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:

If Procter and Gamble (P&G) were a city, it would be the size of Boulder, Colorado. The company employs more than 100,000 people in 70 countries. Its research and development team is made up of more than 20,000 specialists working across locations, languages, and areas of expertise, from cleaning chemicals to paper products to over-the-counter medications.

P&G approached Datascope to help the company connect these researchers to one another and the rest of the organization. In working with P&G leaders, Datascope found that the company needed a better way to access and leverage employee expertise. Managers routinely got requests from researchers looking to work with others in their subject areas, but didn’t know how to identify the right partners or set them up for fruitful collaboration.

Datascope gathered internal data, including unstructured research data on the scientists’ interests and who they partner with most often. The team used that information to develop two new systems that bridge the gap for P&G researchers and managers. The first is an internal search engine that lets managers quickly find and connect the right experts across P&G offices worldwide. The second is a data visualization tool that highlights subject areas ripe for more collaboration among experts and research teams, who may already be asking similar questions. This intelligent tool can surface relevant, timely information managers need to connect their teams.

P&G already had a practice of collecting information for product research, but it wasn’t until Datascope came on the scene that the company took advantage of large, multi-layered data sets and made them more intelligent, so leaders could expand P&G’s expertise through new global partnerships.

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:

The second a smartphone debuts, buyers, bloggers, and journalists begin writing comments and reviews—and users start troubleshooting. Motorola Mobility wanted to tap into this river of data, but didn’t have the right tools to collect and respond to it.

Motorola’s design, engineering, and service teams hoped to identify product problems early, address them quickly through customer support, and ultimately fix them in future releases.

So Datascope built a custom engine that aggregates and analyzes feedback from hundreds of millions of phrases and internet references, drawn from consumer sites, user forums, news coverage, social media feeds, and product reviews. The tool parses key, product-specific information and routes it to the right Motorola teams: hardware, software, connectivity, and interface design, to name a few.

The analytics and visualization engine not only studies product performance in real time, but it also uses algorithms to gauge customers’ emotional reactions: Do they like the phone or hate it? Do they have complaints? Are they recommending it to friends?

Datascope’s tool translates all this data into simplified to-dos that are sent to the correct service and repair staff before user issues can mar a product launch or even the company’s reputation. And as engineers discover more about how a phone performs in the real world, they learn how to avoid making similar mistakes in the future.

The tool proved valuable as soon as it launched in 2012: When Motorola released the RAZR M smartphone, customers had a hard time figuring out how to use wifi and voice features at the same time and lodged complaints online. The engine recognized the pattern of complaints and alerted Motorola's customer support team, which was able to post responses with clear instructions in every relevant forum, turning a potential customer satisfaction problem into a positive interaction.

Motorola continued to use the engine to address issues in later releases of the RAZR M. The advance warning made engineers’ lives easier, while better handsets and software made for a more seamless customer experience. Improvements were also evident in the RAZR M’s well-reviewed next generation, the RAZR MAXX.

Based on the tool’s success, Motorola used it to improve the company’s supply chain and product development process. And beginning in 2014, with the Moto 360 smartwatch, Datascope’s analytics engine has been used to gauge performance and public sentiment not just for new smartphones, but for Motorola Mobility’s entire line of products.

For most parents, ensuring their child’s proper nourishment is a top priority. But that’s not always easy, especially for parents on the go. Plum Organics, an organic baby food company, set out to solve that problem by providing families with pureed fruits and veggies in pouches, making it easy for them to feed their babies. Plum approached IDEO for help designing a non-pouch package that could showcase the vibrancy of the ingredients within.

By conducting research and in-person interviews with families, Plum set out to ensure that the new product was both desirable and functional for parents and their babies. By joining families in their homes, IDEO was able to gather essential insights that helped inform prototypes and the final design, like the fact that nothing can replace the feeling of making an intimate connection with a child through spoon feeding; that baby food is often wasted if a parent can’t remember how long a product has been in the fridge; that families struggle with how to spoon-feed their children on the go without making a mess, and that both parents and retailers were concerned that baby food jars don’t stack securely on shelves.

