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.

To answer that question, we teamed up with Healthworx Studio to run an intensive five-week sprint and design a business that would address issues of access in rural health, leaning on AI to supercharge the process.

We kicked off with a lot of questions: Could we produce more rigorous, higher-quality results if we used gen AI tools to augment our team? Would it come up with innovative ideas for how to make healthcare more equitable? Could we get further faster? The answer was yes—with a lot of caveats. (For a deep dive into our approach, principles, and learnings, check out our Designing with AI Report.)

It quickly became clear that while Gen AI tools can’t replace human ingenuity, they certainly fuel it. When it came to generating solutions to a problem this complex, AI had very little to offer in comparison to human teammates. But it did help us innovate much faster and with more depth, bringing us up to speed on initial stakeholder context and synthesizing and incorporating datasets —crucial parts of the process that can take a lot of time. Here’s where we succeeded and failed, and what that taught us about using AI going forward.

Opening the aperture

Did a machine just listen to dozens of podcasts, summarize them, and give us themes in an hour? Yes it did. Thanks to tools like Preplexity.ai, which enables social listening on platforms like Reddit, we were able to quickly synthesize diverse perspectives from varied sources and distill themes that seamlessly integrated into our research process. 

Working with these tools feels like being bitten by a radioactive spider and gaining a suite of superpowers. We can rapidly develop contextual awareness of numerous stakeholders and their pain points in relation to the challenges we aim to address. With our lens widened, the questions we asked became more pointed and the concepts we designed more crisp. “The AI enables efficient pattern matching across massive datasets, unlocking value from information that was previously siloed or inaccessible,” explains Jaime Goff, Product Design Lead at Healthworx Studio. “By leveraging these capabilities, we can incorporate a breadth of knowledge beyond what our team could internalize before. It really expands what we can achieve by connecting us to data in new ways.”

The importance of coming together

But as our use of AI tools increased, there were unexpected sandtraps, too. For one, we noticed a steep decline in the quality of our team interactions. We thought that getting an AI boost would be “like having an extra designer in the room with us.” But the reality was we each retreated into our corners with our own AI assistant, forging ahead with new ideas. When it was time to reconvene, we were on wildly divergent tracks, and re-aligning to move forward as a team was an enormous undertaking. 

Another caveat: While generative AI tools helped us gather new forms of data, it was still critical to hear directly from the people who would be using these solutions. 

Nicole lives on a ranch the size of the City of San Francisco. After her husband broke his leg in a freak accident, she had to make a harrowing journey, traveling two hours to the nearest hospital. Stories like Nicole’s taught us a lot about what it’s actually like to access healthcare in rural areas, and the resilience it requires. It was the people we spoke with who brought nuance to the problem our team was trying to solve, inspiring our most critical insights and building confidence in our concepts. As much as we tried, we could not find an artificial substitute that could come close.

It was the people we spoke with who brought nuance to the problem our team was trying to solve, inspiring our most critical insights and building confidence in our concepts. As much as we tried, we could not find an artificial substitute that could come close.

Smelling the AI B.S.

When reviewing a few AI-generated venture concepts with the Healthworx team, the room fell silent. The concepts were all variations of the same idea, repeated and rehashed. “Generative AI can rapidly spin up concepts that seem good enough at first glance,” Goff says. “But when you scrutinize them, the limitations become obvious.” Even after extensive prompting with our AI co-pilots, we were still back to the same place, with a bunch of repetitive concepts. 

But when the team mined our own insights, we were able to find a truly compelling venture idea.

Late into the night, when the team was riffing, we shifted our approach from working alongside AI to guiding it. We had ChatGPT review and improve on its own ideas, asking it to strengthen the overall concept as it went. The tool acted like jet fuel, helping us add rigor and build out the venture, ultimately producing a successful pitch presentation that included high-fidelity mockups, early working AI prototypes, and an in-depth pitch deck.

Supercharging our process

We’re in the caveman era of generative AI, and there are plenty of unintended consequences to be concerned about. But we’re optimistic about how a human-AI partnership that leverages human creativity and nuanced subject matter expertise alongside AI tools allows us to quickly outsource parts of the process, add rigor, and iterate faster, supercharging design and innovation.

