Tag Archives: AI

AI and the Future of Design

AI and the Future of Design: What will the designer of 2025 look like?

In the latest installment of the series on AI and Design, Rob Girling argues that designers may well provide the missing link between AI and humanity.

For anyone doubting that AI is here, the New York Times recently reported that Carnegie Mellon University plans to create a research center that focuses on the ethics of artificial intelligence. Harvard Business Review started laying the foundation for what it means for management, and CNBC started analyzing promising AI stocks. I made the relatively optimistic case that design in the short term is safe from AI because good design demands creative and social intelligence.

But this short-term positive outlook did not alleviate all of my concerns. This year, my daughter started college, pursuing a degree in interaction design. As I began to explore how AI would affect design, I started wondering what advice I would give my daughter and a generation of future designers to help them not only be relevant, but thrive in the future AI world.

Here is what I think they should expect and be prepared for in 2025.

Everyone will be a designer

Today, most design jobs are defined by creative and social intelligence. These skill sets require empathy, problem framing, creative problem solving, negotiation, and persuasion. The first impact of AI will be that more and more non-designers develop their creativity and social intelligence skills to bolster their employability. In fact, in the Harvard Business Review article I mentioned above, advice #4 to managers is to act more like designers.

The implication for designers is that more than just the traditional creative occupations will be trained to use “design thinking” techniques to do their work. Designers will no longer hold a monopoly (if that were ever true) on being the most “creative” people in the room. To stay competitive, more designers will need additional knowledge and expertise to contribute in multidisciplinary contexts, perhaps leading to increasingly exotic specializations. You can imagine a classroom, where an instructor trained in design thinking is constantly testing new interaction frameworks to improve learning. Or a designer/hospital administrator who is tasked with rethinking the inpatient experience to optimize it for efficiency, ease of use, and better health outcomes. We’re already seeing this trend emerge — the Seattle mayor’s office has created an innovation team to find solutions to Seattle’s most immediate issues and concerns. The team embraces human-centered design as a philosophy, and includes designers and design strategists.

Stanford’s d.school has been developing the creative intelligence of non-traditionally trained designers for over a decade. And new programs like MIT’s Integrated Design and Management program are also emerging. Even medical schools are starting to train future physicians in design thinking. This speaks to design’s broader relevance, but also to a new opportunity for educators across disciplines to include creative intelligence training and human-centered design in their curricula.

Designers as curators, not creators

I already wrote about how tools like Autodesk Dreamcatcher use algorithmic techniques to provide designers with a more abstracted interface for creation. Given sufficient high-level direction, constraints, goals, and a problem to solve, these tools can spit out hundreds of variations of a design, leaving designers to pick their favorites or keep re-mixing them until they get closer to a great design.

The implications of this vary across design disciplines. In architecture, the parametric movement dubbed Parametricism 2.0 demonstrates the potential of technologically enhanced creativity. Its implications are already being explored in the gaming industry, as we design virtual environments and large virtual cities. Just take a look at the game No Man’s Sky — it relies on a procedurally generated deterministic open universe, which includes over 18 quintillion (1.81019) planets. While No Man’s Sky was unsuccessful as a game, it shows the direction that eventually will come to dominate virtual content development — the designer’s role will be to set the goals, parameters, and constraints, and then review and fine-tune the AI-generated designs.

Generative design techniques aren’t especially new, but deep reinforcement learning is a relatively new technique that emerged in the last three to four years and is responsible for much of the recent excitement and progress of AI as a discipline. Google’s DeepMind created an artificial intelligence program called Deep Q, which uses deep reinforcement learning to play Atari games and improve itself over time, eventually acquiring amazing skills like discovering unknown loopholes in the games.

The real breakthrough with DeepMind’s Deep Q, and its successor AlphaGo — the computer program that plays the board game Go — is that the AI doesn’t have any domain knowledge or expertise in game play. And it doesn’t even need someone to codify the rules of how to play. It just has visual input, controls, and an objective of trying to maximize its score. To that extent, games are an ideal test environment for artificial intelligence to learn.

