go live, it might still be relevant if the questioning raises a significant blocker that no one saw, but those concerns are much more likely to have to wait for a later revision. So in general, attune your feedback to the stage of the project. Early iteration? Iteration that was later? Polishing work in progress? Each of these needs a different one. The right timing will make it more likely that your feedback will be well received.

Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. Before writing, it’s important to make sure the person we’re writing will actually benefit them and improve the overall project. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Although it’s possible, and that’s okay, it’s hoped not to be the case. Acknowledging and owning that can help you make up for that: how would I write if I really cared about them? How can I avoid being passive aggressive? How can I be more helpful?

Form is relevant especially in a diverse and cross-cultural work environments because having great content, perfect timing, and the right attitude might not come across if the way that we write creates misunderstandings. There could be many reasons for this, including the fact that occasionally certain words may cause specific reactions, that non-native speakers may not be able to comprehend all thenuances of some sentences, that our brains may be different, and that we may perceive the world differently. Neurodiversity is a requirement. Whatever the reason, it’s important to review not just what we write but how.

A few years back, I was asking for some feedback on how I give feedback. I was given some helpful advice, but I also found a surprise in my comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That wasn’t my intention at all! I felt really bad, and I just realized that I provided feedback to them for months, and every time I might have made them feel stupid. I was horrified … but also thankful. I quickly changed my situation by adding “oh” to my list of replaced words (your choice between aText, TextExpander, or others ) so that when I typed “oh,” it was immediately deleted.

Something to highlight because it’s quite frequent—especially in teams that have a strong group spirit—is that people tend to beat around the bush. It’s important to keep in mind that having a positive attitude doesn’t necessarily mean passing judgment on the feedback; rather, it simply means that even when you give difficult, or difficult feedback, you do so in a way that’s respectful and constructive. The nicest thing that you can do for someone is to help them grow.

We have a great advantage in giving feedback in written form: it can be reviewed by another person who isn’t directly involved, which can help to reduce or remove any bias that might be there. When I shared a comment with someone I knew,” How does this sound,”” How can I do it better,” or even” How would you have written it,” I discovered that the two versions had different meanings.

The format

Asynchronous feedback also has a significant inherent benefit: it allows us to spend more time making sure that the suggestions ‘ clarity and actionability meet two main objectives.

Let’s imagine that someone shared a design iteration for a project. You are reviewing it and leaving a comment. Let’s try to think about some factors that might be helpful to consider, as there are many ways to accomplish this, and context is of course a factor.

In terms of clarity, start by grounding the critique that you’re about to give by providing context. This includes specifically describing where you’re coming from: do you have a thorough understanding of the project, or is this your first encounter with it? Are you coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s point of view do you consider when providing feedback? Is the design iteration at a point where it would be okay to ship this, or are there major things that need to be addressed first?

Even if you’re giving feedback to a team that already has some background information on the project, providing context is helpful. And context is absolutely essential when giving cross-team feedback. If I were to review a design that might be indirectly related to my work, and if I had no knowledge about how the project arrived at that point, I would say so, highlighting my take as external.

We frequently concentrate on the negatives and attempt to list all the things that could be improved. That’s of course important, but it’s just as important—if not more—to focus on the positives, especially if you saw progress from the previous iteration. Although this may seem superfluous, it’s important to remember that design has a number of possible solutions to each problem. So pointing out that the design solution that was chosen is good and explaining why it’s good has two major benefits: it confirms that the approach taken was solid, and it helps to ground your negative feedback. In the longer term, sharing positive feedback can help prevent regressions on things that are going well because those things will have been highlighted as important. Positive feedback can also help to lessen impostor syndrome as an added bonus.

There’s one powerful approach that combines both context and a focus on the positives: frame how the design is better than the status quo ( compared to a previous iteration, competitors, or benchmarks ) and why, and then on that foundation, you can add what could be improved. There is a significant difference between a critique of a design that is already in good shape and one that isn’t quite there yet.

Another way that you can improve your feedback is to depersonalize the feedback: the comments should always be about the work, never about the person who made it. It’s” This button isn’t well aligned” versus” You haven’t aligned this button well”. This can be changed in your writing very quickly by reviewing it just before sending.

In terms of actionability, one of the best approaches to help the designer who’s reading through your feedback is to split it into bullet points or paragraphs, which are easier to review and analyze one by one. You might also think about breaking up the feedback into sections or even across multiple comments if it is longer. Of course, adding screenshots or signifying markers of the specific part of the interface you’re referring to can also be especially useful.

One approach that I’ve personally used effectively in some contexts is to enhance the bullet points with four markers using emojis. A red square indicates that it is something I consider blocking, a yellow diamond indicates that it should be changed, and a green circle indicates that it is fully confirmed. I also use a blue spiral � � for either something that I’m not sure about, an exploration, an open alternative, or just a note. However, I’d only use this strategy on teams where I’ve already established a high level of trust because it might turn out to be quite demoralizing if I deliver a lot of red squares, and I’d have to reframe how I’d communicate that.

Let’s see how this would work by reusing the example that we used earlier as the first bullet point in this list:

• 🔶 Navigation—I anticipate one to go forward and the other to go back when I see these two buttons. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
• � � Overall— I think the page is solid, and this is good enough to be our release candidate for a version 1.0.
• � � Metrics—Good improvement in the buttons on the metrics area, the improved contrast and new focus style make them more accessible.
• Button Style: Using the green accent in this context gives the impression that it’s a positive action because green is typically seen as a confirmation color. Do we need to explore a different color?
• Tiles—It seems to me that the tiles should use the Subtitle 2 style rather than the Subtitle 1 style given the number of items on the page and the overall page hierarchy. This will keep the visual hierarchy more consistent.
• � � Background—Using a light texture works well, but I wonder whether it adds too much noise in this kind of page. What is the purpose of using that?

What about giving feedback directly in Figma or another design tool that allows in-place feedback? These are generally difficult to use because they conceal discussions and are harder to follow, but in the right setting, they can be very effective. Just make sure that each of the comments is separate so that it’s easier to match each discussion to a single task, similar to the idea of splitting mentioned above.

One final note: say the obvious. Sometimes we might feel good or bad about something, so we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. You might have to reword it a little bit to make the reader feel more comfortable, but don’t hold it back. Good feedback is transparent, even when it may be obvious.

Another benefit of asynchronous feedback is that written feedback automatically monitors decisions. Especially in large projects,” Why did we do this”? There’s nothing better than open, transparent discussions that can be reviewed at any time, and this could be a question that arises from time to time. For this reason, I recommend using software that saves these discussions, without hiding them once they are resolved.

Content, tone, and format. Although each of these subjects offers a useful model, focusing on eight areas, including observation, impact, question, timing, attitude, form, clarity, and actionability, is a lot of work at once. One effective approach is to take them one by one: first identify the area that you lack the most (either from your perspective or from feedback from others ) and start there. Then the second, followed by the third, and so on. At first you’ll have to put in extra time for every piece of feedback that you give, but after a while, it’ll become second nature, and your impact on the work will multiply.

Thanks to Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

” Any feedback?” is perhaps one of the worst ways to ask for opinions. It’s obscure and unfocused, and it doesn’t give us a sense of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

When we realize that receiving input can be seen as a form of design study, it might seem counterintuitive to begin the process with a question. In the same way that we wouldn’t perform any studies without the correct questions to get the insight that we need, the best way to ask for feedback is also to build strong issues.

Design criticism is never a one-time procedure. Sure, any great comments process continues until the project is finished, but this is especially true for layout because architecture work continues iteration after iteration, from a high level to the finest details. Each stage requires its unique set of questions.

