For 6-year-old Dave Jr., a long line at Disneyland triggered a massive meltdown. His parents were concerned and a little embarrassed, but not surprised; Dave Jr. struggled to keep his emotions in check.

Hoping to help, Dave Jr.'s uncle, entrepreneur Craig Lund, joined forces with researchers at Harvard Medical School and Boston Children’s Hospital, along with a video game designer who had worked on Quick Hit and NBA 2K. Together, they set out to design something that could teach coping skills to kids like Dave Jr. who need to manage “big emotions,” as well as children suffering from anxiety, ADHD, and other behavior issues, which are on the rise.

Their collaboration resulted in a video game called Mightier and a startup called Neuromotion Labs—a 10-person team of psychologists, game designers, and engineers who embedded at IDEO Cambridge for a one-month sprint to improve the game and get ready for launch.

To play Neuromotion's game, kids are first taught simple, calming breathing exercises. During gameplay, kids wear heart-rate monitors on a wrist or arm that detect spikes caused by stress or anger; as their heart rates go up, the game's difficulty increases. Kids have opportunities to pause and try deep breathing to counter the ramped up challenge. As it turns out, "gamifying" restraint builds strong incentives for kids to take charge of their emotions—they have to if they want to win.

Already activated around boosting mental and emotional health, IDEO's design team worked side-by-side with Neuromotion to study how parents and children experience Mightier. From home visits to group interviews to a summer camp-style design session with kid players, live feedback fueled the next iteration of the gaming platform and better product-market fit.

IDEO helped Neuromotion hone the visual design and mechanics of Mightier and expand it's suite of games. The team observed that the Mightier program was more successful the more involved parents of players became, which revealed a need for additional resources for adults. So they created new supports, including a more detailed orientation and a personalized coaching service for parents staffed by trained therapists.

But can a video game actually help kids cope? Early peer-reviewed studies showed that playing Mightier reduced outbursts by 62 percent, oppositional behaviors by 40 percent, and parental stress by 19 percent. After 12 weeks of using Mightier, a survey of kids and parents showed that 96 percent of parents saw positive behavior changes in their children, while 92 percent of kids learned new coping skills.

Shortly after the design sprint, Neuromotion secured its next round of funding and officially launched Mightier’s array of “bioresponsive games.” The games have already been played more than a million times, and Neuromotion has measured more than a 100 million heartbeats. Mightier games are helping kids and families across the country.

What about Dave Jr.? Recently, his sister told Lund she "accidentally" bumped Dave Jr.’s bike off a pier and into the ocean. She was expecting an outburst of anger, but after eight months of playing Mightier, Dave Jr. stayed cool. His uncle couldn’t be prouder.

Many of us have let vegetables wither in the crisper drawer, or thrown out a child’s half-eaten restaurant meal, but the sheer scale of food waste around the globe is hard to grasp. According to the United Nations, about a third of the food the world produces every year—1.3 billion tons—is lost during production or tossed by consumers, with North Americans throwing out the most food per capita. The average American wastes enough food each month to feed another person for 19 days.

IDEO received a series of grants from The Rockefeller Foundation to find solutions, given the power of IDEO’s human-centered design approach to address systemic challenges. Through a number of projects with The Rockefeller Foundation and other organizations, IDEO designers from across the U.S. devised novel ways to tackle food waste.

For IDEO’s first initiative, designers tapped into the enthusiasm of the broader creative community, in partnership with The Rockefeller Foundation, the City of San Francisco’s Department of Environment, the Closed Loop Foundation, ReFED, and other groups. In the summer of 2016, OpenIDEO—IDEO’s open innovation practice—launched the Food Waste Challenge, asking how people might curtail waste by rethinking our relationship with food. Between June and October, more than 20,000 people from 113 countries took part in the challenge, tracking their personal waste and brainstorming solutions.

Challenge participants submitted more than 450 ideas. A team of food industry experts helped select the 12 top proposals, which included software to help people buy food collectively from wholesalers and a service that delivers extra meals from corporate events to those in need. Ultimately, the Closed Loop Foundation chose to award Full Cycle Bioplastics a $50,000 grant to scale up its idea to convert inedible food and paper waste into a fully compostable alternative to oil-based plastic.