With those insights in mind, the team designed a transparent bowl that allows consumers to see the natural color of Plum’s vibrant, organic food. A resealable lid makes it easy for parents to store food between feedings, and the container includes a feature that allows them to track the day that they opened the pack to ensure that they don’t end up throwing away perfectly good food. Lastly, the new package is easily and safely stackable and includes a divot in the lid for parents to rest a spoon on, making for a much cleaner and more sanitary feeding experience.

Baby Bowls for Plum are now available at retailers nationwide and are a natural evolution for the brand, helping Plum continue to provide high-quality, organic baby food for consumers and their children, even if they’re eating on the go.

Accessing our genetic code is as easy as spitting in a tube, but how can we benefit from all that DNA data? IDEO surveyed more than 1,000 Americans about the gene sequencing services they want. "Give me things I can act on,” one respondent said. “Give me advice, action plans, apps, and tools. Information is just air until I can put it to use." As it turns out, tools that can translate our genetic information into better life choices—to improve our health, chart our family history, or even find an effective exercise routine—are hard to come by.

Inspired to organize and apply the wealth of genetic data in all of us, Helix envisioned the first online platform for products that offer insights based on a person’s unique DNA sequence. The startup’s founders approached IDEO to help them get to launch by identifying their future market segments and designing their brand and product offering.

Helix sequences all 22,000 of your genes from one saliva sample—sent in a mail-in kit—and hosts a marketplace of products developed by trusted brands and innovative developers that explore your health, ancestry, entertainment, family, fitness, and nutrition. Similar to the Apple app store, Helix lets you pay individually for the products you want and is a platform for developers to launch new offerings over time. After you've provided a DNA sample once, every product in the Helix store is made available to you on-demand. So, as new products are launched and new discoveries are made in the field of genomics, the data from your original sample is all you’ll need to keep exploring your personal genetic insights.

IDEO engaged a range of users, including early adopters of at-home genetic tests and “quantified self” enthusiasts, and surveyed potential Helix customers across the country. That qualitative and quantitative research validated Helix’s “app store” business model and provided key insights into the products people were most interested in.

Through the partnership, Helix uncovered what users need most from a genomics company:

• to prioritize the accuracy and privacy of DNA test results
• to encourage a sense of discovery and exploration of our genes
• to celebrate each individual’s unique qualities

A team of ethnographers, data scientists, and designers at IDEO helped direct the startup’s brand approach (including its name, Helix) and crafted a blueprint for how the company connects with customers and presents its product. The Helix store launched in July 2017.

Our DNA used to be a mystery—something we guessed at by observing our parents. Now, easy access to our genetic code—and the tools to truly understand it—arrives on our doorstep.

Earlier this year,  Snapchat introduced My AI, a relentlessly cheerful chatbot powered by OpenAI’s GPT technology. The avatar, pinned to the top of your chat feed, was ready to respond to every passing thought, be your 24/7 rant buddy, or even…your new best friend.

You might imagine that Gen Z, cradled by the arms of technology from their earliest friendships found on Club Penguin or Minecraft, would welcome My AI. After all, this is a generation for whom dating starts with the subtle “like” of a post or in the DMs of a swiped-up Instagram story.

But in a surprising twist, Snap’s chatbot was an instant flop, resulting in a spike of 1-star reviews.

That tracks with the responses of the 13- to 21-year-olds we spoke to, all of whom voiced a resounding “no” to the idea of AI infringing upon their relationships. Rather than forming attachments to the programmed responses of AI, they are interested in cultivating genuine bonds with others that don’t require an algorithmic intermediary.

“How does this change our expectations of real life people?” asked one 19-year-old. “I feel like that could be super problematic for friendships because you're like, oh, I just want this person to be different. Why can't they talk like this? Why do they laugh like this? Why can't they understand this? Why don't they know everything about me? Why can't they read my mind?”

Young people already feel the damage social media has had on their relationships and mental health. And they're wary that AI will interfere with the relationships they’re just learning to foster.

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Meanwhile, brands are in an arms race to create AI companions and AI clones that can be integrated into products and services. But when our team put a series of hypothetical Gen AI-powered relationship products in front of a group of young people, they balked and even expressed discomfort. They want technology that augments human relationships, not bots that replace them.

These insights led to three principles that we’re using as guideposts as we design this space.

