Summary
Designers stand at the verge of a great professional opportunity: artificial intelligence. This technology enables computers to study the world and make predictions using unstructured data. We can speak to machines—and machines can speak back. We can gesture to devices, expressing emotion and intent, and machines can respond meaningfully. We can look to computers not just for interaction, but for companionship. How can designers adapt and thrive in this evolving terrain? How might we map out new brands, platforms and experiences between human and machine? What dangers must we address? What destructive ideologies must we reveal? What possibilities for a better future might we explore and prototype?
Key Insights
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Designers and data scientists have complementary approaches that must collaborate for effective AI experiences.
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Anticipatory design can preempt user needs, creating highly personalized experiences across industries like fast food, retail, and healthcare.
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Users tend to overtrust autonomous AI systems, but their trust can quickly erode when predictions are inaccurate, requiring balanced design strategies.
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Designers should build interfaces that allow users to verify AI outputs and provide feedback in the moment of use.
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Human-AI teaming enables users to manage complex systems and discover insights unattainable alone, as seen in intelligence analysis prototypes.
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Designers must thoughtfully decide which human skills to preserve versus which to automate, informed by metaphors like Elizabeth Churchill's pedal-assist system.
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AI operates as an alien intelligence without understanding consequences, so humans must provide ethical context and oversight.
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Younger designers exhibit enthusiasm but lack critical skepticism; educational programs must nurture a balanced perspective on AI.
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Learning data science vocabulary empowers designers to collaborate effectively with technical teams and shape AI-driven products.
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The emergent field of contestable AI UX patterns highlights the need for interfaces that support in-the-moment user challenges to AI outputs.
Notable Quotes
"Designers need data, but data also needs designers."
"If we don’t collaborate, we’ll end up with a lot of meals that nobody wants to eat and that are really bad for us."
"Anticipatory design means the system serves up what the user needs or desires before they even request it."
"Humans tend to overtrust autonomous systems, like following GPS directions into a lake."
"When the AI prediction is wrong, trust erodes very quickly; balancing skepticism and trust is critical."
"Human and AI teaming can produce insights and wisdom that would be difficult to discover alone."
"The question is not just what to automate, but what human skills do we want to preserve."
"AI is a kind of pedal assist system: sometimes you want it to push you, sometimes you want to pedal yourself."
"AI has no understanding of consequences; humans bring ethical meaning and responsibility."
"Designers must resist manipulation and marginalization inherent in automated systems to envision futures we want to live in."
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