And while the AI hype is founded, its limitations, which became patently clear in the ways it addressed a complex challenge like rural healthcare, made us appreciate how important humans are to this equation. Goff says it best: “This project showed the value of individuals bringing their unique brains and nuance to the table to work alongside AI. Our minds provide the spark that drives real progress.”

For those who crave the details, learn more about our approach, principles, and experiments with our transformative collaboration with Healthworx Studio here or reach out to ai@ideo.com

Visuals created with Midjourney.

Healthcare has a lot of big problems to solve. Could AI help?

At a recent business roundtable, the topic was how to set product innovation up for success. I spend the bulk of my days helping organizations stretch to tackle business challenges by coming up with breakthrough ideas, so it might seem sacrilegious to allow those ideas to fail.  But since that breakfast, I found myself scrutinizing not only what failure looks like, but also how it feels.

There’s a saying that’s usually applied to writing: “Kill your darlings.” It’s a nudge to let go of a much-chewed-over clever phrase that doesn’t help the overall story.

We use the saying at IDEO, too. But our “darlings” are hypotheses or “sacrificial concepts” that we quickly put to the test and are willing to abandon. Iteration is the lifeblood of the design process—and the magic of it is that it allows for what Harvard Business School professor Amy Edmondson calls “productive failure.”

When companies face business challenges that require innovation, the instinct is to look for and land on a solution and sell it internally, so you secure permission to move forward. And what if the path you’ve chosen doesn’t pan out? We have a natural instinct to persist: The company has allocated money and resources, and it’s easier to hang onto the hope that a turnaround is just ahead than to pivot. 

But hope isn’t enough in an era of new baselines like disruptive AI and climate change. Companies must stretch further, build resilience, and find ways to meet an ever-evolving new customer. 

To keep pace, we have to reframe  business challenges as human challenges: What is desirable from a human point of view? What do people really need? How can we help a brand like H&M meet its customers’ desire to use less plastic? And also help the retailer meet its climate goals by reducing waste from its supply chain? Insights drawn from in-depth interviews with and observation of customers and other stakeholders combined with data already collected by the organization help us generate hypotheses that we can quickly test. 

In the case of H&M, we suggested replacing the plastic packaging they used to ship online orders with paper. But there were many hurdles to clear to make sure that would work across a global supply chain with multiple brands. It ended up taking several months and multiple pilots to ensure the more sustainable packaging would work.

Finding out that something doesn’t work—and, crucially, why—sets you up to more deeply understand the constraints you're operating within. And reframing an abandoned concept as a learning rather than a failure allows you to prioritize continuous improvement, keep teams motivated, and build stakeholder confidence . 

Organizations may feel like they don’t have the luxury of time to test innovative ideas. But proof of concept needn’t take more than one to two weeks and can be done at low-cost. One timesaver is to test hypotheses in parallel. That approach also allows teams to let go of darling concepts and view the goal as learning rather than validation. 

By one estimate, 95 percent of new products fail, and baking failure into the exploratory phase helps ensure the product or service that emerges has been battle-tested. A hypothesis that doesn’t work out isn’t a Failure, it’s a failure, and that feels different. In the case of H&M, prototyping packaging options not only led us to a paper solution that cut plastic, it led to us digging deeper on climate goals and ultimately redesigning their supply chain to cut millions of tons of waste.  

At the roundtable, we talked about the challenge of working within a company culture that doesn’t tolerate failure. I’ve worked in a number of those environments and cultures; they’re tough. Failure carries emotional baggage. If you got a taste of it as a child and were a diligent but mostly average student like me, you did everything you could to avoid seeing that red letter atop a test ever again.  

I’m currently working within a culture that makes room for failure. Some of that is inherent in the design process, which is optimistic and pragmatic. But my colleagues also share an important mindset. They focus more on impact than the idea or activity that produces it. There is a deep respect for diversity of perspective and a shared belief that if there’s a better way to do it, we’re going to do it that way. 