1️⃣ Skip the engineered reality; reflect authenticity

Perfect, personalized AI bots might breed dissatisfaction with flawed human friends. Plus, they’re just plain spooky. Gen Zs told us they would prefer tools designed to help them embrace the imperfections of relationships and help them navigate. “I don't like the idea of being able to mold someone,” one respondent told us. “One of the teachings that I feel is super valuable in my life is acceptance and being able to go, okay, this is where I can meet this person.” Wary of social peacocking, face filters, and all the doctored images of social media, they feel AI friends would only further the fakery they’re actively trying to undo.

2️⃣ Elevate human intuition and empathy

There is a real concern that an over-reliance on AI could cause people to lose touch with their intuition. Gen Zers know that awkward moments with others—conflicts with friends, job interviews, even a bad vacation—are part of the human handshake. “Relationships are about you learning as you go,” another respondent said. “You're not going to learn how to resolve conflict by yourself, you're not going to learn how it feels to be lonely and push yourself to go meet people.” At the same time, they’d gladly accept help with maintaining friendships. A personal coach that could suggest activities or check calendars for times when you’re both free? Sure. Relationship advice? Bring it on. Perfectly streamlined interactions? No thanks.

3️⃣ Build in transparency to gain trust

The people we chatted with were concerned about AI accessing their conversations. “There's a lot of personal things that my friends and I talk about. And I wouldn't just want a third party listener all up in the mix or storing photos or information. I wouldn't want to feel like it knows my whole life.” They want to know how much listening AI is doing, and how their data will be used by the companies that create it. They’re concerned about the racism that has surfaced, and how a system that reflects human bias might shape their perceptions of their own identity and the world. The concern is well-founded, and presents an opportunity for companies to be transparent about the information they collect and use to improve AI models, and mitigate unintended consequences.

Snapchat's My AI and the host of potential AI-powered relationship products may seem attractive, promising the allure of companionship and understanding. Yet, this generation, while tech savvy, recognizes the value of genuine, organic human connections. The charm of flawlessly crafted bots pales against the nuanced, idiosyncratic, tender core of human interactions.

The next generation has opinions about what we build, and their message is clear: AI is welcome to augment, enhance, and support, but when it comes to forging meaningful relationships, humans must remain at the helm. It’s a potent reminder that while technology shapes our world in novel ways and companies vie to be first to market, the essence of humanity—the value of mutual understanding, the beauty of our imperfection, and the need for companionship without a whiff of profit motive—should never be sidelined.

As we step into a future where AI is integrated into every experience, let’s remember that the best guides are our own instincts, not a bot trained on reading the internet. The collective wisdom of Gen Z might just be the compass we need.

Is your organization interested in designing more human-centered AI experiences? Let’s talk.

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If you've missed Parts One and Two of our Gen Z + Gen AI series, you can catch up here and here.

AI helped you with your final paper and made your workout plan—why not have it help resolve a conflict between you and your friends, or help you pick your career?

Because that’s where artificial intelligence crosses the line from innocuous to intrusive—at least for the group of 13- to 21-year-olds with whom we spoke. To better understand how the next generation will respond to a new wave of AI products, services, and experiences coming online, we prototyped hypothetical apps to elicit feedback. “AI Passion Coach” for one, is a guide that identifies your skills and makes suggestions for how and where to apply them. That didn’t go over so well. “I’m all for AI helping me find the most optimal way to learn once I know what my passion is,” a college freshman told us, “but finding a passion for me? Not so much.”

After sharing six concepts, we came away with some strong hunches about how this cohort wants to show up in the world—both in person and digitally. They’re not looking for products that can be creative for them, they want tools that help them be creative themselves—a subtle but important difference.

Just as digital maps have ruined our collective sense of direction, Gen Z fears that the generative AI’s shortcuts and automations may diminish their ability to form their own identity.

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As one 19 year-old explained, “It's so much more valuable when you experience and learn something yourself versus being told it.”

