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.

Direct feedback that teaches rather than chides requires trust, and trust takes time.

Unlike humans, AI craves to know when it’s wrong. The entire premise behind machine learning is that it learns from failure or success. For example, we may feel that weather algorithms always get it wrong, but they can only improve by comparing their forecast to what actually happened. It’s therefore our job to tell the system when it’s wrong and acknowledge when it gets it right—but that requires a level of trust.

We can often tell if our friends or partners are unhappy with our actions, even if they don’t directly tell us. We can read their facial expressions, subtle changes in their tone of voice, and body language. Machines, however, don’t have that kind of intuition. Until we’re all walking around with some kind of lightweight EEG machine strapped to our head, machines will need to find proxies for how to sense human emotions, desires, and preferences. The obvious way to do this is to just to ask us, but that is manufacturing a transactional relationship, not a trusting one.

All I’m asking AI is for a little respect

A good example of an AI asking for trust rather than earning it can be found in the personal styling services that are popping up. They are doing some amazing things in integrating data science into every component of their business to drive growth. But my experience put me in the awkward position of feeling like I needed to explain myself and share sensitive personal details with someone I’d just met.

Signing up for the subscription service begins with a long and detailed survey about body type and style preferences. I spent a good 30 minutes thoughtfully answering myriad questions to create my style profile, and yet I returned everything that they sent me in the first box. None of it jived with my personal style, and only one thing fit.

I had put the time into creating a relationship with the AI—training it with my intimate information, such as how my body was shaped—and that process had given me a false sense of mutual understanding. If it had just taken a look at my Instagram profile and sent me a box, I would have given it permission to get it all wrong. But its surprisingly clunky and unnatural way of “sensing” my preferences for clothes set an unrealistically high expectation of what was to follow. Questions about slightly nuanced styles of plaid let me to believe that it could understand I like simple patterns—and then it sent me a shirt better fit for my grandfather.

By asking me to train a system before we had established a relationship of trust, the AI had breached it before it had even formed. When I’m in a trusting relationship, I can forgive someone for an error. But this felt different—like I’d been duped into a false sense of intimacy. I’m going to try one more box, but I have a strong hunch I’ll be cancelling my subscription soon.

AI is a relationship

While rare, there are a few AI with whom I’m in a trusting relationship of mutual respect. I relish my moments of training them because they respect my time and provide me with value as I train them—even when the AI is mostly wrong. I’ve come to truly value those moments when they tell me I’m wrong, because they do so in a way that deeply respects my position as a human and their position as a machine.

The format of the playlist is likewise brilliant: I don’t need to rate the songs but simply listen to them or skip them after I’ve heard a bit, and songs that I love get added to my own playlists or saved to my phone. Over time, it learns my preferences and can dish me up even better tunes. There’s no artificiality to training Spotify, and each and every time I train it, there’s value back to me as the user. Most importantly, Spotify has earned my trust through helping me discover a slew of new artists and, in doing so, earned its right to be wrong. (I don’t really love St. Vincent, but I understand why Spotify thinks I would.)

But we’re not the only one doing the teaching. When it comes to “training” humans, Waze and Google Maps are setting the standard. Their features are clearly based on a deep understanding of the common human emotional conditions that we endure during traffic: stress, anxiety, impatience, and a deep temptation to bail on our algorithmically recommended route in favor of our own “shortcuts” (which are almost never shorter).

Maybe the most brilliant bit of human-centered design inside of these navigation apps is how they highlight alternative routes and how much longer they’d take. Instead of having to blindly trust the route the AI has chosen, it considers its own possible fallibility and assures us by showing us the other routes we might be considering. Thinking of bypassing the highway? That’ll take another four minutes. Want to cut through that residential area? Here’s some construction of which you might not be aware.

In this way, Waze and Google Maps serve as a sort of angel on our shoulder, counseling us away from our inner traffic-hating demons. They’re not “AI-splaining” or chiding us for considering alternate routes, but rather giving us the necessary information to make the right decision. They’re rooted in a deep respect of human agency.

At IDEO, we prefer to think of AI as Augmented Intelligence rather than Artificial Intelligence. Taking a human-centered approach to building relationships between AI and humans compels us to meet humans on their terms, building relationships of trust and respect, and always remembering that intelligent systems must exist in service of humanity, not the other way around.