In IDEO’s London studio, we have a framed, handwritten quote: “I don’t hate you, I just hate your idea.” It was never intended to be framed, but it’s a fabulous reminder about not taking failure personally. If we truly share a collective goal of doing well and doing good, we need to generate and test as many ideas as we can—and be okay with killing our darlings to get there. It’s the only way to make real change.

Is your intolerance for failure holding you back? I’d love to hear more.

Should we allow new ideas to fail?

Two of those shifts? Generative AI, and our rapidly changing climate.

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Together, these two forces are moving both the people side of the equation—what we need and how we behave—and the how side of design: what’s possible.

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Welcome to the Climate Era

A new age is upon us. Steam propelled the original Industrial Revolution; electricity powered the second; preliminary automation and machinery engineered the third; and cyberphysical systems—or AI-powered computers—are shaping the Fourth Industrial Revolution.

But the universal context is our climate. The Climate Era is our time-windowed opportunity to reverse the costs of the industrial and digital eras—creating a more abundant future for all. The way through it is to find ways to reinvent our economies, in part by turning necessary choices (like conservation and circularity) into desirable ones.

To the degree that the climate crisis can be solved, we already have solutions and technologies. The central question of the Climate Era is not can we do it? It’s will we do it?

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Hello, generative AI

If the challenges of the Climate Era have been building up over centuries, the transformative power of generative AI seems to have hit the world in a flash.

And this is a critical moment to interrogate our relationship with technology. At IDEO we do that through the tools and habits of design: building to think, taking time to understand people deeply, investigating the farthest consequences we can imagine, and embracing new skills, disciplines, and ways of being in the world through experiments.

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Combined forces

These two forces—AI and the Climate Era—have the potential to change everything for everyone. And in some ways, they already have. More often than not, AI and Climate thought live in different conversations. But what might happen when they’re brought together?

The pull of personality

Here’s an example of how AI might help us be climate-friendly manufacturers and consumers: It can help you get to know your clothes before you buy them.

We want and we need to build a circular economy. But its biggest challenge is scale: getting to the necessary infrastructure and processes, and—maybe the most challenging—getting enough people to participate.

There are signs of shifts at the policy level: You see it in Europe, for example, where the EU has a regulatory framework to promote (and require) circular behaviors from both businesses and consumers alike. And more and more people are participating in circular-like ways, such as thrifting. We see younger consumers pushing brands to become more active in developing and promoting sustainable versions of their products (so long as they’re not more expensive).

All that made us think about a pair of jeans.

Jeans lack the physical traits necessary for conversation. But, for an exhibit of speculative design at IDEO, we imagined them capable of communication. 

For starters: We might ask the jeans about their (un)life story, what went into their creation, or how they like to be treated. We might learn about where they were manufactured, their previous owners, and how to fix them if they ripped. Knowing all this about your jeans would give you a much better sense of whether they were a good fit.

Through AI, all of us will soon be conversing regularly with non-humans. And what else might “speak” through AI? Vehicles that remind us that they’re happier when filled with passengers and bound for the carpool lane?

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Speaking for the trees

Most of the sustainability problems we seek to fix were created in the design and strategy choices that were made early on in a product’s journey. The lifecycle analysis is a robust process. But it’s costly and generally retrospective, analyzing only those products and practices that already exist.

What about when we’re exploring different potential options and what could be, not what is? 

AI can help us incorporate a real sense of the “true cost” of a product and give nature a seat at the table early on. AI that draws on scope 1,2, and 3 datasets could help protect nature’s best interests in the decision-making phase. To be credible and useful, such an AI would need to synthesize scientific data, cultural data, and archives of experiments. And it would need to have some ability to understand the ground truth of things: learning from both human and technical inputs how things really are, right now, in the soil, in the ocean, in the community, and on and on.

