• Lucas Miller: Becoming Superhuman in the Age of AI

  • Jul 8 2024
  • Length: 1 hr and 24 mins
  • Podcast

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Lucas Miller: Becoming Superhuman in the Age of AI

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  • My guest today is Lucas Miller; it’s his second time on the show; please look up his earlier episode. I highly recommend it. We met over a year ago in Zurich, where I shared with a small group of investors what I learned about my life, investing process, and work in general during the unusual pandemic years. We bonded right away since Lucas told me that my lessons rhyme with what he is studying and researching as a cognitive neuroscientist and human performance researcher at UC Berkeley’s Haas School of Business, where he is the youngest faculty member. At Berkeley, Lucas teaches MBA students and is best known for his course called "Becoming Superhuman: The Science of Productivity and Performance". Since COVID began, Lucas has given over 600 talks and keynotes to financial institutions, private equity firms, and investment funds on how to optimize their workflow and enhance creative thinking. He’s been featured in Forbes, Wired, and the Wall Street Journal Few might now, that when Lucas was 21, he published his first book on the science of successful learning and getting work done. He wrote most of the book during a summer off in Nepal, and, of all places, the book became most popular not in America, but in Hong Kong! I’m including a link to a free digital copy in the notes to episode: bit.ly/beyondbrilliance Today, we discuss the aim of artificial intelligence (AI) to recreate human intelligence, its evolution with large language models like ChatGPT, and its ability to generate answers and summaries from vast amounts of data, despite occasional inconsistencies and hallucinations. Lucas shares that outsourcing lower-level thinking to AI tools allows humans to focus on higher-level tasks and ask better quality questions, emphasizing the need to verify AI-generated information and ensure accuracy and reliability. My guest tells me to avoid overconfidence in AI and to maintain human judgment in decision-making. We explore how AI can automate low-impact tasks, augment human work, and transform industries, noting that the speed of AI adoption and improvement is faster than previous technological revolutions. We highlight that AI can enhance human capabilities and elevate work, but certain tasks will always require human involvement. We talk about the impact of AI on different fields and tasks, which will require individuals to adapt and find new ways to add value. Lucas shares insights on how the brain evolved to help humans survive and reproduce, not to optimize and make rational decisions, leading to errors in thinking and judgment due to its limited capacity and finite processing power. My guest tells me that AI cannot replace human qualities such as trust, empathy, creativity, and moral judgment. Stay tuned until the end, when you will hear how success for AI in the next 50 years would look like. Podcast Program – Disclosure Statement Blue Infinitas Capital, LLC is a registered investment adviser and the opinions expressed by the Firm’s employees and podcast guests on this show are their own and do not reflect the opinions of Blue Infinitas Capital, LLC. All statements and opinions expressed are based upon information considered reliable although it should not be relied upon as such. Any statements or opinions are subject to change without notice. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and unless otherwise stated, are not guaranteed. Information expressed does not take into account your specific situation or objectives, and is not intended as recommendations appropriate for any individual. Listeners are encouraged to seek advice from a qualified tax, legal, or investment adviser to determine whether any information presented may be suitable for their specific situation. Past performance is not indicative of future performance.
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