And suddenly, as with any great research, we need to examine what we got up, get to the base of its perspectives, and take action. Iteration, evaluation, and problem. This look at each of those.

The query

Being available to input is important, but we need to be specific about what we’re looking for. Any comments,” What do you think,” or” I’d love to hear your mind” at the end of a presentation are likely to garner a lot of different ideas, or worse, to make people follow the lead of the first speaker. And next… we get frustrated because vague issues like those can change a high-level moves review into folks rather commenting on the borders of buttons. Which theme may be important, so it might be difficult to get the team to pay attention to it.

But how do we get into this scenario? It’s a combination of various components. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to keep the question open and assume that everyone else will agree. Another is that in nonprofessional debate, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the issues, and we don’t make any improvements to them.

The work of asking good questions guidelines and focuses the criticism. It also serves as a form of acceptance, outlining your willingness to make remarks and the types of comments you want to receive. It puts people in the right emotional state, especially in situations when they weren’t expecting to give opinions.

There isn’t a second best method to request feedback. It simply needs to be certain, and sensitivity can take several shapes. The level than depth model for design critique has been a particularly helpful tool for my coaching.

” Stage” refers to each of the actions of the process—in our event, the design process. The kind of feedback changes as the consumer research moves forward to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed opinions into updated designs as the job has evolved. The layers of user experience could serve as a starting point for future inquiries. What do you want to know: Project objectives? user requirements? Functionality? Content? Interaction design? Information architecture UI design? navigation planning Visual design? Branding?

Here’re a few example questions that are precise and to the point that refer to different layers:

• Functionality: Is it desirable to automate account creation?
• Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
• Information architecture: This page contains two competing pieces of information. Is the structure effective in communicating them both?
• User interface design: What do you think about the error counter at the top of the page, which makes sure you see the next error even if it is outside the viewport?
• Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Do you have any suggestions for how to handle this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

The other axis of specificity is determined by how far you’d like to go with the information being presented. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially helpful from one iteration to the next when it’s crucial to highlight the areas that have changed.

There are other things that we can consider when we want to achieve more specific—and more effective—questions.

A quick fix is to get rid of the generic qualifiers from questions like “good,” “well,” “nice,” “bad,” “okay,” and” cool.” For example, asking,” When the block opens and the buttons appear, is this interaction good”? is it possible to look specific, but you can spot the “good” qualifier and make the question” When the block opens and the buttons appear, is it clear what the next action is” look like?

Sometimes we actually do want broad feedback. Although that’s uncommon, it can occur. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or perhaps you should just say,” At first glance, what do you think”? so that it’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

Sometimes the project is particularly broad, and some areas may have already been thoroughly explored. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. Although it’s not something I’d recommend in general, I’ve found it helpful in avoiding getting back into rabbit holes like those that could lead to even more refinement if what’s important right now isn’t.

Asking specific questions can completely change the quality of the feedback that you receive. People who have less refined critique abilities will now be able to provide more useful feedback, and even experienced designers will appreciate the clarity and effectiveness gained from concentrating solely on what is required. It can save a lot of time and frustration.

The iteration

Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Many design tools have inline commenting, but many of them only display changes as a single fluid stream in the same file. These types of design tools cause conversations to end after they are resolved, update shared UI components automatically, and require designers to always display the most recent version unless these would-be useful features were manually disabled. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That approach to design critiques is probably not the best approach, but some teams might benefit from it even if I don’t want to be too prescriptive.

The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. Any platform that can accommodate this type of structure can use this. By the way, when I refer to a “write-up or presentation“, I’m including video recordings or other media too: as long as it’s asynchronous, it works.

There are many benefits to using iteration posts:

• It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
• Decisions are made immediately available for future review, and conversations are also always available.
• It creates a record of how the design changed over time.
• It might also make it simpler to collect and act on feedback depending on the tool.

These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. From there, there can be additional feedback techniques ( such as live critique, pair designing, or inline comments ).

I don’t think there’s a standard format for iteration posts. However, there are a few high-level elements that make sense to include as a baseline:

1. The goal
2. The layout
3. The list of changes
4. The querys

Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. In every iteration post, I would copy and paste this, so I could do it again. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple posts. The most recent iteration post will have everything I need if I want to know about the most recent design.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts is actually very effective at ensuring that everyone is on the same page.

The design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. In essence, it’s any design work. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger picture.

It might also be helpful to have clear names on the objects since it makes them look better to refer to. Write the post in a way that helps people understand the work. It’s not much different from creating a strong live presentation.

For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

Finally, as mentioned earlier, it’s crucial that you include a list of the questions to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question by its number.

Not every iteration is the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then, later, the iterations begin coming to a decision and improving it until the feature development is complete.

I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be just a concept to start a conversation, or it might be a cumulative list of all the features that have been added gradually over the course of each iteration until the full picture is achieved.

Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. Although this may seem like a minor labeling tip, it can be useful in many ways:

• Unique—It’s a clear unique marker. Everyone knows where to go to review things, and it’s simple to say” This was discussed in i4″ with each project.
• Unassuming—It works like versions ( such as v1, v2, and v3 ) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Exploratory, incomplete, or partial should be the definition of an argument.
• Future proof—It resolves the “final” naming problem that you can run into with versions. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

The wording release candidate (RC ) could be used to indicate when a design is finished enough to be worked on, even if there are some areas that still need improvement and, in turn, require more iterations, such as” with i8 we reached RC” or “i12 is an RC” to indicate when it is finished.

The review

What typically occurs during a design critique is an open discussion that can be very productive between two people. This approach is particularly effective during live, synchronous feedback. However, when we work asynchronously, using a different approach is more effective: we can adopt a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

Asynchronous feedback is particularly effective around these friction points because of this shift’s significant benefits:

1. It removes the pressure to reply to everyone.
2. It lessens the annoyance of snoop-by comments.
3. It lessens our personal stake.

The first friction is being forced to respond to every comment. Sometimes we write the iteration post, and we get replies from our team. It’s simple, straightforward, and doesn’t cause any issues. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the respondent is a stakeholder or a person who is directly involved in the project and whom we feel we need to speak with. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Responding to all comments at times can be effective, but when we consider a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives in asynchronous spaces:

One is to let the next iteration speak for itself. That is the response when the design changes and we publish a follow-up iteration. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
• Another option is to respond politely to acknowledge each comment, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. These will be included in the upcoming iteration. In some cases, this could also be just a single top-level comment along the lines of” Thanks for all the feedback everyone—the next iteration is coming soon”!
• Another option is to provide a quick summary of the comments before moving on. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

The swoop-by comment, which is the kind of feedback that comes from a member of a team or non-project who might not be aware of the context, restrictions, decisions, or requirements, or of the discussions from earlier iterations, is the second friction point. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. It can be annoying to have to repeat the same response repeatedly in swoop-by comments.

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, if responding to a previously litigated point is useful, a brief response with a link to the previous discussion for additional information is typically sufficient. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

Swoop-by commenting can still be useful for two reasons: first, they might point out something that isn’t clear, and second, they might have the power to fit in with a user’s perspective when they are seeing the design for the first time. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

The personal stake we might have in relation to the design could be the third friction point, which might cause us to feel defensive if the review turned out to be more of a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego ( because yes, even if we don’t want to admit it, it’s there ). In the end, presenting everything in aggregated form helps us to prioritize our work more.

Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You must examine it and come to a decision that can be justified, but sometimes “no” is the best choice.

