American businesses are on notice: To be competitive in today’s market, you must diversify your workforce.

One way to widen the talent pool is to pay closer attention to people who have acquired their skills through alternative routes. Millions of Americans learn on the job, in community colleges, at boot camps, or through life experience. According to Opportunity@Work, more than 70 million Americans are overlooked because of degree requirements. Despite their abilities, these “STARs” (those who are skilled through alternative routes) find themselves stuck in jobs for which they’re overqualified and underpaid.

Opportunity@Work, an innovative social enterprise, reached out to IDEO to help collaborate with companies, talent developers, and STARs seeking career growth. To make this overlooked talent pool more visible, we created a campaign and video to rally companies. We also designed a data dashboard to help regional employer networks identify qualified talent and potential partnerships with skill-building programs. And to provide STARs with direct support, we scaffolded the job-seeking experience, focusing on key moments like the interview process.

It’s time for businesses searching for talent to open their eyes, look to the STARs, and see what they’re missing.

83% of HR professionals said they had difficulty finding suitable candidates in the past 12 months.

62% of Black people, 55% of Hispanic people, and 50% of non-Hispanic white people have become skilled through alternative routes, such as community college, workforce training, boot camps, certification programs, military service, or job experience.

Over the past 40 years, inflation-adjusted wages have increased 8% for college graduates with a bachelor’s degree while decreasing by 15% for people with only a high school degree.

Thousands

of state jobs in Maryland no longer require a four-year college degree

skills-based

The White House is adjusting educational requirements for I.T. professionals in favor of a skills-based approach

For many organizations, frontline workers like grocery store clerks, nurses, hospitality workers, and transit employees are an essential part of doing business.

So much so that they continued to show up at the office throughout the COVID-19 pandemic even as everyone else went remote. As the point of contact with customers and key systems, these workers often know exactly when, where, and why things don’t work, and they come up with powerful hacks and workarounds to make things better. Yet these insights and innovations rarely make it to the corporate office. And that’s a problem: large organizations often hire design and innovation consulting firms while not taking advantage of a latent source of deep, in-house expertise. It’s equally discouraging to workers who would gladly share their ideas if they were only asked. No surprise, then, that frontline workers are quitting their jobs in droves.

What could companies learn by listening?

IDEO partnered with the Ford Foundation to create the Worker Voice Design Lab, where leaders from a port authority, an airline, and a health care provider worked alongside frontline workers. That led to the planting of a seed of innovation in each organization, with interventions designed with and by workers implemented operationally at the core of the business. In one case, a group of workers zeroed in on specific problems with such clarity that they were quickly able to develop a digital prototype for testing. No one was less surprised than the workers themselves, who simply said: Well, nobody ever asked us before. Sometimes the most innovative idea a leader can have is to listen, learn, and act on their employee’s smart ideas.

A large portion of the job churn since March 2020 has been concentrated in frontline services such as accommodation, food services, and retail.

Lack of career growth is the number one reason people leave their jobs according to more than 18,000 frontline workers across 150 companies.

2 pilot initiatives

being led by frontline workers in 2022

The climate era demands new offers and new ways of working.

Would you like to be able to plug your jigsaw into your truck? How about taking a fully reclined snooze after a long day of fishing? Questions like these led to quick prototypes that ended up in Ford’s new, electrified F-150 truck, which has more outlets than the average apartment and can power your entire home. This was no small update. The way Ford reimagined the truck experience from powertrain to power nap is emblematic of how much customer-centricity is now embedded in Ford’s culture.

For well over a decade, we’ve partnered with Ford in the U.S., the EU, and China to help the organization bring to life a shared vision of the future of mobility. Together we scaled new capabilities throughout the company by running proof-of-concept “beacon” projects and, to embed this new customer-centric mindset, built a human-centered-design hub called D-Ford. This organization within the organization has become a magnet for talent and is spread across six global locations: London, Shanghai, Melbourne, São Paulo, Palo Alto, and Detroit. Ford’s commitment to serving the needs of people and the planet is what propelled the rethink of the F-150, the best-selling vehicle in the U.S. for over 40 years. It was a high-stakes move, and one that represents a major turning point for the automaker: For the first time, its primary profit source would be electric. The new Lightning is still built Ford tough, but also built for the future.‍

Passenger vehicles produced 41% of carbon dioxide emissions worldwide in 2020.

One in every 20 passenger vehicles sold in the United States is a Ford F-150.

Before going electric, the Ford F-150 emitted about 100 tons of CO₂ over a 200,000-mile lifespan.

200,000

pre-orders of the electric F-150 truck, named one of Time's Best Inventions of 2021

Most Innovative Design Company of 2022

according to Fast Company

America’s leading retailers share a common goal—doing less harm to the planet.

The systemic challenges standing in the way require a bold new approach, and no single company can solve them alone. So Closed Loop Partners convened a group consisting of founding partners CVS Health, Target, and Walmart, along with 12 other leading retailers. As the innovation partner, IDEO helped launch a global search for breakthrough sustainable ideas that yielded more than 450 submissions from startups and entrepreneurs to reinvent the single-use plastic retail bag, with nine finalists entering a six-month accelerator.

New alternatives ranged from biodegradable solutions to systems that kept reusable bags in rotation. IDEO teams not only facilitated collaboration between startups and sustainability leads from partner retailers, but also provided a boost of additional expertise from industrial, data, and business designers. In a matter of months, teams were able to launch prototypes in select CVS Health, Target, and Walmart stores in California and New Jersey.

Everyone involved in the consortium knew that replacing single-use plastic retail bags is a problem that won’t be solved quickly or easily. But the Beyond the Bag challenge helped them learn that designing for the policy and infrastructure of tomorrow requires tangible steps, taken together, today.

A hundred billion plastic bags are used in the US every year, and less than 10% of them are recycled.

Every year, plastic retail bags are among the top ten items found on beaches and waterways worldwide.

9

stores tested solutions across Northern California

Millions of dollars

raised by two startups

2

startups acknowledged by Fast Company's World Changing Ideas Awards

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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.