Several feedback sessions on AI Passion Coach, along with two other hypothetical concepts: AI Venture Accelerator, a creative co-founder that helps you bring your idea to life, and AI Muse, an idea generator that accelerates your creative pursuits, yielded insights from which we drew three design principles for creating products and services that are more aligned with what young people want. If your business is integrating generative AI, consider these guidelines:

1️⃣ Use AI to Scaffold the Creative Process

The Gen Zs we talked to don’t want to be handed the answer. They want to develop the capabilities to create something of their own. “I think there's a line where AI can provide the groundwork and help be a resource, but then we get to choose what we do with it from there,” one 19-year-old said. Exploration, experimentation, and reflection are important parts of the creative process that young people don’t want to see stripped away.

To align with that desire, companies can create AI services that help users discover and learn why and how something is created. Those aged 12 to 25 told us over and over again that being able to adjust their level of input, and add their own vibe was very important to expressing who they are.

2️⃣ Lower the Barriers to Entry

This cohort recognizes that there are tactical skill sets that they and others may not have access to. They welcome AI opening up opportunities for those who may have great ideas, but lack the knowhow to execute them. “I’ve been working on developing an app for sustainability. I can't code, and I don't know how to make an app, but I had the idea and wanted to make it real,” a college freshman shared with us. Instead of removing humans from the equation, companies could leverage AI to help users jumpstart their ideas and offer access to the resources and knowledge necessary to turn those ideas into reality.

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3️⃣ Connect Creative Communities

Gen Zs find a sense of belonging and community through creative pursuits and look for those who share similar interests. “I feel like the beauty in creating things is definitely the insights I'm getting from other people,” said a 19-year-old entrepreneur. Just as mobile phones consume our attention, they suspect that other emergent technologies will isolate people and put optimization and productivity above the slower process of sharing ideas. “You achieve things more quickly,” said a 20-year-old student, “but you're lacking the relationships that you build over time when trying to achieve those things together.” For companies looking to augment human creativity, this presents an opportunity. Instead of being a generator of machine-made solutions, AI can be a facilitator of human collaboration, allowing people to share tips, learn from diverse experiences, and build community.

As generative AI upends the way humans work, there’s a lesson to glean from this research. Generative AI’s omniscience and ability to generate staggering creative output almost instantaneously is undeniably seductive. But the fundamental values that we cherish—our creative agency, our ability to actualize new ideas, and our need to bond with others through collaborative work—are all key to the successful adoption of the AI products and services of the future.

These principles are a good starting point for how to innovate wisely with human needs in mind. In Part III of this series, we will dive into how AI might impact the next generation’s relationships and mental wellbeing.

Missed Part One of our Gen Z + Gen AI series? Head here.

It wouldn’t be a stretch to assume, then, that those between the ages of 12 and 25 would glom onto everything generative AI.

But that’s not what we found.

IDEO embarked on a data-driven approach paired with qualitative research with a group of Gen Zs, asking them what they think about the AI that so many companies are rushing to fold into new and existing products. The findings immediately challenged many of the prevailing assumptions about Gen Z.

As companies begin to leverage AI to power everything from art and music generators to dating apps, and even personal companions, it’s imperative that we understand how people will respond. This is a group that has already weathered the consequences of untested technology thrust upon them during their formative years (hello, social media), and it’s only fair that they have a say in shaping the next generation of technology and determining what aligns with their needs, and what disrupts their core values.

“I love being deeply connected to my intuition,” one 19-year-old told us. “And I feel like this technology can truly interfere with that and be super invasive to our natural rhythm and flow and trusting ourselves.”

To uncover ways we can responsibly design and innovate for their needs, we launched a stream of research into how to design AI for future generations.

Our interdisciplinary team—which includes members of this cohort—began with a quantitative approach, following conversations on AI on TikTok, meticulously analyzing hashtags, video topics, and comments.

What emerged was a strong consensus—AI is a helpful tool for boosting productivity and efficiency, particularly for school (help with homework), career development (writing a resume or cover letter), and daily routines (workouts or meal plans).

But we also discovered a profound ambivalence and much debate regarding the role AI should play in three specific domains: creative expression, human relationships, and mental wellbeing. What was striking is that these pillars are fundamental to identity formation and self-perception—integral parts of the coming-of-age experience that have already been significantly shaped by social media and the pandemic.

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To dig deeper into this dichotomy, we created six sacrificial concepts—hypothetical AI products and services of the future.