Beautiful, human-centered, human-AI relationships are about understanding human beings and our wonderful, weird intricacies and inconsistencies. They’re about designing the experience of AI around humanity, rather than the other way around. AI can only function well if it learns from its mistakes, and that means establishing trusting relationships with humans so they’ll feel comfortable saying when it’s wrong.

This article was originally published in Quartz Ideas.

Illustrations by Cassandra Fountaine.

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It’s awkward to correct a stranger when they’re wrong. How did you feel when Miguel from IT, whom you’ve only met once, told you that “learnings” wasn’t a real word? Or when Robin lectured you about the correct pronunciation of “macaron” at the office holiday party?

But, for the most part, that relationship is passive. And that begs the question, what if we could teach our machines more actively? Could we school them on very specific things that are important to us? That thought became the perfect setup to build a little experiment involving selfies.

A self-portrait or a selfie is actually more than just one picture. It’s one picture out of endless tries which all look pretty much the same ... except that they don’t. At least not to the person taking the self-portrait. That person’s individual aesthetic, packed with subtle and subjective nuances, must be captured at exactly the right moment. Adding to the challenge, it's hard to explain to someone else the way you squint your eyes when you nail your smile or how you purse your lips to look roguish.

Enter Brainchild: a machine learning–based camera that can be taught individual preferences and make them accessible as a function. You can train the camera to understand how you like to see yourself without going through 100 iterations. And most importantly, it allows you to share your sensibility with somebody else.

Brainchild is just a prototype for now, but I'm hoping others will be inspired to build on the idea.

Beautiful, baby, beautiful

Machines are a billion times faster in quantitative tasks than we are. For a long time, the problem was one of not understanding quality. But that has changed with the improvement of so-called deep learning techniques—a subset of AI or machine learning.

By teaching Brainchild how you would like to be portrayed, it can assess the quality of what it sees in real time, and give you haptic feedback when it perceives you looking your best, so you can simply take that one picture.

It also allows others taking a snapshot of you to see you as if through your own eyes. Taking portraits is a very intimate art. Rather than taking the human out of the loop, Brainchild augments this human-to-human interaction by making it more collaborative.

A feel-good feedback loop

The intervals between interacting with machine-learning products and experiencing their learnings are often very long. There are many technical challenges, but more accessibility and immediate feedback would help us teach more actively and develop a better intuition for them. In return, machines could learn better and become more personal.

Brainchild is designed to provide immediate feedback. You teach it how you like to be portrayed, instead of letting it guess, and every picture you take based on its haptic recommendation serves as feedback on how well it learned and how well you taught it. (Plus, it's private. Brainchild works offline and stores all of your information locally, so there's no danger of it being shared.)

Smile!

How does the Brainchild prototype work? There are countless technical parameters we could talk about, but in the most simple terms, it makes use of a so-called transfer learning process based on a fine-tuned convolutional neural network—a technique frequently used in computer vision.

Brainchild needs to be taught five fundamentals:

1. What a human face looks like
2. How to learn about new faces
3. How to isolate the face in a picture
4. The way the portrait subject looks normally
5. The way the portrait subject looks when they deem themselves looking their best

The first two points require huge amounts of coding, data, number crunching, and time. That’s what consumed most of my time (next to working on the wrong file for a day!).

The third point addresses the fact that when you take a portrait there is always something behind you. To focus only on you without distraction, Brainchild extrudes your face from the background. That is something it learns before you use it.

Then you become the teacher. In order to learn how you look your best, it needs to know how you look normally. So, you feed it a few examples of both, either by taking new snapshots, or by using pictures stored on your phone.

To help Brainchild differentiate between the two picture sets you simply twist the front plate, switching between two learning modes. The serious smiley means every picture you take will teach Brainchild how you look “normally”. Switching to the happy smiley means every picture you take will teach it what it looks like when you look your best. This is how you get to know each other.

As soon as the camera spots you in a way that matches what you taught it about looking good, it will gently vibrate and light up the camera’s trigger button. The vibration and brightness increase the closer your match with your own ideal.

Brainchild doesn’t snap the photo for you, it just signals you at the optimal moment to do so. You can also hand the camera to someone else to capture you in the way you like to be captured. And the more you teach it, the more accurate it becomes.