With such a nature-centered AI in play, deployed ethically, we can imagine it occupying different roles and settings. As an advocate in the boardroom (where it might pose strategic questions or even cast a vote), or as an inventor in the materials lab (where it might suggest radically more sustainable ways to use resources and optimize production). ‍

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Everything in play

When we talk about making great choices in the Climate Era, especially at the policy or regulatory level, we’re talking about something unbelievably complicated. There are so many factors to consider, in so many dimensions.

And AI can help us think systemically. Take something like fishing. To regulate it, we need to understand  the immediate economic impact (such as business profit); the effect on communities and livelihoods; taxation and employment; the effect of granting more or fewer fishing licenses; how to balance production and protection of spawning areas); and biodiversity. AI can synthesize all of that information and data and make suggestions that expand our imagination about what’s possible. 

Another thing artificial intelligence has a knack for is running simulations. What if AI could help you simulate the tradeoffs among biodiversity, job creation/local livelihoods, and business success?

We imagined this kind of thing in a piece of work with our friends at Conservation International.

A simulation is often quite technical, and AI is already great at that. But we can also imagine an AI pushing people to consider their choices in other ways. What if it could point you to the right humans, on island nations for example, to enrich your understanding of potential impacts, far beyond your own frames of reference?

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The age of transformers

There are so many ways the Climate Era and AI, two transformative forces, might collide in service of building better futures. We picked out just three:
• Driving consumer adoption and adaptation by making things that are better
• Optimizing and reimagining production by giving nature a voice and a seat at the table
• Radically reworking how we make climate choices, especially at the largest scale

But, of course, they’re not the only transformers at work. We are, too. Especially those of us in positions of power and influence.

The Climate Era is here.
The Age of AI has arrived.
And it’s still our world to make and remake—for the better, if we choose.

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‍This article is adapted from a session delivered by IDEO in NYC at the 2023 FastCo Innovation Festival. With editing support from Christina Drill.

The problems we’re being asked to solve are changing. It’s less about helping partners innovate in incremental ways, and more about big transformational shifts in how we live and work.

In some cases, we knew nothing about the people we were trying to reach, so addressed them with the default direct marketing salutation, “Dear Valued Customer.” Finding the target audience was like being spun around blindfolded, then praying you were walking in the right direction.

Thirty-seven years later, we know virtually everything about everyone. Thanks to data mining and feeble privacy laws, we can pinpoint your exact location, health status, consumption habits, and, troublingly, what makes you laugh, cry—even think. All of that data is now being poured into the greased pan of generative AI where—we are promised—it will bake the most delicious cake, made just for us.

From direct marketing to AI-driven personalization, I’ve witnessed a transformation in how businesses reach their customers. We've never known so much about people, and yet we've rarely understood them less. In my view, using data alone to understand people has the same flattening effect as “Dear Valued Customer.”

But there is an antidote: Human-centered design.

Goodbye “Dear Valued Customer”‍

Once, at an international conference, I heard a speech by someone who worked for a large social media company. The premise of the talk was that a person’s “likes” could mirror their answers on a personality test. The more likes the social media company could analyze, the better they could predict a person’s personality—and to a level of accuracy that could beat what your friends knew of you; beat your family; and maybe know you better than you knew yourself.  

With that kind of knowledge, companies are able to design user experiences that feel like intimate conversations. But are they, really? Or is it only the illusion of intimacy—the hackneyed output of a data-driven predictive power?

It made me wonder: Is how we appear online—even to ourselves—who we really are?

Of course not. People are not reducible to their preferences. People contain multitudes. People change their minds, regularly and often. They respond to things that feel authentic and responsive to their experiences and identity—especially if they have historically been written off, underrepresented, or marginalized. 

The new customer, if we can imagine them in their infinite richness, has in recent times slogged through a global pandemic; discovered the unwelcome uplands of hiked interest rates and housing shortages; and likely contended with some form of professional burnout. Human lives are necessarily messy: You can’t rely on troves of data and canned messages to reach them, let alone persuade them. People can smell a door-to-door algorithm from a mile away. 