1. AI Venture Accelerator: A creative co-founder that helps you bring your idea to life
2. AI Passion Coach: A guide that identifies your skills and makes suggestions for how and where to apply them
3. AI Muse: An generator of inspirational ideas that accelerate your creative pursuits
4. Our AI Friend: A bot that helps your friend group interact and connect
5. New AI, New Me: An avatar trained on your preferences that has experiences for you
6. Build a FrAInd: Your ideal bestie come to life, based on celebs and influencers you love

We presented the concepts to 12 young people, aged 13 to 21, encompassing varied life experiences and levels of familiarity with AI. Together, we delved into what really matters to them, unearthing their desires and concerns about the technology that will influence their future.

The insights we gleaned made us check our assumptions. The participants expressed a yearning for opportunities to learn through relationships, to try new things, and to embrace failure as part of their growth. They voiced concern about how AI companions might influence their expectations of genuine and complicated humans.

“You might start comparing your simulated friend with your real friends,” said one 20-year-old student. “And then start noticing all the flaws in your real friends, which might start damaging your relationships.”

Another participant pondered the consequences of a tool that eradicated mistakes or smoothed over challenges, as it would create an all-too-perfect reality. They viewed these experiences as essential components of life itself, stressing, “Let us figure out our challenges, let us work through things and have those emotions. Give us tools that could aid us along the way, or work on it, but let us have that experience because I think we need it.”

“Let us figure out our challenges, let us work through things and have those emotions.”

The lessons imparted by this cohort defy the prevailing technology-centric mindset and challenge the stereotypes slapped onto Gen Z.

As builders of AI products, we believe we must always return to people. We're not suggesting we press pause on exploring novel ways to integrate emerging technologies into our systems. But let's check our assumptions, consider the unintended consequences, and design AI for future generations with care and intention. Failing to do so risks making costly bets on products, services, and experiences that will fail outright. Or worse, creating new problems.

Look out for the second part of this series, where we’ll share innovation principles for AI that will help organizations leverage the power of design to learn, understand, and build not just for young people, but with them.

Screenagers. Digital natives. The TikTok generation. It's hard to find an epithet for those born between the mid 1990s and early 2010s—aka Gen Z—that doesn’t call out a dependency on technology.

（Read the English version here）

私がプログラミングに興味を持ったのは、大学院でグラフィックデザインを学んだときでした。ある授業で「ジェネラティブデザイン」という、コードを使って視覚的なアウトプットを生み出すデザインの考え方を学んだのです。この考え方は、私が以前フォトジャーナリストとして働いていたときにカメラで行っていたこととすぐに共鳴しました。デジタルカメラでは、レンズを通して世界を観察し、シャッタースピード、絞り、フォーカス、構図を操作して、最終的な結果を作り出していました。そして、出来上がった写真を確認し、必要に応じて設定を変更し、また納得のいく写真が撮れるまで何度も撮り直します。プログラミングでも同じように、プログラムを走らせ、生み出されたビジュアル観察し、自分が望む結果になるまでコードを操作する、というプロセスを経験しました。

大学院での自由な時間を利用して、私はプログラミングについて独学で学び、Processingのような視覚表現に適したプログラミング環境を使って、グラフィックデザインを作る実験を始めました。修士課程では、プログラミング、ジャーナリズム、グラフィックデザインの3つの分野の交点に重点を置きました。

卒業後、プログラミングの実験を続ける機会はほとんどありませんでした。IDEOで働くようになってからは、グラフィックデザインを試す時間が増えましたが、プログラミングとデザインに対する情熱を再発見したのは、育児休暇に入ったとき。育児休暇中、自分に使える時間はオムツ替えや授乳、お風呂といった子どもの世話の合間のわずかな時間。この貴重な時間をどのように過ごしたいか、子育ての経験が改めて考えるきっかけをくれました。コンピュータの前に座り、なまった頭でPythonで数行プログラムを書くことを通じて、コードを使ってグラフィックデザインをすることの素晴らしさを改めて実感したのです。