It might seem mundane to teach a camera how to take a better selfie, but the technology has already inspired one of our clients to rethink parts of a high precision medical device that could dramatically reduce treatment costs for patients, and another software engineer to work on a playful version of FaceID.

I myself am now working on a body pose add-on for fashion photography, and am curious to see all of the other ways we might actively teach our machines and help them augment us in more personal ways.

Instagram: @brain_children
Concept and Technology: Jochen Maria Weber
Visual Design: Tiffany Yuan
Industrial Design: Leo Marzolf
Special thanks: Tobias Toft

We teach our machines every day. Voice assistants learn how to talk to us based on what we say to them. Navigation apps guide us based on the routes we take. Without millions of teachers like you, our machines would be much dumber.

What do you do when a panel is truly the star of the show? Can you still design meaningful participation from your guests beyond the Q&A?

This was our challenge when IDEO CEO Tim Brown, pioneering social entrepreneur Jacqueline Novogratz (Founder of Acumen), and visionary CEO Carlos Rodriguez-Pastor (CEO of Intercorp and Founder of Innova Schools) sat down for a conversation about design and bravery in our New York office. We knew these three would inspire guests with heroic stories of using design to create change at scale and challenging orthodoxies. But could we keep the crowd inspired after the conversation ended?

Our best bet, we decided, was to design a series of activities that would send guests on a heroic journey of their own—from hearing the call to adventure to facing fears to celebrating triumph over adversity. The result? A happy swirl of exploration and discovery, with guests staying late to gather around the hands-on exhibits like family in the kitchen at the holidays.

Here are seven ways to leverage a panel discussion and design an event they’ll never forget.

1. A moment to unwind

Create a ritual to help guests wash away the baggage of the day and be present for all that follows. We invited guests to partake in a sonic shower, an immersion in music that stretches the ears and awakens the senses.

Try this: An aromatherapy bar for deep breaths of invigorating or relaxing scents.

2. Active imagining

Even the most thought-provoking panels amount to a type of passive contemplation for listeners. Follow a panel with a prompt to actively imagine. We asked guests to hear the call of service, by imagining they were a person they serve and writing in that person’s voice in response to questions like, “What would it take for you to feel confident about the future?”

Try this: A finish-the-doodle mural wall or a listening booth with a guided meditation.

3. Space to be vulnerable

Offer your guests the surprising jolt of inspiration that comes from being vulnerable and naming your fears. We designed an anonymous confessional, tricked out with blacklight and digital wizardry, where guests wrote their fears on a private screen, then watched their words magically appear on a monitor in type for party guests to see.

Try this: Pair strangers up using matching name tags and asking them to find each other and swap secrets.

We designed an anonymous confessional to help guests embrace vulnerability.

4. Fast-tracked inspiration

Inspiration can also be fast and light. We sent guests on a tour of themed rooms devoted to New York’s legendary cultural movements—Punk, BeBop, Hip Hop, the Beats, and the Harlem Renaissance. Each room was chock-a-block with images, sound, and strips of paper bearing anthemic words from the movement. It was a blast of culture felt through the senses.

Try this: Give guests a deck of cards created from your favorite inspirational Instagram memes.

Guests were invited to tour the most iconic cultural movements in New York history.

5. Skin in the game

Putting one’s body on the line—through movement, physical sensation, or embodied action—is the ultimate form of engagement. For our biggest test of bravery, we dared guests to stick their arm through a hole in a black screen to blindly receive a semi-permanent Jagua-ink tattoo from an artist on the other side. No requests or restrictions permitted.

Try this: Ask guests to enter a space through one of two thresholds marked by declarations of identity, like “I’m an artist” or “I’m an activist.”

The ultimate trust exercise—blindly allowing a stranger to draw on your skin with semi-permanent ink.

6. Making

Who doesn’t like to roll up their sleeves and craft something fun? Making gives your guests an outlet for any new, creative ideas your event has inspired. We handed guests shortbread cookies, pipette bags full of icing, and examples of exquisite cookie decoration to emulate.

Try this: A collage-making table with old magazines, construction paper, scissors, and glue sticks.

7. Silly celebration

Even the most buttoned-up among us appreciate the chance to let their hair down. We gave permission to get silly with an IDEO designer’s GIF Dance Party, accompanied by another designing spinning live music. Guests grooved in front of a camera for a few seconds, then watched their avatar populate a digital dance floor on monitors throughout the space.