At the conclusion of the Food Waste Challenge, OpenIDEO launched the Food Waste Alliance, a platform for participants and experts to stay engaged with the most promising ideas and innovators. The alliance helped entrepreneurs share resources, prototype new concepts, secure funding, hire staff, and form partnerships. OpenIDEO invited hundreds to join the alliance, and 92 percent of members told IDEO they made progress in their work as a result. One member company, RISE, received funding from another participant who discovered RISE through the alliance. This investment let RISE prototype its concept for milling spent grain from beer brewing into flour for baked goods and ultimately join the prestigious Food-X accelerator.

The Rockefeller Foundation also supported IDEO’s work with City Harvest, a New York organization that collects 160,000 pounds of unused food each day and delivers it to soup kitchens and food pantries. City Harvest wanted to understand the habits of local families who visit food banks in an effort to ensure all the food the group distributes gets eaten. To get a peek into these families’ kitchens, in January 2017, IDEO researchers conducted observations and interviews across New York City’s five boroughs. Pantry customers cooked for the researchers, giving them an inside look at how the families engaged with the food they had available and what food meant to each of them: tradition, stability, even adventure. Based on insights from pantry visitors, IDEO made recommendations for City Harvest, including community-run cooking classes and a way for families to request specific foods or reserve pick-up times by text message. IDEO also created three video vignettes to help build even greater empathy between City Harvest and the people it serves.

In spring 2017, capping IDEO’s work with The Rockefeller Foundation, the organizations teamed up with World Wildlife Fund and Hyatt hotels in Florida, New York, and New Jersey to rethink all-you-can-eat buffets. IDEO studied diners and staff at Hyatt buffets and found that employees—from event planners to kitchen staff—each add a cushion of extra food to cover their bases, while guests overfill their plates to avoid missing out. In the end, diners eat just half the food organizers serve, while the rest goes to waste. This and other data-driven insights gleaned about diners’ habits led to subtle substitutions, including smaller plates of meats and cheeses that can be ordered from servers and individual pastries rather than whole cakes. These alternatives have not only built on Hyatt’s existing food waste management strategies, but have also helped reduce buffet costs at Hyatt Regency Orlando and continued to receive support from guests.

The problem of food waste is too enormous to ignore. Wasted food means squandered resources, lost money, and ultimately, hungry people—more than 15 million in the United States alone. Designers and innovators from coast to coast have helped find solutions to the crisis that fulfill a variety of needs, from preserving produce sent to food pantries to keeping plastic packaging out of the oceans. The Rockefeller Foundation and other IDEO partners are leveraging powerful design techniques to pave the way for a waste-free future.

In 2017, IDEO acquired longtime partner Datascope and integrated the company’s data scientists and engineers. Datascope team members aren’t just passionate data scientists; they’re human-centered designers who happen to work with data, as illustrated by successful collaborations like this one:

In today’s job market, there’s no such thing as being "done" with your education. This is particularly true in the fields of data science, machine learning, and AI, where significant advances are made on a monthly basis. To meet this need for more in-depth training, Metis—part of Kaplan—wanted to create a comprehensive data science program for students from all backgrounds. Metis asked Datascope to design the curriculum from scratch, drawing on the company’s deep expertise in the field.

Datascope spoke with practitioners across industries to identify the key skill sets that make them successful: a grasp of design; fluency with data management, coding, and algorithms; and effective communication with coworkers and the wider world. The team crafted a 12-week bootcamp that develops these specific abilities.

In order to prepare students for the work world, the bootcamp is structured less like a class and more like a company, where students are “hired” as data scientists—with projects to complete—starting on day one.

Students collaborate on group projects and presentations in a way that mirrors real workflows, and practice pair programming to learn from one another. Using techniques drawn from design, students are invited to refine their project briefs and continually reevaluate their approach.

Instead of a final exam, at the end of the course, students tackle five real-world, open-ended data science projects inspired by Datascope’s client work. One project involves using data from subway turnstiles to detect patterns in the volume of street traffic; another asks students to use data they scrape from the web to predict a movie’s box office profits using regression analysis.

After students complete the bootcamp, they receive an additional three months of career support, from mock interviews to site visits with potential employers. In addition to designing the curriculum, Datascope taught the first three student cohorts and helped Metis build its teaching team as it expanded the program from New York to San Francisco, Chicago, and Seattle. Metis now offers online courses, evening classes, and corporate trainings in data science.

If you’re going to take a data science bootcamp, it’s best to take one designed by data scientists.

You’re whizzing along on your bike, en route to a new restaurant for a client meeting. You reach an unfamiliar intersection; which way to go now?