As the designer leading the project, you’re in charge of that decision. In the end, everyone has their area of specialization, and the designer is the one with the most background and knowledge to make the right choice. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

Thanks to Mike Shelton and Brie Anne Demkiw for their contributions to the initial draft of this article.

Although I’m not certain when I first heard this statement, it has stuck with me over the centuries. How do you generate solutions for scenarios you can’t think? Or create products that are functional on products that have not yet been created?

Flash, Photoshop, and flexible pattern

When I first started designing sites, my go-to technology was Photoshop. I created a design for a 960px paint that I would later add willing to. The growth phase was about attaining pixel-perfect reliability using set widths, fixed levels, and absolute placement.

All of this was altered by Ethan Marcotte’s speak at An Event Apart and the subsequent article in A Checklist Off in 2010. I was sold on responsive pattern as soon as I heard about it, but I was even terrified. The pixel-perfect models full of special figures that I had formerly prided myself on producing were no longer good enough.

My first encounter with flexible design didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. You can’t really put responsiveness at the end of a job, which I learned the hard way. To make smooth design, you need to prepare throughout the style stage.

A new way to style

Making information accessible to all devices a priority when designing responsive or smooth websites has always been the goal. It relies on the use of percentage-based design, which I immediately achieved with local CSS and power groups:

.column-span-6 { width: 49%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-4 { width: 32%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-3 { width: 24%; float: left; margin-right: 0.5%; margin-left: 0.5%;}

Therefore with Sass but that I could use @includes to re-use repeated blocks of code and transition to more semantic premium:

.logo { @include colSpan(6);}.search { @include colSpan(3);}.social-share { @include colSpan(3);}

Media concerns

The next ingredient for flexible design is press queries. Without them, regardless of whether the content remained readable, would shrink to fit the available space. ( The exact opposite issue developed with the introduction of a mobile-first approach. )

Media concerns prevented this by allowing us to add breakpoints where the design could adapt. Like most people, I started out with three breakpoints: one for desktop, one for tablets, and one for mobile. Over the years, I added more and more for phablets, wide screens, and so on. 

For years, I happily worked this way and improved both my design and front-end skills in the process. The only problem I encountered was making changes to content, since with our Sass grid system in place, there was no way for the site owners to add content without amending the markup—something a small business owner might struggle with. This is because each row in the grid was defined using a div as a container. Adding content meant creating new row markup, which requires a level of HTML knowledge.

String premium was a mainstay of early flexible design, present in all the frequently used systems like Bootstrap and Skeleton.

 
1 of 7
 
2 of 7
 
3 of 7
 
4 of 7
 
5 of 7
 
6 of 7
 
7 of 7

Another difficulty arose as I moved from a design firm building websites for little- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those positions, I began to work more frequently with recyclable parts.

Our rely on multimedia queries resulted in parts that were tied to frequent window sizes. If the goal of part libraries is modify, then this is a real problem because you can just use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process never really hitting that “devices that don’t already occur” goal.

Then there’s the problem of space. Media concerns allow components to adapt based on the viewport size, but what if I put a component into a sidebar, like in the figure below?

Container queries: our savior or a false dawn?

Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. Although there are JavaScript workarounds, they can lead to dependability and compatibility issues. The basic theory underlying container queries is that elements should change based on the size of their parent container and not the viewport width, as seen in the following illustrations.

One of the biggest arguments in favor of container queries is that they help us create components or design patterns that are truly reusable because they can be picked up and placed anywhere in a layout. This is an important step in moving toward a form of component-based design that works at any size on any device.

In other words, responsive elements are meant to replace responsive layouts.

Container queries will help us move from designing pages that respond to the browser or device size to designing components that can be placed in a sidebar or in the main content, and respond accordingly.

My issue is that layout is still used to determine when a design needs to adapt. This approach will always be restrictive, as we will still need pre-defined breakpoints. For this reason, my main question with container queries is, How would we decide when to change the CSS used by a component?

The best place to make that choice is probably not a component library that is disconnected from context and real content.

As the diagrams below illustrate, we can use container queries to create designs for specific container widths, but what if I want to change the design based on the image size or ratio?

In this example, the dimensions of the container are not what should dictate the design, rather, the image is.

Without reliable cross-browser support for them, it’s difficult to say for certain whether container queries will be successful. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might always need to modify these elements to fit our content.

CSS is changing

Whilst the container query debate rumbles on, there have been numerous advances in CSS that change the way we think about design. The days of fixed-width elements measured in pixels and floated div elements used to cobble layouts together are long gone, consigned to history along with table layouts. Flexbox and CSS Grid have revolutionized layouts for the web. We can now create elements that wrap onto new rows when they run out of space, not when the device changes.

.wrapper { display: grid; grid-template-columns: repeat(auto-fit, 450px); gap: 10px;}

The repeat() function paired with auto-fit or auto-fill allows us to specify how much space each column should use while leaving it up to the browser to decide when to spill the columns onto a new line. Similar things can be achieved with Flexbox, as elements can wrap over multiple rows and “flex” to fill available space. 

.wrapper { display: flex; flex-wrap: wrap; justify-content: space-between;}.child { flex-basis: 32%; margin-bottom: 20px;}

You don’t need to wrap elements in container rows, which is the biggest benefit of all of this. Without rows, content isn’t tied to page markup in quite the same way, allowing for removals or additions of content without additional development.

This is a big step forward when it comes to creating designs that allow for evolving content, but the real game changer for flexible designs is CSS Subgrid.

Remember the days of crafting perfectly aligned interfaces, only for the customer to add an unbelievably long header almost as soon as they’re given CMS access, like the illustration below?

Subgrid allows elements to respond to adjustments in their own content and in the content of sibling elements, helping us create designs more resilient to change.

.wrapper { display: grid; grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); grid-template-rows: auto 1fr auto; gap: 10px;}.sub-grid { display: grid; grid-row: span 3; grid-template-rows: subgrid; /* sets rows to parent grid */}

CSS Grid allows us to separate layout and content, thereby enabling flexible designs. Meanwhile, Subgrid allows us to create designs that can adapt in order to suit morphing content. Subgrid is only supported in Firefox at the time of writing, but the above code can be implemented behind an @supports feature query.

Intrinsic layouts

I’d be remiss not to mention intrinsic layouts, a term used by Jen Simmons to describe a mix of contemporary and traditional CSS features used to create layouts that respond to available space.

Responsive layouts have flexible columns using percentages. Intrinsic layouts, on the other hand, use the fr unit to create flexible columns that won’t ever shrink so much that they render the content illegible.

frunits is a statement that says,” I want you to distribute the extra space in this way, but never make it smaller than the content that is inside.”

—Jen Simmons,” Designing Intrinsic Layouts”

Intrinsic layouts can also make use of a mix of fixed and flexible units, letting the content choose how much space it occupies.

What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Without having the same breakpoints or the same amount of content as in the previous implementation, components and patterns can be lifted and reused.

We can now create designs that adapt to the space they have, the content within them, and the content around them. We can create responsive components without relying on container queries using an intrinsic approach.

Another 2010 moment?

This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. It’s another “everything changed” moment for me.

But it doesn’t seem to be moving quite as fast, I haven’t yet had that same career-changing moment I had with responsive design, despite the widely shared and brilliant talk that brought it to my attention.

One possible explanation for that is that I now work for a sizable company, which is quite different from the role I held as a design agency in 2010! In my agency days, every new project was a clean slate, a chance to try something new. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase.