But what about design? That’s where the curator role comes in. In the future, designers will train their AI tools to solve design problems by creating models based on their preferences.

For instance, after years of working in the health care space, Artefact has developed a deep and broad perspective on the key issues in digital health design necessary for changing patient behaviors. I can imagine a time when we will have enough data to enter behavior goals and ask the AI system to design a solution framework that overcomes anticipated issues like confirmation bias and the empathy gap.

The ongoing era of superstar designers

As AI-driven parametric design enables designers to quickly and easily create millions of variations of a design, most designers’ productivity will dramatically increase. Suddenly, we’ll be able to explore massive numbers of alternative directions in a fraction of the time we need today. With increased productivity and better tools, it will be easier for amateur designers to create acceptable — if not exceptional — work, and potentially put price pressure on professional design services.

But while the barriers to learning and mastering the craft will be lower, the design industry’s superstars will most likely remain unaffected. We saw a similar trend in print and graphic design in the 90s. The arrival of desktop publishing software ultimately eliminated the lower end of the market. But it also created broader appreciation for design from everyone, increasing the demand and the differentiation for the very best designers. Until AI is capable of surprising us with completely novel ideas, superstar designers and companies that invest in them will continue to dominate, increasing the value of design brands.

From traditional to virtual designers

A cynic might say that, as a massive number of people lose their jobs to AI-powered automation, they would escape in a virtual reality world, powering a growing demand for virtual worlds, objects, and experiences. Hopefully, we can avoid this dystopian scenario, but as virtual, augmented, and mixed reality explodes, it will become the next frontier of opportunity for design. Challenges like how we interact with each other in virtual reality and how we create and communicate shared experiences are not only unique for this new medium, but require skills such as creative and social intelligence that are hard to outsource to AI.

In addition, virtual worlds may generate new demand for the more traditional design disciplines, such as architecture, interior design, object design, and fashion, as we rush to create virtual worlds.

Designing AI, designing the future of humanity

By framing the argument to show how AI is stealing our design jobs, I’ve perhaps done a disservice to AI’s contributions to the design profession. When humans and computers work together, they can do amazing things that neither could do alone — just take a look at Michael Hansmeyer’s unimaginable shapes. With their millions of facets, these forms cannot be built by a human alone, yet they can redefine architecture.

While this is just one example, there is something undeniably appealing about finding ways to amplify our creativity as individuals and across professions. I can see the potential for a future where our personal AI assistants, armed with a deep understanding of our influences, heroes, and inspirations, constantly critique our work, suggesting ideas and areas of improvement. A world where problem-solving bots help us see a problem from a variety of perspectives, through different frameworks. Where simulated users test things we’ve designed to see how they will perform in a variety of contexts and suggest improvements, before anything is even built. Where A/B testing bots are constantly looking for ways to suggest minor performance optimizations to our design work.

Far from threatening the design occupation, AI offers a huge opportunity for design, especially for those involved in designing the interactions we have with the emerging AI systems. How do we design those AI design tools? How will we design the intelligent services and platforms of our future? How should we design these systems in a way that helps us augment our creativity, our relationships with the world, our humanity?

That is a tall order and an exciting opportunity for us and for the generations to come.

This article originally appeared in O’Reilly Design. / From Medium

10 Principles for Design in the age of AI

We’re on the cusp of a new era of design. Beyond the two-dimensional focus on graphics and the three-dimensional focus on products, we’re now in an era where designers are increasingly focusing on time and space, guided by technological advances in artificial intelligence, robotics, and smart environments.

While great thinkers like Dieter Rams and George Nelson offered their own design principles in past eras, industrial designer Yves Béhar points out that there are no comparable manifestos or guidelines for designers working with AI, robotics, and connected technology today.

Lasst week, in a talk delivered at the inaugural A/D/O/ Design Festival in Brooklyn, Béhar presented his vision for what those guidelines should look like–in the form of 10 principles for design in the age of AI.