Instead of dismounting and digging for a phone, you brush your hand along your jacket sleeve for directions, then double-tap the denim to re-start your music. Without taking your eyes off the road, you’ve taken care of the problem.

This intuitive interface for connected apparel began with Levi's, makers of durable workwear for 140 years, and Google, creators of forward-looking technology, which joined forces to fashion the first item of clothing with touch-sensitive, copper-core threads woven directly into the fabric. Once it was established that the first connected garment from the partnership would be a jacket within Levi’s Commuter line, with interaction on the sleeve, Google worked with IDEO, leaders in designing for human needs, to develop the gesture language of the jacket and industrial design of the technology within.

This is the first connected garment that helps us break free from devices. It seamlessly incorporates Jacquard by Google technology to perform digital tasks, such as navigation, communication, and music playing with a few swipes or taps on the sleeve.

Jacquard by Google—a platform that makes it possible to integrate touch and gesture interactivity into fabrics using conductive yarn and standard, industrial looms—was inspired by a curious twist of history. The Jacquard loom, invented in France in 1804, used punch cards to automate the process of weaving complex patterns into fabric. In the 1940s and ’50s, engineers employed a similar punch-card technique to program the first computers.

IDEO spent time on the project early on, collaborating with Google engineers and Levi’s clothiers on the jacket’s development, helping craft an experience that would make the intelligent threads intuitive to wearers.

Working alongside Google and Levi’s, IDEO’s work included:

• The industrial design of the electronics integrated into the snap tag and connector (the tag snaps onto the jacket’s cuff and connects to your phone via Bluetooth)
• A vocabulary of gestures on the cuff of the jacket that lets you interact with the jacket’s technology
• Early exploration of the basic design philosophy and conceptual design for the interaction model of a corresponding smartphone app that ties it all together (works with both iOS and Android phones)

The IDEO team’s first task was to validate what commuters of all stripes wanted from the garment, in addition to the work Levi’s did in researching with its consumers. In interviews, group exercises, and wear tests with urban cyclists and other workers on the go, the team learned that cyclists needed a way to stay connected, while still living in the moment. That meant being able to answer calls, hear text messages, get the next direction, and control their music without using a screen.

Levi’s, Google, and IDEO developed a language of movement for Jacquard-enabled fabric that feels familiar and human and builds on the ways people would naturally interact with a garment (a whole-hand brush along the sleeve, as opposed to a one-finger tap on a touch screen, for instance).

Then came the design and engineering of the snap tag on the jacket’s cuff, which gently notifies you of calls, texts, and other jacket interactions with light and vibration feedback. The flexible, lightweight strap incorporates the look and feel of a Levi’s jean button, while housing advanced electronics that capture touch data. The tag is removable, charges via USB connection, and works in conjunction with a mobile app that lets you configure settings for the garment, set notifications, and customize gestures and interactions.

The Levi’s Commuter Jacket with Jacquard by Google changes the game because it’s simply that—a jacket—with technology that adds new utility and value, allowing us to wear our everyday interactions on our sleeves.

The Levi’s Commuter Trucker Jacket with Jacquard by Google hit stores in October 2017.

IDEO and Google have a long history of collaboration. Learn more about our work on Google Bloks here.

In one sentence, who are you?

I am an illustrator who enjoys bringing any amount of joy to people through my creations.

What do you do? How did you learn how to do it?

I create different drawings using pencil and ink. The illustrations range from patterns to caricatures, unique creatures, and other one-off ideas. I grew up sketching and doodling and it has continued. When I moved to LA, I was suddenly surrounded by an amazing cadre of artists and creators who constantly inspire me, as well as push me to keep improving myself. That is how I learned my craft and continue to learn, because I believe you never truly finish learning.

What are your 3 favorite possessions?

Miniature Back to the Future 2 hover board; Magnum P.I. Tiki Mug; a drawing of my fiancé and me, which she drew. Not in that order.

What does a typical work session look like?

I have a running list of ideas and sketches that I pull from if I don't have an art show with a specific topic that I am working towards. Usually, I'll do some Google searches on the topic at hand and pull a bunch of reference photos for perusal during the pencil drawing stage. I sketch out the drawing inside a pre-drawn area, such as 4x6 or 5x7. Art that is easy to frame is always a goal of mine, because I love framed art and it drives me mad when I see things tacked onto a wall or cork board. After finalizing the pencil drawing, I'll usually step away for a moment or two to play a video game or watch a show. I like to do something that differentiates the time between stages. Once I come back to the drawing, I pull out all the different micron pens that I think I will use for the piece. I check the nibs, and then I begin inking. I put on dramas in the background to listen to, or things I've seen a ridiculous number of times. West Wing and Parks and Recreation are two such shows.