Another possibility is that I now feel more prepared for change. In 2010 I was new to design in general, the shift was frightening and required a lot of learning. Additionally, an intrinsic approach isn’t exactly new; it’s a different way to use existing skills and CSS knowledge.

You can’t framework your way out of a content problem

Another reason for the slightly slower adoption of intrinsic design could be the lack of quick-fix framework solutions available to kick-start the change.

Ten years ago, responsive grid systems were everywhere. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

Because having a selection of units is a hindrance when creating layout templates, intrinsic design and frameworks do not work together quite as well. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.

And then there are design tools. We probably all used Photoshop templates for desktop, tablet, and mobile devices to drop designs into and show how the site would appear throughout our careers at some point.

How do you do that now, with each component responding to content and layouts flexing as and when they need to? Personally, I’m a big fan of this kind of design in the browser.

The debate about “whether designers should code” is another that has rumbled on for years. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. It’s not ideal to do this in a graphics-based software package. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it continue to function? Is the design too reliant on the current content?

Personally, I look forward to the day intrinsic design is the standard for design, when a design component can be truly flexible and adapt to both its space and content with no reliance on device or container dimensions.

Content should come first

Content is not constant. After all, to design for the unanticipated or unexpected, we must take into account content modifications, such as the earlier Subgrid card example, which allowed the cards to adjust both their own content and that of their sibling elements.

Thankfully, there’s more to CSS than layout, and plenty of properties and values can help us put content first. Subgrid and pseudo-elements like ::first-line and ::first-letter help to separate design from markup so we can create designs that allow for changes.

This is not the same as previous markup hacks like this.

 First line of text with different styling...

—we can target content based on where it appears.

.element::first-line { font-size: 1.4em;}.element::first-letter { color: red;}

Much bigger additions to CSS include logical properties, which change the way we construct designs using logical dimensions (start and end) instead of physical ones (left and right), something CSS Grid also does with functions like min(), max(), and clamp().

This flexibility allows for directional changes according to content, a common requirement when we need to present content in multiple languages. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.

Directional variables must be specified in the Sass version.

$direction: rtl;$opposite-direction: ltr;$start-direction: right;$end-direction: left;

These variables can be used as values—

body { direction: $direction; text-align: $start-direction;}

—or as real estate.

margin-#{$end-direction}: 10px;padding-#{$start-direction}: 10px;

However, now we have native logical properties, removing the reliance on both Sass ( or a similar tool ) and pre-planning that necessitated using variables throughout a codebase. These properties also start to break apart the tight coupling between a design and strict physical dimensions, creating more flexibility for changes in language and in direction.

margin-block-end: 10px;padding-block-start: 10px;

There are also native start and end values for properties like text-align, which means we can replace text-align: right with text-align: start.

Like the earlier examples, these properties help to build out designs that aren’t constrained to one language, the design will reflect the content’s needs.

Fluid and fixed

We briefly covered the power of combining fixed widths with fluid widths with intrinsic layouts. The min() and max() functions are a similar concept, allowing you to specify a fixed value with a flexible alternative. 

For min() this means setting a fluid minimum value and a maximum fixed value.

.element { width: min(50%, 300px);}

The element in the figure above will be 50 % of its container as long as the element’s width doesn’t exceed 300px.

For max() we can set a flexible max value and a minimum fixed value.

.element { width: max(50%, 300px);}

Now the element will be 50 % of its container as long as the element’s width is at least 300px. This means we can set limits but allow content to react to the available space.

The clamp() function builds on this by allowing us to set a preferred value with a third parameter. Now we can allow the element to shrink or grow if it needs to without getting to a point where it becomes unusable.

.element { width: clamp(300px, 50%, 600px);}

This time, the element’s width will be 50 % of its container’s preferred value, with no exceptions for 300px and 600px.

With these techniques, we have a content-first approach to responsive design. We can separate content from markup, meaning the changes users make will not affect the design. By making plans for unanticipated changes in language or direction, we can begin to future-proof designs. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

Situation first

Thanks to what we’ve discussed so far, we can cover device flexibility by changing our approach, designing around content and space instead of catering to devices. But what about that last bit of Jeffrey Zeldman’s quote,”… situations you haven’t imagined”?

Rather than someone using a mobile phone and moving through a crowded street in glaring sunshine, it’s a very different design to be done for someone using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

Choice is so crucial because of this. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.

Thankfully, there is a lot we can do to provide choice.

Responsible design

” There are parts of the world where mobile data is prohibitively expensive, and where there is little or no broadband infrastructure”.

” I Used the Web for a Day on a 50 MB Budget“

Chris Ashton

One of the biggest assumptions we make is that people interacting with our designs have a good wifi connection and a wide screen monitor. However, our users may be commuters using smaller mobile devices that may experience drops in connectivity while traveling on trains or other modes of transportation. There is nothing more frustrating than a web page that won’t load, but there are ways we can help users use less data or deal with sporadic connectivity.

The srcset attribute allows the browser to decide which image to serve. This means we can create smaller ‘cropped’ images to display on mobile devices in turn using less bandwidth and less data.

The preload attribute can also help us to think about how and when media is downloaded. It can be used to tell a browser about any critical assets that need to be downloaded with high priority, improving perceived performance and the user experience. 

There’s also native lazy loading, which indicates assets that should only be downloaded when they are needed.

With srcset, preload, and lazy loading, we can start to tailor a user’s experience based on the situation they find themselves in. What none of this does, however, is allow the user themselves to decide what they want downloaded, as the decision is usually the browser’s to make. 

So how can we put users in control?

The return of media inquiries

Media concerns have always been about much more than device sizes. They allow content to adapt to different situations, with screen size being just one of them.

We’ve long been able to check for media types like print and speech and features such as hover, resolution, and color. These checks allow us to provide options that suit more than one scenario, it’s less about one-size-fits-all and more about serving adaptable content.

The Level 5 spec for Media Queries is still being developed at this writing. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

For instance, there is a light-level feature that enables you to alter a user’s style when they are in the sun or the darkness. Paired with custom properties, these features allow us to quickly create designs or themes for specific environments.

@media (light-level: normal) { --background-color: #fff; --text-color: #0b0c0c; }@media (light-level: dim) { --background-color: #efd226; --text-color: #0b0c0c;}

Another key feature of the Level 5 spec is personalization. Instead of creating designs that are the same for everyone, users can choose what works for them. This is achieved by using features like prefers-reduced-data, prefers-color-scheme, and prefers-reduced-motion, the latter two of which already enjoy broad browser support. These features tap into preferences set via the operating system or browser so people don’t have to spend time making each site they visit more usable. 

Media concerns like this go beyond choices made by a browser to grant more control to the user.

Expect the unexpected

In the end, the one thing we should always anticipate is that things will change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

We can design for content, but we can’t do it for this constantly changing landscape. By putting content first and allowing that content to adapt to whatever space surrounds it, we can create more robust, flexible designs that increase the longevity of our products.

A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. There are still many more things we can do to adopt a more intrinsic approach, from responsive to fluid and fixed. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.

When it comes to unexpected circumstances, we need to make sure our goods are accessible whenever and wherever needed. We can move closer to achieving this by involving users in our design decisions, by creating choice via browsers, and by giving control to our users with user-preference-based media queries.

Good design for the unexpected should allow for change, provide choice, and give control to those we serve: our users themselves.

We’ve been conversing for many thousands of years. Whether to present information, perform transactions, or just to check in on one another, people have yammered aside, chattering and gesticulating, through spoken discussion for many generations. Only recently have we begun to write our conversations, and only recently have we outsourced them to the system, a system that exhibits a far greater affection for written communications than for the vernacular rigors of spoken speech.

