How an MIT Research Scientist Makes AI Useful

I sit down with Bryan Reimer, Ph.D., a Research Scientist at MIT who leads research on human-centered technology at the intersection of AI, human behavior, mobility, and public policy.

Bryan has spent over two decades studying how people actually behave inside complex systems, especially in cars, organizations, and high-stakes environments where “automation” can help… or quietly make things worse.

Topics we cover:

• Why companies rush into “AI strategy” without defining the use case or ROI
• Tech-first vs consumer-first thinking and how to design for real humans
• Why observation beats assumptions when building for behavior change
• “Copilot, not autopilot”: how Bryan uses AI without giving up authorship
• Using ChatGPT as a communications teammate for editing, tone, and clarity
• The hidden problem of “work slop” and how AI can help interpret messy writing
• Why incentivizing AI adoption inside companies actually matters
• Skill atrophy: what we lose when we automate too much, and what we should build instead

Tools, Platforms, and References Mentioned:

• ChatGPT
• OpenAI’s AI Leadership Guide
• GM Super Cruise, Tesla Autopilot
• How to Make AI Useful (book, co-authored with futurist Magnus Lindkvist)

Who this episode is for:

• Founders and operators building AI into products or teams
• Leaders trying to create an AI strategy that actually makes sense
• Anyone navigating trust, safety, and ethics in automation
• Builders who care about human behavior, not just features

Learn more about Bryan Reimer:

• Book: How to Make AI Useful (available on Amazon)
• Bryan Reimer on LinkedIn: linkedin.com/in/bryan-reimer

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