I don't like to start inking unless I am going to finish a drawing that night. Sometimes, a piece is too large, and I have to break it up over two nights. If that happens, I make sure the pens I've used on the previous night are away from all my other pens. I do this to achieve a consistency within the lines. Once finished, I scan the piece, put it within a predetermined frame, and pack it up for a craft fair or deliver it if it's for an art show. Rinse and repeat as necessary.

How do you get over creative block?

I used to stop drawing and just stew for a bit until it finally passed, which could take a bit of time. As I've gotten older, and ever so slightly more confident in my abilities, I push through it. I just keep drawing. Yes, sometimes the drawings are awful, but as Lauren (my future wife) always says, "sometimes you just have to pass a rat."

How do you see the world in 2078?

A lazy utopia, filled with autonomous everything. Humanity will have moved past Earth and outward into the stars while robots cater to our every whim and we become fat and happy. I could be confusing my vision of the world in 2078 with the timeline in Wall-E—who doesn't yearn for the saccharine dreams of Pixar in 2017. It is tough to image the future right now because at this moment it feels as though we are hanging by a loose wire, and any minute now someone with a spray tan is going to cut the wire and tell us all how huge his ratings are, as we all fall to our collective doom. I hope we make it to 2078, if only so that I can enjoy my hover chair and 128-ounce Slurpee.

What’s number one on your bucket list?

I should say something epic like bungee jumping off of Thomas Jefferson's nose on Mount Rushmore, but honestly, I'd like to have my own artist's studio. Some place I could retreat to and tune out the world and draw silly pictures. That to me is something I want to do before I fade out of this existence.

Who are you creative crushin’ on lately?

I've had a one-sided love affair with Dustin Harbin for a long time. I own two of his original pieces and his diary comics book. The man can use an ink nib like Aaron Sorkin can turn a phrase.

I’ve been creative crushing on Austin Salmi since I saw his doodles, patterns, and adorable characters on Instagram almost two years ago. Austin’s work, learned through practice and osmosis in his job surrounded by artists, has a giggly character about it that fits his intention to hide the ugliness of the world for a moment, and make lovely order out of chaos. I got to learn a bit more about him and his process in this installment of Creative Crushes.

We had just begun work on a project exploring how we might help a medical-liability insurance company increase patient safety by learning from past incidents. As we talked, our conversation shifted away from excitedly imagining ideas for data-driven tools toward ways our work might potentially do harm.

What if our designs ended up raising premiums for doctors and, in turn, healthcare costs for patients? What if they kicked doctors off their insurance? What if doctors stopped reporting adverse events to keep their premiums from rising? There was real potential that our work could result in reduced patient safety or increased cost of care. We could inadvertently build a tool that could be used against the very people we were trying to help.

Today, data systems and algorithms can be deployed at unprecedented scale and speed—and unintended consequences will affect people with that same scale and speed. How can we always make sure we’re putting people first when designing large scale systems? Especially when those systems will change over time and evolve without direct human supervision?

The seed planted during that bar conversation has grown into a set of principles, activities, and now a set of cards that our teams—both data scientists and designers across every other discipline—use to ensure we’re intentionally designing intelligent systems in service of people.

We’re far from the first people to ponder this. We’ve been inspired by organizations like AI Now and Data + Society, books like Weapons of Math Destruction and Technically Wrong, academic communities like FATML and CXI. In particular, we’ve been eagerly following O’Reilly’s series on data ethics (and encourage you to read their free ebook, Ethics and Data Science).

To develop our own set of guiding principles, we started with people. We talked to folks all across the globe: We interviewed IDEO teams about where they found challenges. We spoke to our clients about where they saw intelligent systems go awry. We spoke to the public about where smart designs seemed to cross lines. We observed and read about AI systems that had gone off the rails and worked to understand how this might have been avoided. We learned a lot.

We came up with an original design, iterated on them, and landed on a set of four design principles and ten activities that can help guide an ethically responsible, culturally considerate, and humanistic approach to designing with data. These activities are meant to provoke thought; they’re a vehicle for introducing new ideas and stimulating conversations around ethics throughout the design process.