Laptops have trouble because between spoken and written speech, talk is more primitive. Machines must wrestle with the complexity of human statement, including the disfluencies and pauses, the gestures and body speech, and the variations in expression choice and spoken dialect, which may impede even the most skillfully crafted human-computer interaction. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret visual interpersonal cues.

In contrast, written language develops its own fossil record of dated terms and phrases as we commit to recording and keeping usages long after they are no longer relevant in spoken communication ( for example, the salutation” To whom it may concern” ). Because it tends to be more consistent, smooth, and proper, written word is necessarily far easier for machines to interpret and know.

Spoken language is not a luxury in this regard. Besides the nonverbal cues that decorate conversations with emphasis and emotional context, there are also verbal cues and vocal behaviors that modulate conversation in nuanced ways: how something is said, not what. Our spoken language conveys much more than the written word could ever contain, whether it be rapid-fire, low-pitched, or high-decibel, sarcastic, stilted, or sighing. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

Voice Compositions

We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too ( ). We typically strike up a conversation as a result:

• we need something done ( such as a transaction ),
• we want to know something, some kind of information, or
• we are social beings and want someone to talk to ( conversation for conversation’s sake ).

A single conversation from beginning to end that achieves some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface, also fits into these three categories, which I refer to as transactional, informational, and prosocial. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but it must not be one particular voice interaction.

Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. Additionally, there is ongoing debate about whether users actually prefer the type of organic human conversation that starts with a prosocial voice and progresses seamlessly into new ones. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users ‘ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ( ).

That leaves two different types of conversations we can have with one another that a voice interface can also have easily, including one that is transactional and one that is informational, teaching us something new ( “discuss a musical” ).

Transactional voice interactions

When you order a Hawaiian pizza with extra pineapple, you’re typically having a conversation and a voice interaction when you’re tapping buttons on a food delivery app. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza ( generously topped with pineapple, as it should be ).

Alison: Hey, how are things going?

Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Alison, can I get a pineapple-onion pizza in Hawaii?

Burhan: Sure, what size?

Large, Alison.

Burhan: Anything else?

Alison: No thanks, that’s it.

Burhan: Something to drink?

I’ll have a bottle of Coke, Alison.

Burhan: You got it. That will cost$ 13.55 and take about fifteen minutes.

Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Transactional conversations exhibit a few key characteristics: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Alison might only want to place an order at Crust Deluxe, but she might not want to leave without a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. We’re after much more than just a prosocial mini-conversation at the beginning, even though we do it once more to establish politeness.

Alison: Hey, how are things going?

Burhan: Hi, welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

Alison, do you have any menu items that are halal?

Burhan: Absolutely! On request, we can make any pie halal. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you considering any additional dietary restrictions?

Alison: What about gluten-free pizzas?

Burhan: For both our deep-dish and thin-crust pizzas, we can definitely make a gluten-free crust for you, without a problem. Anything else I can answer for you?

Alison: That’s it for now. Good to know. Thank you.

Burhan: Anytime, come back soon!

This dialogue is radically different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions that seek the truth through information gathering. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. Responses are typically longer, more in-depth, and carefully communicated to ensure that the customer understands the main ideas.

Voice Interfaces

Voice interfaces, in essence, use speech to assist users in accomplishing their objectives. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned with pure voice interfaces, which are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with because multimodal voice interfaces can lean on visual components like screens as crutches.

Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.

IVR ( interactive voice response ) systems

Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged in the early 1990s with text-to-speech ( TTS ) dictation programs that recited written text aloud, as well as speech-enabled in-car systems that gave directions to a user-provided address. We became familiar with the first real voice interfaces that could actually be spoken with the help of interactive voice response ( IVR ) systems, which were developed as an alternative to overburdened customer service representatives.

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. When you call an airline or hotel company, which is a common practice in the corporate world, these systems were primarily intended as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), which are more likely to happen when you call one. Despite their functional issues and users ‘ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

IVR systems have a reputation for having less scintillating conversation than we’re used to in real life ( or even in science fiction ), but they are great for highly repetitive, monotonous conversations that typically don’t veer from a single format.

Screen readers

The screen reader, a program that converts visual information into synthesized speech, was a development that accompanied the development of IVR systems. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. The most recent version of a voice-over-text format of content delivery is probably the one that is closest to it.

Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 ( ). In the same year, Jim Thatcher created the first IBM Screen Reader for text-based computers, which was later reworked for computers with graphical user interfaces ( GUIs ) ( ).

With the rapid growth of the web in the 1990s, the demand for accessible tools for websites exploded. Screen readers started facilitating quick interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one with the introduction of semantic HTML and especially ARIA roles in 2008, allowing them to do so in an aural and temporal space. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. in A List Apart, writes Aaron Gustafson, “into useful information.” ” At least they do when documents are authored thoughtfully” ( ).

There’s a big deal with screen readers: they’re difficult to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. Working with web-based interfaces takes a cognitive toll for many screen reader users.

In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

I disliked the operation of Screen Readers from the beginning. Why are they designed the way they are? It makes no sense to present information visually and then only to have that information translated into audio. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. ( )

In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, users of the visual interface have the advantage of freely scurrying around the viewport to find information, ignoring areas that are unimportant to them. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might benefit from more streamlined user interfaces, especially more advanced voice assistants.

Voice assistants

Many of us immediately associate voice assistants with the popular subset of voice interfaces found in living rooms, smart homes, and offices with the film A Space Odyssey or with Majel Barrett’s voice as the omniscient computer from Star Trek. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And because of their assistive potential, they are quickly gaining more and more attention from accessibility advocates.

Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others created their vision for a” semantic web agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” ( hinter paywall ). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

There are a lot of variations in the programmability and customization of some voice assistants compared to others ( Fig. 1 ). As a result of the breadth of voice assistants available today ( Fig. 1 ). At one extreme, everything except vendor-provided features is locked down, for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond their existing capabilities. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, which are still unavoidable today.

At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, developers who feel stifled by the limitations of Siri and Cortana are increasingly using programmable voice assistants that allow for customization and extensibility. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Users of the Amazon Alexa and Google Assistant ecosystems can choose from among the thousands of custom-built skills available today.

As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they’re also selling and open-sourcing an unheard array of tools and frameworks for designers and developers that aim to make creating voice interfaces as simple as possible, even without code.

Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. In contrast, many development platforms, such as Google’s Dialogflow, have omnichannel capabilities that allow users to create a single conversational interface that then becomes a voice interface, textual chatbot, and IVR system upon deployment. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.

Voice content

Simply put, voice content is content delivered through voice. Voice content must be free-flowing, organic, contextless, and concise in order to preserve what makes human conversation so compelling in the first place.

Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. We’re most concerned with the content in this book being delivered auditorically, not as an option but as a necessity.

For many of us, our first foray into informational voice interfaces will be to deliver content to users. There is only one issue: any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice-activated text?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, massive vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window while being viewed in microfilm format in newspaper archives. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:

An example of microcontent can be a day’s weather forecast [sic], the arrival and departure times for an airplane flight, an abstract from a lengthy publication, or a single instant message. ( )

I would update Dash’s definition of microcontent to include all instances of bite-sized content that transcends written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. The best way to learn how your content can be stretched to the limits of its potential is through microcontent, which will inform both established and new delivery channels.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly see when the next train is coming from a digital sign underground, but voice interfaces keep our attention occupied for so long that screen reader users are all too familiar.

Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.

Fundamentally, how voice content manifests in perceived time and space both affect the legibility and discoverability of our voice content.