プログラミングは創造ツールの一つ

グラフィックデザイナーは、新しい技術を自分の仕事に取り入れる機会に飛びつくことが多いですが、私にとってプログラミングは、デザイナーが長年にわたって使ってきた他のたくさんのツールと何ら変わらないものでした。コンピュータが普及し始めた頃、デザイナーはスクリーン印刷機を補完するためにPhotoshopやIllustratorなどのツールを学びましたし、コピー機やリゾグラフは昔から実験的な視覚的な表現に使われてきました。

私自身、ビジュアルを作るための新しいテクニックを試すことを常に求めています。ポスターやブランディングのためのイメージを作るのに、3Dモデリングやレンダリングなどのツールを使うことが多いのですが、初めてプログラミングを学んだとき、従来のグラフィックデザインの成果物で使われるようなイメージを作る上での新たなツールになる可能性をすぐに感じたのです。

IDEOのパートナーであるマイケル・ヘンドリックスの音楽をテーマにしたイベントのために作ったポスターとブランディングも、従来のグラフィックデザインをサポートするようなプログラミングの活用のひとつです。ポスターのデザインでは、楽器のシンセサイザーに使われている波形のアイデアと、マイケルの著書Two Beats Ahead のテーマである「ありえない組み合わせでデザインのインスピレーションを得る」ということを参考にしました。「シンセサイザー風の波形と紙」という、ありそうでなかった組み合わせで、イベントのビジュアルを作ることにしたのです。

ポスターの背景は、Line-Usというロボットアームをプログラミングして、鉛筆で音楽の正弦波を紙に描き続けることで作成しました。その絵を撮影し、色を変えてから最終的なポスターのデザインに落とし込みました。

プログラミングで波形を描くことで、手描きでは難しい、繰り返される波の数学的な正確さと美しさを視覚化することができました。一方で鉛筆で描くことで、波そのものがラフな質感を持ち、音楽制作の有機的なプロセスも表現することができました。

クリエイティブパートナーとしてのプログラミング

プログラミングは、単なる創造のためのツールという枠を超え、驚きや喜びを通じて私たちにインスピレーションを与えてくれるような素晴らしいクリエイティブパートナーにもなり得ます。ChatGPTやDALL-EのようなAIベースのツールの台頭により、このようなクリエイティブな活動の中でこうした機械を試す人が増えています。実際私もIDEOのデザイナーが、行き詰っている問題についてAIチャットボットに質問しているのを見たことがあります。デザイナーはチャットボットに、"どうすればデジタルシステムをより人間らしい形に拡張できるだろうか？"などと質問できるのです。通常、AIの回答はそれだけでは素晴らしい解決策にはなりませんが、「文脈を考慮しましょう」といった回答は、デザイナーを新しいアイデアやプロトタイプに向けて刺激するのに十分な後押しになるかもしれません。

プログラミングも同じように、特に予期せぬ結果で私を鼓舞してくれることに気付きました。初期のプログラミングでは、あらかじめ定義された文法構造にランダムな単語を挿入することで、ソーシャルメディアへの投稿を自動生成するシンプルなアルゴリズムを書きました。このプログラムは、"24 Especially Terrible Wedding Animals Every Film Lover Needs（"全てのシネフィルが必要な特段ひどい結婚式動物24選”）のようなランダムに生成されるフレーズで笑いと驚きをもたらしてくれました。

生成されたフレーズが思いがけず不条理なユーモアに満ちていたことから、このプロジェクトを「ソーシャルメディアの投稿」から、「風刺的なフェイクニュースの見出しの作成」へとシフトさせることにしました。ネットで得られる情報の質が時に怪しくなることへの批判として、投稿生成プログラムを活用し、フェイクニュースの見出しを無限に自動で書き出すようにしたのです。

このプロジェクトの最新版である「AI News Network」は、1時間ごとに実際のニュースの見出しを自動的にダウンロードし、見出しの単語を形容詞や名詞などの品詞に分類し、ランダムに新しいフェイクニュースの見出しとして組み立てます。ヴィンテージのブラウン管画面には、私が作成した偽のブランド名が表示され、無限に続くヘッドラインが表示されます。私が書いたプログラムは、プロジェクトの内容を自動的に生成するクリエイティブパートナーとしての役割を果たしてくれます。見出しの作成は、プログラムに任せているので、うっかり信じてしまいそうになるような、でもやっぱり荒唐無稽なコンテンツに、私自身驚くことがあります。「インドネシア、ボブ・ディランを非難」のような偽の見出しを見ると、ボブ・ディランがインドネシアを怒らせるようなことをしたのだろうかと思うし、「サル男、ジョー・バイデンからの支持を撤回」のような無意味な見出しにはただ苦笑してしまいます。