To start, here are our principles:

1. Data is not truth

Data is human-driven. Humans create, generate, collect, capture, and extend data. The results are often incomplete, and the process of analyzing them can be messy. Data can be biased through what is included or excluded, how it is interpreted, and how it is presented. Unpacking the human influence on data is essential to understanding how it can best serve our needs.

2. Don’t presume the desirability of AI

Just because AI can do something doesn’t mean that it should. When AI is incorporated into a design, designers should continually pay attention to whether people’s needs are changing, or an AI’s behavior is changing.

3. Respect privacy and the collective good

While there are policies and laws that shape the governance, collection, and use of data, we must hold ourselves to a higher standard than “will we get sued?” Consider design, governance of data use for new purposes, and communication of how people’s data will be used.

4. Unintended consequences of AI are opportunities for design

Just as with any design endeavor, we know that we’re not going to get it right the first time. Use unanticipated consequences and new unknowns as starting points for iteration.

To get started with the activities, you can download the cards here. We hope that these activities provoke dialogue and provide concrete tools to help our community ethically design intelligent systems.

Thank you to the larger team who helped make these cards come to life—Ben Healy, Jane Fulton Suri, Jess Freaner, Mike Stringer, Justin Massa, Connie Oh, and KP Gupta, who designed them.

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A design researcher, a business designer, and a data scientist were sitting at a bar. It sounds like the setup of a joke, but the conversation was actually quite serious.

As a user experience and interaction designer with a hybrid art and tech background, I’ve long been a fan of the concept of using art and design as a Trojan horse to make tricky concepts accessible. Through intrigue, curiosity, and play, these experiences can bypass our biases and open the door to understanding, without requiring deep comprehension. If you’ve ever visited a children’s science museum and watched kids excitedly engaging with subjects that would bore them to tears in book form, then you’ve seen the power of experience and play at work.

Meet ERNEST

That’s why my colleagues and I created ERNEST, an installation that gives the viewer the job of training a rudimentary artificial intelligence. Using facial and emotional recognition tech, ERNEST shows the user imagery and tries to see how happy it makes them. Our goal for this project was to engage users in a game-like experience to help them understand how machine learning models are trained, and subtly hint at the areas where bias could creep in.

Fellow IDEOer Matt Visco and I wanted to make sure ERNEST didn’t look like a modern computer—we designed it to look vintage. With its old hardware and nostalgic graphics, ERNEST doesn’t feel smart on the surface. Its look is meant to evoke a time when computers carried the promise of a utopian future, prior to mass connectivity and the ubiquitous collection of personal data.

The full installation uses five monitors, two computers, and three Raspberry Pis, which power several video loops that reveal the training data behind ERNEST, and give passersby a sense of the experience even if they don’t engage directly with it.

How it Works

ERNEST uses computer vision to perceive the user ambiently through facial recognition, allowing it to detect when a user is looking at it and how far away they are. When a user gets close enough, ERNEST comes alive and asks the user to help it learn. It then shows the viewer images intended to make the user happy, and gauges their emotional reaction based on their facial expression using a pre-trained model. The facial tracking and emotional data is displayed to the viewer in real time, encouraging users to make faces at ERNEST. Viewers can then validate the accuracy of the model to help ERNEST know if it was correct or not.

(Sound complicated? The video below might make it clearer.)

We installed ERNEST in IDEO San Francisco’s lobby for a couple of months, and also brought it to the San Francisco Art Institute Fort Mason Gallery for the CODAME Intersections exhibition in November 2018.

The Results

Many participants loved to challenge ERNEST, often emoting in varying ways through numerous loops of the game. Once, a group of participants spent nearly 20 minutes playing with ERNEST, takings turns to compare how it perceived each person.

When viewers interact and play with ERNEST, we’re helping them see that machines can have almost human-like perception, reacting differently to different faces, and sometimes being uncannily accurate...or completely wrong. The wrong guesses were in many cases more interesting, and were in fact a very intentional part of the design. We wanted users to see that artificial intelligence is sometimes not as intelligent as we might think.

ERNEST is meant to be a game, but what happens when real-world AI makes the wrong guesses? Or what if those wrong guesses are uneven, indicating an unintentional bias, such as working well for some faces but not others?