Try this: A box of masks and capes and the promise of a free drink for anyone who orders as a superhero.

We asked guests to get jiggy with it, and they obliged.

To summarize: Get creative. Get physical. Get weird. Your guests will thank you for it.

Got an idea for an out-of-the-box event activity? Share it with us on Twitter using the hashtag #DisruptThePanel.

Ever attend a conference? Then it won’t surprise you to know that every event planner out there wants to disrupt the panel conversation. (We’ve been experimenting with the format for years and sometimes a panel is still the best choice.)

There was a lot to celebrate. We’d launched an innovation lab and piloted new products as part of a larger, multi-year collaboration to expand the organization’s human-centered design capabilities and enable culture change.

And our collaboration had revealed something crucial: In order for the product to be successful we also needed to support the underlying organization, which meant looking more holistically at strategy, process, tools, and incentives.

That became an opportunity for me, an interaction and product designer by training, to apply my trade through an organizational lens. It turned out that the prototyping methods that I had learned could also be applied to people and processes. By experimenting, responding to feedback, and iterating, we could help nudge behavior change within the organization.

Here are the five big lessons I took away:

1. Speak their language

We were working with product managers, engineers, and designers, so instead of explaining what we planned to change with academic research and abstract frameworks, we used language they already understood. We were going to run scrappy experiments, learn quickly, and iterate. If the ideas didn’t work, we’d pivot and try something new. But instead of prototyping products, we were experimenting with people and processes.

Big insight: Meet people where they are. Ground organizational design in a familiar context, and make it tangible in order to build trust.

2. When facing big change, start small

Behavior change is hard. So, we started with small experiments. What was the least that we needed to design in order to learn—the minimum viable product (or MVP)—and to help nudge new behaviors? In one instance, to test our hypothesis on the need for a company-wide training program, we started by creating a workshop for one multi-disciplinary team of 10. Its success soon paved the way for a broader rollout.

Big insight: Organizational change doesn’t have to begin with big initiatives. Starting small with prototypes can lead to big learnings and start to shift behavior.

3. Measure impact in creative ways

Email surveys are an obvious way to take the pulse and determine whether experiments are resonating with individuals, but they can easily fall to the bottom of a priority list. We tested more lightweight, in-the-moment feedback methods. After prototyping a beer and knowledge-sharing gathering, we asked attendees to place a magnet on a board to indicate their responses to a few questions, like: “Would you come again?” and “Did you learn something?” It was an easy and immediate way to figure out if the idea was worth evolving.

Big insight: Simple and in-the-moment measurement tools can be enough proof of concept to move forward quickly.

4. Find the right ambassadors

Early on, I was determined to get all of the senior executives involved in our prototypes. What was I thinking? Their understandably divided attention and packed calendars made that next to impossible. In the end, some young, energetic community managers were the ones who embraced our ideas and helped push them forward. Not only did they have the time and passion for the projects, but they were also trusted leaders within the company. Community managers helped us organize an informal gathering of product people to share methods over beers. (Yes, beer again. When in Germany!) We asked a VP to simply show up. When he saw the overwhelming attendance and impact on the community, he became one of our biggest advocates. Teams that had been working in silos started to meet regularly. The more we demonstrated quick wins, the more senior leaders got on board to encourage new behaviors throughout the organization.

Big insight: The best agents of change may not be the most senior folks. Look for individuals with passion and social capital.

5. Make it stick

There are two things that we did that helped ensure that our ideas lived on after we were gone. First, we found owners within the organization who would commit to moving our ideas forward. Second, we helped create an internal group dedicated to maintaining momentum. This group provides leadership training and coaches teams to ensure both a top-down and bottom-up approach to behavior change.

Big insight: Prototypes are just the beginning. Organizational transformation requires dedicated owners and a multi-layered strategy.

It all adds up to a set of behaviors: Get scrappy, get tangible, find your people, and learn by doing. It never hurts to do some reflection from a rooftop, too.

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Not long ago, a coworker and I found ourselves contemplating the eclectic Berlin skyline. We were on the rooftop of our client’s office—a leading European brand in online retail—and thinking back on what we’d learned from embedding with them for a year.

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.