2つの世界の間で踊るプログラミング

実用性は低いですが、私がプログラミングに最も惹かれるのは、プログラミングが持つ感覚ゆえかもしれません。グラフィックデザインのようなクリエイティブな活動では、明確な正解はありません。どのグラフィックも、他よりも正しいと証明できるわけではありません。それでもある特定のグラフィック表現が正しいように感じることがあります。私たちはデザイナーとして、直感的に良い結果を得たと判断することができるのです。論理的に正解を示すことはできなくても、直感的に「これはいい！」と感じることがあります。スタンリー・キューブリック監督は、「物事の真実は、考えることではなく、感じることにある」と述べています。

しかし、プログラミングの場合、コードそのものについて自分がどう感じるかは関係ありません。プログラムには、ある結果を出すためのさまざまなアプローチがありますが、コードを一つでも間違えれば、エラーになり何もできなくなります。プログラミングの世界は残酷なまでに論理的で、精密さがなければ機能しません。しかし、その論理と直感のコントラストにこそ、私はスリルを感じるのです。ビジュアルを表現するためにコードを書くとき、私の脳は論理と感覚の2つの世界の間で踊ることができるのです。

最近のプロジェクトでは、IDEO Tokyoのスタジオに、小型カメラでレトロなピクセル画像を撮影し、古いブラウン管スクリーンに表示する「フォトブース」のようなものをつくりました。このプロジェクトのプログラミングでは、論理と直感の世界を行き来することができました。画像データを格納する数学的な配列を作成してからプログラムを実行すると、カラフルなブロックから私の顔の写真がゆっくりと出来上がっていくのを見ることができました。コーディングはロジックですが、ビジュアルを見る瞬間は、純粋に直感的な疑問でいっぱいです。ピクセルが大きければレトロ感があるけれど、被写体は識別できるのか？画像の不思議さを楽しんでもらいつつも、飽きさせないような描画速度になっているか？色彩はクールか？何か違和感があれば、再びプログラムの世界に飛び込み、コードの行をいじり、バグを修正し、データ構造を入れ替える。そして、再びプログラムを走らせ、どう変わったかを確認するのです。「うん、これはいい感じ。でも、この1行を変えたらどうなるんだろう......」。このように、私の脳の論理的側面と直感的側面を常に行き来することは、刺激的で中毒性があります。片方が休んでいる間、もう片方は遊んでいるのです。

あなたの意外な組み合わせ

プログラミングをツールとして、またパートナーとして使うことで、グラフィックデザインの新しいアプローチを発見し、驚きと興奮を得ることができます。皆さんも、プログラミングが好きというわけではないかもしれませんが、一見異なるコンセプトがどのように組み合わされ、新しい驚きをもたらしてくれるのか、ぜひ探索してみてください。新しいアプローチに出会ったとき、そのアプローチが自分の情熱を思い起こさせるかどうか、そしてその新しいアプローチと今の仕事を組み合わせる機会はあるか、探してみましょう。その中に意外な発見があるかもしれません。

IDEOの多くのコミュニケーション・デザイナーと同様に、私もグラフィックデザインのバックグラウンドを持っています。「グラフィックデザイン」と聞くと、いわゆるビジュアルを作る仕事が思い浮かぶかもしれません。新しいブランドの価値を視覚的に伝えるために、ロゴをスケッチしたり、カラーパレットを選んだりするデザイナーを想像する人もいるでしょう。あるいは書籍やプレゼン資料のレイアウトを作成し、書体をじっくり選び、画像やテキストを配置して、ダイナミックなページを作る仕事も思い浮かべる人もいるかもしれません。

実際私もこうしたいわゆるグラフィックデザインを日々の仕事として行ってますが、最近はそれ以外の活動にも時間を割くことが増えています。それは「プログラミング」です。

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.