We wanted people to realize that designing systems that can ambiently perceive humans without direct input is rife with ethical concerns. And already, systems like these are being deployed at scale. The Guardian predicts emotionally-aware tech is already a $20B industry. Even something seemingly benign like ERNEST causes us to wonder—if an AI is trying to make the viewer happy, who determines what “happy” is? What if bad actors train Ernest to think that disturbing content is “happy?” What if the technology is repurposed to provoke anxiety or anger? What happens if we deploy technology like ERNEST widely?

Of course, ERNEST only scratches the surface of these big ethical questions, but we hope that it helps give people insight into how artificial intelligence thinks, and the ways its thinking can be flawed. The more that we as a society can start to understand these systems, the better we can judge their quality, and work to design them to be in line with our shared human values.

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Artificial intelligence and machine learning are among the hottest topics of the tech world, but some of us at the frontier forget that many people feel intimidated—or even afraid of—these technologies. The pop-culture trope of machine intelligence gone rogue has been a part of our cultural psyche for a good 150 years. Think 2001: A Space Odyssey’s HAL 9000, The Terminator’s Skynet, and The Matrix’s... Matrix. Combine that fear with arcane tech-speak like “recurrent neural network” and “generative adversarial network,” and in addition to feeling emotionally intimidating, AI and ML can also feel incomprehensible.

Feedback is a tricky thing. There’s always going to be differing opinions of right and wrong, and even if it’s explained to you in a calm, clear voice, it can sting like nothing else. But getting feedback on your work is the only way you'll grow. It forces you to rationalize your thinking and creative decision-making, and teaches you to swallow your pride.

I learned the hard way: A few years ago, I designed my first typeface called Emotiv. It was a concept for a messaging app that would help people express their emotions through language (instead of emojis).

Eager to get my work out there, I decided to send a sample to a very well-respected typographer whose work I greatly admired. Given this individual’s reputation (and my lack of experience) I was reluctant to share at first, but with encouragement from friends, I sent it along with an explanation of how it came to be, not really expecting a response.

A few days passed, and much to my surprise, an incredibly lengthy reply fell into my inbox and hit me like a ton of bricks. It was the toughest feedback I’d ever received. Alignment issues, inconsistencies, readability problems, the email went on and on. It felt like my career was ending before it even had a chance to begin. We designers consider our creations extensions of ourselves—meaning that we take the pain of feedback personally.

While I can't offer up permanent thick skin, I have come up with 4 mindset shifts that will help you get—and give—negative feedback in a constructive way:

1. Introduce constraints

The least helpful feedback goes something like, “Hmmm, I’m not sure I like this.” We all have personal tastes, but there is no build-off point from that—no way to develop and improve. Instead, ask the person giving you feedback to be constructive, give their rationale, and ask as many questions as they’d like, rather than give you a gut reaction.

2. Tag team

Rather than putting yourself on the receiving end, get involved in the process. Imagine that the work being critiqued isn’t yours and offer your own thoughts. That will help you stay focused on the work itself. Plus, by making the feedback process more of a collaborative effort, you can understand the work from new angles to make it better together.

3. Be Spock

Do your best to take your emotions out of the equation. Instead of hanging on every negative word, look for unbiased points that will help you better define and execute the work. Even if the person giving you feedback is using words like “I like...”, or “I don’t like…”, those words aren’t aimed at you—they’re aimed at uncovering the fundamental thinking or execution behind the work.

4. Don’t ask for the answer

When the feedback process unearths a problem with your work, it’s tempting to simply ask for a clear solution to the problem. But that won’t push you to go further and explore other possibilities. Solving the problem yourself gives you another opportunity to learn and grow your skills.

Looking back, I now see now that the typographer who crushed me was actually providing a great service. (Honestly, you could tell someone they are terrible at something in considerably fewer words.)

I’d made the same mistake my fellow design student had made in that first class—I reacted as if it was a personal attack on me as a designer. But that feedback prodded me to become much more critical about my own work, studying details that others might not notice, with an eye toward readability and alignment.

Getting negative feedback can hurt. You pour your time and effort into creating something, and with the swiftest of comments, it gets cut down. But receiving it not only makes your work better, it makes you better... especially at giving feedback.

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Nothing prepares you for the reality of receiving negative feedback. In one of my first design classes, I watched in horror as a fellow student had his work ripped in two for the first time in front of all of us. Shortly afterwards, he quit the course.

I help organizations cut through complexity by shaping how they show up, through brand strategy, identity, and storytelling.