1. Design solves an important human problem.

What problem are you trying to solve with AI? Considering the multitude of “smart” products that are actually quite stupid, it’s a question worth asking.

“At CES there was a lot of mundane automation that is more part of what I would call gadgetry–versus automation that truly improves people’s lives or delivers considerable amounts of service or value,” Béhar says. “What is our intent in the world? For a company, for a product, for a service, I think it’s an important question to ask ourselves.”

He points to the smart crib he designed, called Snoo. The problem he was trying to solve was clear: The lack of sleep for parents with young children. It’s a problem that’s well-documented, both anecdotally and in research; Béhar would go so far to say it’s a national health issue (he’s also a parent himself, so he’s experienced the exhaustion of having a baby firsthand). The seriousness and specificity of this issue is what helped focus the design.

2. Design is context specific (it doesn’t follow historical cliches).

“If anyone has been at CES this year or seen reports, you’ve seen hundreds of little robots,” Béhar says. “They’re white, cutesy, with googly eyes; they’re there to entertain us and keep the dog company.”

But Béhar believes that the trend of anthropomorphizing robots is nothing more than a historical cliche–and should be avoided. “Why do we need to anthropomorphize these kinds of machines?” he asked. “Why do we need to replicate human interactions or emotions?”

Moving beyond these well-worn cultural cliches, to instead put context first, will be important for designers working on truly “smart” objects.

3. Design enhances human ability (without replacing the human).

Robots are coming for our jobs–right? Well, not if they’re designed to enhance our human abilities. This principle encourages designers to think about how products can thoughtfully augment people rather than replace them. “Can we design different services to complement humans and their lives instead of replicate them?” Béhar asks.

Béhar recently worked with the startup SuperFlex to design a supportive body suit that uses synthetic, electrical muscles to augment differing levels of mobility in elderly people, rather than replace their natural strength completely. Part of the London Design Museum exhibition New Old, the device looks a bit like a wetsuit and is meant to be worn underneath the user’s clothes (though Béhar thinks people will want to show it off).

It’s a prime example of how technology can be designed as a human aid. “By continuing to support movement I think we can make a big difference in people’s lives,” he says.

4. Good design works for everyone, everyday.

Béhar points out that not everyone in a household will necessarily love their new robotic housemates the way a tech-lover might; others may be less swayed by a newfangled gadget. “With home innovation, what’s typically happened is the person who installed it loves it, and everybody else in the home hates it.”

That’s the opposite of what a well-designed smart product should do. Béhar says he wants to design tech that isn’t just pleasing to one user, but is present and useful for everyone in a home. “Which means that technology can’t be something that’s hard to install, something that is hard to live with,” he says.

5. Good tech and design is discreet.

It should make your life easier, but it shouldn’t get in the way.

“We’ve adapted ourselves over thousands of years to receive information and act on that information,” Béhar explains. “If the wind starts coming from my right, if the temperature drops, I will naturally interpret that as the fact that there may be a storm coming, that there is a weather change. Why can’t we do that with products as well? Why can’t we create subtle signals that allow us to both be informed and control the environments that we’re in?”

Take August, a company that he cofounded, which designed a smart lock that opens your door when it senses you’re there so you don’t have to root around in your bag for your keys. It doesn’t require you to take out your phone, but instead causes your phone to vibrate and the lock to sound, indicating that the door has been successfully unlocked. “Those are what I call invisible interfaces, and continuing to look for this is really key,” he says.

Ultimately, great design means discreet design that doesn’t distract from more meaningful experiences: “You have to decide which [products] allow you to focus on other things that are maybe more important, or which ones take you away from interacting with the environment in a way that’s enriching.”

6. Good design is a platform that grows with needs and opportunities.

When you’re designing with AI, you’re designing a system that learns and grows, with functionality that may change over time thanks to software updates. Béhar says that with every single product he’s launched over the past eight years, he’s found he likes it even more six months to a year after it launched. Products are no longer immutable–they should be designed to allow room for development and change.