In the 1950s, some members of the elite running group had come to accept the idea that it was impossible to run a hour in less than four hours. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.

However, on May 6, 1956, Roger Bannister caught people by surprise. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.

The world then knew that the four-minute hour was possible because of this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Therefore, in the same race, three athletes all managed to cross the four-minute challenge. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

We accomplish a lot more when we think something is possible, and we only think it can be done when we see someone else doing it after all. As for human running speed, we also think there are the strictest requirements for how a website should do.

Establishing requirements for a green website

The key indicators of climate performance in most big sectors are pretty well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. However, in the world of websites and apps, we aren’t held to any specific environmental standards, and we have only recently developed the tools and methods we need to also conduct an environmental assessment.

The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the CO₂ output of a website product. We didn’t measure the pollutants coming out of the exhaust valves on our laptops. The pollution coming from power plants that burn coal and oil are considerably away, out of sight, and out of mind. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. What then do we do?

If we can‘t measure the actual carbon emissions, then we need to get what we can estimate. The following are the main elements that could be used as coal pollution gauges:

1. Transfer of data
2. Electricity’s carbon power

Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.

Transfer of data

Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a great example of how much energy is consumed and how much carbon is released. As a rule of thumb, the more data transferred, the more energy used in the data center, telecoms networks, and end user devices.

The most accurate way to calculate data transfer for a single visit for web pages is to measure the page weight, which is the first time a user visits the page in kilobytes. It’s fairly easy to measure using the developer tools in any modern web browser. Frequently, any web application’s overall data transfer statistics will be included in your web hosting account ( Fig. 2.1 ).

The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes.

A large scope is required to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for roughly half of this data transfer, making them the single biggest contributor to carbon emissions on the typical website.

History clearly shows us that our web pages can be smaller, if only we set our minds to it. While most technologies, including the underlying technology of the web like data centers and transmission networks, become more and more energy efficient, websites themselves become less effective as time goes on.

You might be aware of the idea behind performance budgeting as a method for directing a project team to deliver faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than vague suggestions, much like speed limits while driving, so the goal should always be to come in within budget.

Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Page weight and transfer size are more objective and reliable benchmarks for sustainable web design, whereas web performance often depends more on the user’s perception of load times than it does on how effective the underlying system is.

We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also use competitor page weight to compare the new website to the old one. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class.

We could start looking at the transferability of our web pages for repeat visitors if we want to take it one step further. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For instance, repeat users who load the same page frequently will likely have a high percentage of the files cached in their browser, which means they won’t need to move all of the files back on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. We can learn even more about how to optimize efficiency for users who regularly visit our pages by measuring transfer size at this next level of detail, which will also enable us to establish page weight budgets for situations that extend beyond the initial visit.

Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose carbon emissions and energy consumption data, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

In summary, less data transfer leads to more energy efficiency, a crucial component of reducing web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some.

Electricity’s carbon power

Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. The term” carbon intensity” (gCO₂/k Wh ) is used to describe how much carbon dioxide is produced for each kilowatt-hour of electricity produced. This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO₂/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately ₂00–400 gCO₂/k Wh.

The majority of electricity is produced by national or state grids, where energy from a variety of sources is combined with various levels of carbon intensity. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

Although we don’t have complete control over the energy supply of web services, we do have some control over where our projects are hosted. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. Danish startup Tomorrow reports and maps the user-provided data, and a look at their map demonstrates how, for instance, choosing a data center in France will have significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

Having said that, we don’t want to locate our servers too far away from our users; however, it takes energy to transmit data through the telecom’s networks, and the more energy is used, the further the data travels. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.

We can use website analytics to determine the country, state, or even city where our core user group is located and measure the distance from that location to the data center used by our hosting company by using the distance itself as a benchmark. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea.

For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could look up the travel distance between London and San Francisco, which is 5,300 miles. That’s a long way! We can see how hosting it somewhere in North America, ideally on the West Coast, would significantly shorten the distance and the amount of energy needed to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

Reverting it to carbon emissions

If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. The method my team developed converts the amount of electricity transferred when loading a web page into a CO₂ figure ( Fig. ₂.4), and then converts that data into a figure for the tool. It also factors in whether or not the web hosting is powered by renewable energy.

The Energy and Emissions Worksheet that comes with this book teaches you how to improve it and tailor the data more appropriately to your project’s unique features.

With the ability to calculate carbon emissions for our projects, we could actually expand our page weight budget and establish carbon budgets as well. CO₂ is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds an air of abstraction, carbon budgets do focus our minds on the main issue we’re trying to reduce, which also supports the main goal of sustainable web design: reducing carbon emissions.

Browser Energy

Transfer of data might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational burden is increasingly shifting from the data center to the users ‘ devices, whether they are smart TVs, tablets, laptops, phones, tablets, laptops, or other front-end web technologies. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React allow us to create applications where the” thinking” process is performed either partially or completely in the browser.

All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more energy is used by the user’s devices as a result of the user’s web browser’s increased computation. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally exclude those who have older, slower devices and make the batteries on phones and laptops drain more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. This not only harms the environment, but it places a disproportionate financial burden on the poorest members of society.

In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users ‘ devices. The Energy Impact monitor inside the developer console of the Safari browser is one of the tools we currently have ( Fig. 2.5 ).

You know what happens when your computer’s cooling fans start spinning so frantically that you suspect it might take off when you load a website? That’s essentially what this tool is measuring.

It uses these figures to create an energy impact rating based on the percentage of CPU used and how long it took the web page to load. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.

This section will provide you with that plan of action. It covers how to incorporate safety principles into your design work in order to make tech that’s secure, how to persuade your stakeholders that this work is important, and how to respond to the critique that what we really need is more diversity. ( Spoiler: we do, but diversity alone is not the solution to fixing unethical, unsafe technology. )

The method for equitable safety

Your objectives when designing for protection are as follows:

• discover ways your solution can be used for abuse,
• style ways to prevent the maltreatment, and
• offer assistance for harmed people to regain control and power.

The Process for Inclusive Safety is a tool to help you reach those goals ( Fig 5.1 ). I developed this strategy in 2018 to better understand the different methods I used to create products that were designed with safety in mind. Whether you are creating an entirely new product or adding to an existing element, the Process can help you produce your product secure and diverse. The Process includes five public areas of action:

• conducting studies
• Creating tropes
• pondering issues
• Designing answers
• Testing for health

The Process is meant to be flexible; in some situations, it didn’t make sense for groups to employ every step. Use the parts that are related to your special function and environment, this is meant to be something you can put into your existing style process.

And once you use it, if you have an idea for making it better or simply want to give perspective of how it helped your staff, please get in touch with me. It’s a dwelling report that I hope technicians can use as a practical and useful resource in their day-to-day work.

If you’re working on a product especially for a resilient team or survivors of some form of injury, such as an application for survivors of domestic violence, sexual abuse, or drug addiction, be sure to read Section 7, which covers that position directly and should be handled a bit different. The principles set forth here are for putting safety first when designing a more general product with a broad user base ( which, as we already know from statistics, will include some groups that should be protected from harm ). Chapter 7 is focused on products that are specifically for vulnerable groups and people who have experienced trauma.

Step 1: Conduct research

A thorough analysis of how your technology might be used for abuse as well as specialized insights into the experiences of those who have witnessed and perpetrated that kind of abuse should be included in design research. At this stage, you and your team will investigate issues of interpersonal harm and abuse, and explore any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, racist algorithms, and harassment.

broad analysis

Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. For example, a team building a smart home device would do well to understand the multitude of ways that existing smart home devices have been used as tools of abuse. If you’re creating an AI product, be aware of the potential for racism and other issues that have been reported in other AI products. Nearly all types of technology have some kind of potential or actual harm that’s been reported on in the news or written about by academics. For these studies, Google Scholar is a useful resource.