‍The best organizations are able to stretch how they think about their customers. The most successful businesses are able to understand and reflect back to people things that they don’t even know about themselves. ‍

‍The power of starting small ‍

In China, a client once questioned IDEO’s decision to root an entire concept in the preferences and needs of a small group of people. But when the product was delivered, the client recognized a level of human understanding that data alone could not achieve.

My time at IDEO has shown me that understanding people requires research at depth. For us, that often means ethnography, and you don’t have to have thousands or hundreds or even 50 people in the room to do it. What you need is a small sample of people with a diversity of lived experiences whom you get to know very well. 

Starting small requires designing with people and communities rather than for them, too. Innovation doesn’t spring from our heads as Athena from the forehead of Zeus; it's uncovered through the careful and considered use of tools, mindsets, and methods which we share with teams and communities.

‍Great organizations recognize that the work of understanding their customers is never complete. They continuously challenge themselves to listen and respond to what their customers are telling them, not only through data, but also by including them as co-designers.

The brutality of perfection‍

I once had a custom suit made for me for my wedding. To appear cool and unconventional, I asked for a red lining. The tailor wondered if I would still be fond of that red lining in 10 years. A simple question based on lots of experience. Upon a moment of honest self-reflection, my answer was, no, I would not. So, I followed his advice. I still wear that suit today; not once have I wished for a red lining. Of course, a company selling that same suit to me based on tracked preferences would’ve gladly hawked me any lining I wanted. But I am not sure I would trust that company again. I’d move on.

‍The organizations that will endure will be the ones that stretch their ability to deliver long-term, unexpected value to their customers.‍

I am thrilled by the possibilities of generative AI. IDEO’s experiments with emerging technology are as fervent today as they’ve ever been. And one of the qualities of which I’m most proud is our collective hunch that the most interesting opportunities lie in the messiest places.

That runs counter to the brutal attraction of data and AI in the current moment: an implied promise that an objectively “right” answer is within reach. Much of what we love in the world is so wrong it’s right. Perfect is not interesting, it’s not personal. In our pursuit of the spotless and ideal, we lose the essence that makes us human. The truth is, we value imperfection over perfection. 

New customer, new organization, new baselines ‍

I believe we’ve now reached an inflection point where many of us are experiencing a similar moment, only all at the same time. The last few years have changed how we work, how we socialize, how we spend our money, and how we think about our time. And we are being pushed to rethink how we do business, too. 

One of the baselines affecting us all is the arrival of the Climate Era. The planet reminds us daily that we have entered into a new normal. July was the hottest month on human record, impacting anyone who works outside or without AC—such as the drivers and  workers delivering boxes upon boxes to our doorsteps.

We can expect increased absenteeism and reduced efficiency, much more disruption to supply chains, and customers moving away from known polluters and toward brands that reward their conscience and their wallet. Climate regulation is coming too: The EU is working to impose tougher rules on  production and consumption in fast fashion.

Yet, while two-thirds of businesses are affected by climate change, few are doing enough to prepare for it. If we’re to avoid catastrophe, we’re going to have to redesign everything. And, if we want people to adopt Climate Era behaviors, we’re going to have to make things that are irresistible to them.‍

That means creating sustainable products and services that are simply better than the competition. By stretching to meet new and emerging customer needs, organizations can create products that people love and that are fit for the Climate Era.

When the instinct is to contract, great leaders stretch ‍

The SF adman Howard Gossage had this saying: “Nobody reads advertising. People read what interests them. And sometimes it’s an ad.” After 36 years as an advertising executive, I know better than anyone that we can’t always predict what will interest people.

But now, as the leader of an extraordinary community of designers, I know we have ways to help organizations figure it out. Creative, mind-bending ways that leaders and their teams can stretch to meet their markets and the new customer.

How? By continuously reassessing and expanding our understanding of what people want and need, with care, imagination, and sensitivity. We owe that to people, and we owe it to the planet all of us call home. 

Because in the end, the things that make our time here on Earth worthwhile are the things no algorithm can come up with on its own, no matter how much of the internet it’s ingested. They’re the irreducible things that make us who we are.

Early in my career, I worked on direct marketing mailers for British Telecom’s high-value customers.

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.