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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

  • Web 2.0 has created a 'user trap' where humans are passive, commodified data points rather than active participants.

  • AI amplifies fears rooted in Web 2.0's centralized control and lack of transparency over data inputs and outputs.

  • The dominant AI narrative frames humans as in competition with AI, fostering fear and loss of agency.

  • Shapers are people who actively collaborate with AI, blending human and machine intelligence to amplify outcomes.

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

  • Thick data, or deep qualitative insight, is critical to compensate for context loss inherent in digitization and big data.

  • A cultural shift is needed from data-driven to insight-driven organizations to better integrate diverse data and human perspectives.

  • Decentralized technologies like blockchain show potential, especially for underrepresented communities, but face commercial and idealistic challenges.

  • Researchers should rethink the term 'user' and their own roles, focusing on complex human relationships rather than simplified user categories.

  • Fully escaping the user trap requires understanding and proactive engagement with technology, not simply disconnecting from platforms.

Notable Quotes

"AI is the latest tool that’s gonna help us make better decisions for people, for the planet, for future generations."

"We’re all in the user trap — dependent on technology platforms that reduce our agency and treat us as passive data sources."

"Shapers show a two-way street with AI — coaching the AI and being coached by it."

"Thick data is the opposite of big data — it cuts through noise and rescues lost context."

"Web 2.0 platforms gave us the ability to be producers but the power always goes back to centralized monopolies."

"Our fear of AI comes from not trusting the data inputs powering AI models."

"Being a user has become an identity that limits human expression to a set of pre-approved interactions."

"The role of researchers is to zoom in and zoom out — navigating complexity while understanding the big picture."

"AI products don’t have to be platforms; smaller, open source models allow more control and customization."

"We are at an existential moment — will AI make tech bigger or more humane?"

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