Specific research: Survivors

When possible and appropriate, include direct research ( surveys and interviews ) with people who are experts in the forms of harm you have uncovered. In order to gain a better understanding of the subject and avoid retraumatizing survivors, you should first interview those who work in the area of your research. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

It is crucial to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. While some survivors may not want to be paid, you should always make the offer in the initial ask. Alternative to paying is to donate to a cause fighting the kind of violence the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

Specific research: Abusers

It’s unlikely that teams aiming to design for safety will be able to interview self-proclaimed abusers or people who have broken laws around things like hacking. Don’t make this a goal, rather, try to get at this angle in your general research. Attempt to understand how abusers or bad actors use technology to harm others, how they use it against others, and how they justify or explain the abuse.

Step 2: Create archetypes

Use your research’s findings to create abuser and survivor archetypes once you’ve finished conducting your research. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they’re based on your research into likely safety issues, much like when we design for accessibility: we don’t need to have found a group of blind or low-vision users in our interview pool to create a design that’s inclusive of them. Instead, we base those designs on existing research and what this group requires. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.

The abuser archetype is a person who views a product as a tool to cause harm ( Fig. 5.2 ). They may be trying to harm someone they don’t know through surveillance or anonymous harassment, or they may be trying to control, monitor, abuse, or torment someone they know personally.

The survivor archetype describes a person who is being abused with the product. There are various situations to consider in terms of the archetype’s understanding of the abuse and how to put an end to it: Do they need proof of abuse they already suspect is happening, or are they unaware they’ve been targeted in the first place and need to be alerted ( Fig 5.3 )?

You may want to make multiple survivor archetypes to capture a range of different experiences. They may be aware of the abuse being occurring but not be able to stop it, such as when a stalker keeps tracing their whereabouts or when an abuser locks them out of IoT devices ( Fig. 5.4). Include as many of these scenarios as you need to in your survivor archetype. You’ll use these later when you create solutions to help your survivor archetypes achieve their objectives of preventing and ending abuse.

It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Focus on their objectives rather than the demographic information we frequently see in personas. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll think about how to help the survivor’s goals and the abuser’s goals.

And while the “abuser/survivor” model fits most cases, it doesn’t fit all, so modify it as you need to. For example, if you uncovered an issue with security, such as the ability for someone to hack into a home camera system and talk to children, the malicious hacker would get the abuser archetype and the child’s parents would get survivor archetype.

3. Brainstorming issues

After creating archetypes, brainstorm novel abuse cases and safety issues. You’re trying to identify completely new safety issues that are unique to your product or service by using the term” Novel” in terms of things that are not found in your research. The goal with this step is to exhaust every effort of identifying harms your product could cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

What other abuses could your product be used for besides what you’ve already discovered through your research? I recommend setting aside at least a few hours with your team for this process.

Try conducting a Black Mirror brainstorming if you’re looking for a place to start. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Try to figure out how your product would be used in an episode of the show—the most wild, awful, out-of-control ways it could be used for harm. Participants typically have a lot of fun when I lead Black Mirror brainstorms ( which is great because having fun when designing for safety! ). I recommend time-boxing a Black Mirror brainstorm to half an hour, and then dialing it back and using the rest of the time thinking of more realistic forms of harm.

You may still not feel confident that you have found every potential source of harm after identifying as many opportunities for abuse as you can. A healthy amount of anxiety is normal when you’re doing this kind of work. It’s common for teams designing for safety to worry,” Have we really identified every possible harm? What if something is missing, then? If you’ve spent at least four hours coming up with ways your product could be used for harm and have run out of ideas, go to the next step.

It’s impossible to say for sure that you’ve done everything, but instead of striving for 100 % assurance, acknowledge that you’ve done everything, and pledge to prioritize safety going forward. Once your product is released, your users may identify new issues that you missed, aim to receive that feedback graciously and course-correct quickly.

Step 4: Design solutions

You should now be aware of the ways your product can be used for harm as well as survivor and abuser archetypes describing opposing user objectives. The next step is to identify ways to design against the identified abuser’s goals and to support the survivor’s goals. This is a good idea to include this one alongside other areas of your design process where you’re offering solutions to the various issues your research has identified.

Some questions to ask yourself to help prevent harm and support your archetypes include:

• Can you design your product in such a way that the identified harm cannot happen in the first place? What barriers can you place to stop the harm from occurring if not?
• How can you make the victim aware that abuse is happening through your product?
• How can you assist the victim in understanding what they need to do to stop the problem?
• Can you identify any types of user activity that would indicate some form of harm or abuse? Could your product help the user access support?

In some products, it’s possible to proactively detect harm is occurring. For example, a pregnancy app might be modified to allow the user to report that they were the victim of an assault, which could trigger an offer to receive resources for local and national organizations. Although it’s not always possible to be this proactive, it’s worthwhile to spend a half hour talking about how your product could help the user receive help in a safe manner if any kind of user activity would indicate some form of harm or abuse.

That said, use caution: you don’t want to do anything that could put a user in harm’s way if their devices are being monitored. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. In the next chapter, we’ll walk through a good illustration of this.

Step 5: Test for safety

The final step is to evaluate your prototypes from the perspective of your archetypes, who wants to harm the product and the victim of the harm who needs to regain control over the technology. Just like any other kind of product testing, at this point you’ll aim to rigorously test out your safety solutions so that you can identify gaps and correct them, validate that your designs will help keep your users safe, and feel more confident releasing your product into the world.

Ideally, safety testing happens along with usability testing. If you work for a company that doesn’t conduct usability testing, you might be able to use safety testing to deftly perform both. A user who uses your design while trying to use it against someone else can also be encouraged to point out interactions or other design details that don’t make sense to them.

You’ll want to conduct safety testing on either your final prototype or the actual product if it’s already been released. It’s okay to test an existing product that wasn’t created with safety goals in mind right away; “etrofitting” it for safety is a good thing.

Remember that testing for safety involves testing from the perspective of both an abuser and a survivor, though it may not make sense for you to do both. Alternatively, if you made multiple survivor archetypes to capture multiple scenarios, you’ll want to test from the perspective of each one.

You as the designer are most likely too closely connected to the product and its design by this point to be a valuable tester, you know the product too well, as with other forms of usability testing. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.

Abuse testing

The goal of this testing is to understand how easy it is for someone to weaponize your product for harm. Unlike with usability testing, you want to make it impossible, or at least difficult, for them to achieve their goal. Use your product in an effort to achieve the goals in the abuser archetype you created earlier.

For example, for a fitness app with GPS-enabled location features, we can imagine that the abuser archetype would have the goal of figuring out where his ex-girlfriend now lives. With this in mind, you’d make every effort to discover the location of a different user who has their privacy settings in place. You might try to see her running routes, view any available information on her profile, view anything available about her location ( which she has set to private ), and investigate the profiles of any other users somehow connected with her account, such as her followers.

If by the end of this you’ve managed to uncover some of her location data, despite her having set her profile to private, you know now that your product enables stalking. Returning to step 4 and figuring out how to stop this from occurring is your next step. You may need to repeat the process of designing solutions and testing them more than once.