“Because things can be modified fairly easily, you improve on it,” he says.

7. Good design brings about products and services that build long-term relationships (but don’t create emotional dependency).

Building on principle number six, products should be designed for a much longer term use. Béhar describes a conceptual project he did in the late ’90s for SFMOMA. The museum asked him to design a prototype for the future of the shoe. He ended up designing a shoe that wasn’t based on seasons or styles, but that captured data about how you walk, your pronation, and any weight changes. Then, the manufacturer could replace your current set of shoes with ones designed specifically for your feet. The idea? A product should create loyalty by improving over time, sowing the seeds for a lifelong relationship with a user.

8. Good technology design learns and predicts human behavior.

As machine learning and AI slowly infiltrate our tech, products not only have the ability to learn–they can also predict human behavior in a way that better serves the user.

Béhar illustrates this idea with a social companion robot for the elderly, ElliQ, that he designed for Intuition Robots. It’s meant to help aging adults stay connected to the world when their cognitive functions are diminishing. Instead of waiting for a prompt from its elderly user, the robot proactively suggests personalized activities in order to keep the user engaged. It’s a prime example of how AI can improve a specific aspect of a person’s life based on their behavior.

9. Good design accelerates new ideas.

Béhar thinks that true innovation can be pushed forward faster in the hands of a great designer. For instance, take Ori, an MIT startup that’s designing urban micro apartments. The company’s solution to the housing crunch in cities is to use robotics to make smaller spaces “act” bigger, utilizing connected furniture that transforms a single-room apartment from a bedroom to a living room at the press of a button.

Ori, only conceived several years ago, is slated to hit the market this year–an example of a deeply futuristic (and perhaps potentially dystopian) idea that great design has pulled into reality very quickly.

10. Good design removes complexity from life.

To illustrate this final principle, Béhar showed a video of a rather primitive robot trying to feed a woman breakfast–and failing miserably. There are plenty of menial everyday tasks at which people are still much more adept than robots. But there are also tasks that computers are simply much better at, and these are the areas that designers should be focusing on. The question designers must ask: What is a mundane experience, and what is a meaningful one, and what role should AI play in either?

“I think in general you don’t want to replace behavior or human-led functionality,” Béhar says. Instead, AI can remove some of the pain points of life by reducing complexity and freeing up people’s cognitive space so they can focus on more important endeavors.

Ultimate, Béhar believes that the real question lies in how we imbue artificial intelligence with values. “That’s how I believe we make the world a little less dystopian and more utopian,” he says. But he also neglects to point out ways that design could serve as a buffer against AI’s dark side; when Microsoft CEO Satya Nadella laid out his principles for designing AI responsibly in 2016, he cited transparency, accountability, and protection of privacy as critical components.

While Béhar believes that designers have a responsibility to build products morally, he also believes that a “self-correcting environment” will ultimately act as an ethical safety net–even in the case of Facebook and its fake news crisis. “Businesses are putting these algorithms out there, they are seeing what they do, like increasing traffic, and then they [are] realizing it’s not good if it’s all fake or has a nefarious impact on our lives,” he says. “I do think that there’s a self-correcting mechanism.”

But ultimately it is the role of designers in the age of AI to act as a bulwark against irresponsible, unethical use of technology. After all, the robots are here to stay.

Follow Yves Behar at LinkedIn
10 Principles For Design In The Age Of AI (Original article)

Obsolete

With the rise of technology and the real-time pressures of an online, global economy,

humans will have to be very clever – and very careful – not to be left behind by the future.From the perspective of those in charge, human labor is losing its value, and people are becoming a liability.

This documentary reveals the real motivation behind the secretive effort to reduce the population and bring resource use into strict, centralized control.

Could it be that the biggest threat we face isn’t just automation and robots destroying jobs, but the larger sense that humans could become obsolete altogether?

Watch Obsolete at https://youtu.be/jPmUGq25KBk

More Future at:

http://www.bibliotecapleyades.net/ciencia/ciencia_transhumanism.htm#Multimedia