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From Users to Shapers of AI: The Future of Research

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From Users to Shapers of AI: The Future of Research

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Monday, March 25, 2024 • Advancing Research 2024
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From Users to Shapers of AI: The Future of Research
Speakers: Tricia Wang
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Summary

Discover the transformative power of shifting from passive users to active shapers of AI in Tricia's compelling closing keynote. Unveiling the insidious "User Trap," Tricia exposes the pervasive sense of powerlessness entrenched in our tech-driven world. She champions a radical shift in the researcher's mindset, advocating liberation from the confines of being "user researchers" to versatile professionals adept at navigating the complexities of human-tech interactions, especially ones that force people into becoming users. As AI tooling improves, Tricia envisions a future where human ingenuity stands as the cornerstone, complementing and enhancing the capabilities of advanced AI tools. In this world, researchers who can truly understand human beings, gather thick data, and communicate complexity and context-loss with clarity, will become even more indispensable.

Key Insights

  • The term 'user' reduces complex human relationships to passive roles that serve platform interests.

  • AI’s cultural fear stems not only from the technology itself but from legacy issues of control in Web 2.0.

  • The 'user trap' describes our dependence on digital platforms that erode agency but are essential to modern life.

  • Shapers actively collaborate with AI, going beyond passive use to shape technology’s role in their lives.

  • Four key care skills of shapers are coaching, adaptive intelligence, responsibility, and viewing AI as an extension of self.

  • Big Tech’s control over AI risks repeating the mistakes of social media, potentially amplifying existing problems.

  • Thick data, or qualitative context-rich data, is essential to combat the complexity and context loss in AI-driven outputs.

  • Insight-driven organizational cultures outperform data-driven ones by integrating qualitative and quantitative knowledge.

  • Researchers need to move beyond 'user research' to fully embrace the complexity of people’s interaction with technology.

  • Experimenting personally and professionally with AI helps demystify the technology and encourages proactive engagement.

Notable Quotes

"AI is super polarizing — on one end, it’s discovering millions of new materials, on the other, it’s corrupting children’s experiences."

"We are stuck in the user trap because these platforms are central to being human today."

"In Web 2.0, a small group sets the rules and most people just play within them."

"Fear of AI comes from not trusting the inputs, the data powering these models."

"The user identity is a digital construct that commodifies humans for their data."

"Shapers combine human and machine intelligence and amplify each other’s strengths."

"Researchers might be the last people in organizations accountable for understanding humans."

"Our job is to fight context loss as data moves up layers of abstraction in AI outputs."

"Thick data is the opposite of big data and essential for rescuing lost context."

"Language matters — calling people 'users' reflects and reinforces the reality of reduced agency."

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