Survivor testing

Survivor testing involves identifying how to give information and power to the survivor. It might not always make sense based on the product or context. The survivor archetype’s goal of not being stalked is satisfied by preventing an attempt by an abuser archetype to stalk someone, so separate testing from the survivor’s perspective wouldn’t be required.

However, there are cases where it makes sense. For instance, a survivor archetype’s goal would be to discover who or what causes the temperature to change when they aren’t altering it themselves. You could test this by looking for the thermostat’s history log and checking for usernames, actions, and times, if you couldn’t find that information, you would have more work to do in step 4.

Another goal might be regaining control of the thermostat once the survivor realizes the abuser is remotely changing its settings. Your test would involve trying to figure out how to do this: are there instructions on how to remove and change the password, and are they simple to locate? This might again reveal that more work is needed to make it clear to the user how they can regain control of the device or account.

Stress testing

To make your product more inclusive and compassionate, consider adding stress testing. This concept comes from Design for Real Life by Eric Meyer and Sara Wachter-Boettcher. The authors noted that personas typically focus on those who are having a good day, but that real users are frequently anxious, stressed out, having a bad day, or even going through tragedy. These are called” stress cases”, and testing your products for users in stress-case situations can help you identify places where your design lacks compassion. More information about how to incorporate stress cases into your design can be found in Design for Real Life, as well as in many other effective methods for designing with compassion.

How can a content management system ( CMS ) be set up to reach your current and future audience? I learned the hard way that creating a content model—a concept of information types, attributes, and relationships that let people and systems understand content—with my more comfortable design-system wondering would collapse my patient’s holistic information strategy. By developing content versions that are conceptual and even join related content, you can avoid that result.

I just had the opportunity to direct the CMS application for a Fortune 500 company. The customer was excited by the benefits of an holistic information plan, including material modify, multichannel marketing, and robot delivery—designing content to be comprehensible to bots, Google knowledge panels, snippets, and voice user interfaces.

A content type is essential for an omnichannel articles strategy, and the model needed conceptual types, which are types of types that are categorized according to their meaning rather than their presentation. Our aim was to allow writers to write articles and use it where necessary. But as the job proceeded, I realized that supporting material utilize at the range that my client needed required the whole group to identify a new pattern.

Despite our best efforts, we remained influenced by what we were more comfortable with: design techniques. An holistic content strategy cannot rely on WYSIWYG equipment for design and layout, unlike web-focused material strategies. Our tendency to approach the material model with our common design-system thinking frequently led us to veer away from one of the main purposes of a material model: delivering content to audiences on various marketing channels.

Two fundamental tenets are necessary for a successful content model

We needed to explain to our designers, developers, and stakeholders that we were doing something completely different from their previous web projects, where everyone assumed that content would fit into layouts as visual building blocks. The previous approach was not only more familiar but also more intuitive—at least at first—because it made the designs feel more tangible. The team was able to understand how a content model differs from the design systems we were familiar with by discovering two principles:

1. Instead of layout, semantics must be used by content models.
2. And content models should connect content that belongs together.

Semantic content models

Type and attribute names for semantic content models are used to reflect the content’s intended purpose and not its intended display. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. These types may make it simple to present content, but they do not aid in understanding the meaning of the content, which would have opened the door to the content presented in each marketing channel. In contrast, a semantic content model uses type names like “product,”” service,” and “testimonial” to allow for each delivery channel to interpret and use the content as it sees fit.

When you’re creating a semantic content model, a great place to start is to look over the types and properties defined by Schema. a community-driven resource for type definitions that are understandable on platforms like Google search.

A semantic content model has a number of advantages:

Even if your team doesn’t care about omnichannel content, a semantic content model decouples content from its presentation so that teams can evolve the website’s design without needing to refactor its content. In this way, content can withstand irrational website redesigns.
• A semantic content model also gives you an advantage in the market. By adding structured data based on Schema. A website can provide hints to Google to understand the content, display it in search snippets or knowledge panels, and use it to respond to user voice-interface queries. Without ever visiting your website, potential visitors could easily find your content.
• Beyond those practical benefits, you’ll also need a semantic content model if you want to deliver omnichannel content. Delivery channels must be able to understand the same content in order to use it across multiple marketing channels. For instance, if your content model provided a list of questions and answers, it could be easily displayed on a frequently asked questions ( FAQ ) page as well, but it could also be used by a bot that answers frequently asked questions.

For example, using a semantic content model for articles, events, people, and locations lets A List Apart provide cleanly structured data for search engines so that users can read the content on the website, in Google knowledge panels, and even with hypothetical voice interfaces in the future.

connective content models

Instead of slicing up related content across disparate content components, I’ve come to the realization that the best models are those that are semantic and also connect related content components ( such as a FAQ item’s question and answer pair ). A good content model connects content that should remain together so that multiple delivery channels can use it without needing to first put those pieces back together.

Write an essay or article about it. The meaning and usefulness of an article depend on how well its components are kept together. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? Our well-known design-system thinking on our project frequently led us to want to develop content models that would divide content into distinct chunks to fit the web-centric layout. Similar effects could have been felt to an article that had its headline removed. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.

Let’s take a look at how connecting related content works in a real-world setting to illustrate. A complex layout for a software product page that included multiple tabs and sections was presented by the client’s design team. Our instincts were to follow suit with the content model. Shouldn’t we make adding multiple tabs in the future as simple and flexible as possible?

We felt like we needed a content type called “tab section” because our design-system instincts were so well-known, so that multiple tab sections could be added to a page. Each tab section would display various types of content. One tab might contain the software’s information or specifications. A list of resources might be found under another tab.

Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood by additional delivery channels. How would another system have resorted to counting tab sections and content blocks, for instance, if it had been able to identify a product’s “tab section” when referring to its specifications or resource list? This would have prevented the tabs from ever being rearranged, and it would have required adding logic to each other delivery channel to interpret the layout of the design system. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.

Our customer had a breakthrough when we realized that for each tab, a specific purpose in mind would be revealed, such as the software product’s overview, specifications, related resources, and pricing. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. It wasn’t long after a little digging that the content model didn’t like the idea of tabs. What was important was the meaning of the information that was intended to be displayed in the tabs.

In fact, the customer could have decided to display this content in a different way—without tabs—somewhere else. In response to this realization, we decided to create content types for the software product based on the meaningful qualities the client wanted to display on the web. There were rich attributes like screenshots, software requirements, and feature lists as well as obvious semantic attributes like name and description. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel, including those that follow, could comprehend and display this content.

Conclusion

In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic ( with type and attribute names that reflected the meaning of the content ) and that it kept content together that belonged together ( instead of fragmenting it ). These two ideas made it easier for us to decide what to do with the content model based on the design. Remember: If you’re developing a content model to support an omnichannel content strategy, or even if you just want to make sure Google and other interfaces understand your content, keep in mind:

• A design system isn’t a content model. You should maintain the semantic value and contextual structure of the content strategy throughout the entire implementation process because team members might be drawn to conflate them and force your content model to resemble your design system. Without the use of a magic decoder ring, every delivery channel will be able to consume the content.
• If your team is struggling to make this transition, you can still reap some of the benefits by using Schema. Your website uses structured data from org. The benefit of search engine optimization is a compelling reason on its own, even if additional delivery channels aren’t on the horizon in the near future.
• Additionally, remind the team that decoupling the content model from the design will let them update the designs more easily because they won’t be held back by the cost of content migrations. They’ll be able to create new designs without compromising the compatibility between the content and the design, and they’ll be prepared for the upcoming big thing.

By firmly defending these ideas, you’ll help your team view content as the most important component of your user experience and as the most effective way to engage with your audience.