Working at the intersection of brand and business, I bring an editorial eye and a bias toward making—turning ideas into tangible experiences that people can understand, trust, and believe in.

My work spans government, healthcare, financial services, media, and consumer goods, from launching Gen Z-focused ventures to building innovation labs and reimagining legacy brands. I relish moments of ambiguity and enjoy translating across teams, perspectives, and priorities to move ideas forward.

I started my career in editorial and digital design, shaping cross-platform experiences and identity systems in publishing and agency environments. That foundation still shapes how I work today: I’m detail-oriented, collaborative, and overreliant on the Oxford comma. I hold a BFA in Visual Communication from the School of the Art Institute of Chicago.

For 25 years, I've asked the same question: Who does this design exclude—and what are we going to do about it?

My work spans human-centered strategy, inclusive design, and qualitative research, with clients ranging from Microsoft, Google, and Verizon to the National Science Foundation, and San Francisco Unified School District.

Before IDEO, I taught elementary school in East Palo Alto and spent a decade doing design work with social service organizations—where I learned firsthand what it costs people when systems are built without them in mind.

I am currently writing User Error, a nonfiction book about digital access and the design decisions behind it. I live in Oakland, California.

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My expertise spans brand, communication, and product design across tech, education, the arts, and social impact.

I believe great work demands both high-level vision and obsessive attention to detail, and only happens through collaboration.

I bring an inclusive, hands-on approach and a deep understanding of business, which enables me to consistently deliver excellence while always asking why.

Before joining IDEO, I worked at the brand firms Pentagram and VSA Partners. I began my career as a designer, leading teams at the School of the Art Institute of Chicago and the Milwaukee Art Museum. I hold an MFA in graphic design from Maryland Institute College of Art and a BFA in communication design from the Milwaukee Institute of Art & Design, and have taught at some of the best design schools in the US.

I am responsible for IDEO’s long-term success in China and working with clients to use design as a tool to enable growth. Specifically, I have helped Chinese companies design holistic brand solutions through the development of their products, communication, services, and innovation teams, and I have helped multinationals expand their presence and influence in China.

I advise global leaders on developing China-led innovation and capabilities.

In over 15 years in IDEO Shanghai, I have worked on projects that use design to elevate the quality of the experience of healthcare products and services, streamline processes that increase productivity, create spaces and programs that promote and enable inclusive communities, and build next generation mobility solutions that are planet-positive.

Before joining IDEO, I worked at Philips Electronics and the Electrolux Group in Italy, the Netherlands, and Singapore on a number of breakthrough commercial products. I am a member of the Young President Organization in Shanghai.

Most AI products today are built for work—a space with clear problems and established systems. One founder noticed a gap: personal life is messier, harder to systematize, and mostly left behind by the AI boom. So she built Cue, a personal AI that lives inside iMessage and group chats, to go where the other tools haven't.

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In this episode, Becca Carroll, IDEO's Chief Strategy Officer, talks with Sida Li, co-founder and CEO of Shared Context Lab, about staying anchored to a human need while the technology around her keeps changing shape, why she treats her business model with the same rigor she'd bring to a product, and what it feels like to build a company at this particular, disorienting moment in AI.

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The conversation also gets into how Sida makes design decisions: the language Cue uses to describe itself, the tradeoffs behind building inside iMessage instead of a new app, and a real story about a business idea that didn’t pan out.

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This is the second in a two-part series profiling founders from IDEO's Startups-in-Residence program. The first conversation is with Johannes Seemann, founder of Sooner, on designing GenAI for the emotional side of money.

Most personal financial tools are built to run the numbers and optimize towards a budget. While that works for some, most people experience money as a lived relationship that does not neatly fit into a spreadsheet. Johannes Seemann and Becca Carroll discuss why money is emotional before it is mathematical, and what a human-centered approach to building a generative AI financial product looks like in practice.

Mina Seetharaman talks with Scott Shigeoka, author of Seek and Head of Curiosity Cultivation at the Eames Institute, about what distinguishes genuinely curious leadership from performative curiosity, how power dynamics shape curiosity, and why practicing curiosity can restore energy rather than drain it.

Mina Seetharaman talks with David Epstein, author of Inside the Box and Range, about why total freedom often produces average work, how leaders can design useful limits on purpose, and what organizations such as General Magic and Pixar reveal about the relationship between boundaries and creativity.