Social Neuroscientist - How we make Decisions, Free Will and How "Intelligent" is AI Really?

About the conversation

Donate to my Paypal. Thank you so much! https://www.paypal.com/donate/?hosted_button_id=L38HCUYY5TDTG Dr Redmond O’ Connell is a cognitive neuroscientist from Trinity College Dublin, my alma mater. He has spent decades studying our decision making systems in the brain, how we build evidence in a manner shaped by our experience and perceptions and ultimately how we make heavily biased decisions. He's won many awards and is a brilliant researcher and scientific communicator. 00:00 Intro 03:23 The Brain's Decision-Making Process 04:56 The Evidence Accumulation Process 11:58 Overcoming Biases through Education and Critical Thinking 15:15 Effective Communication to Address Biases 39:52 Introduction and Free Will 55:50 Limitations of Large Language Models 01:02:42 Mimicking the Human Brain in AI 01:10:31 Understanding Consciousness in AI 01:16:29 Exciting Advances and Concerns in the Next Decade of Science To Support the Channel - Get 56% off your first subscription to MAGIC MIND. The health shot to help you enter flow - https://www.magicmind.com/evanmc - Follow the Podcast on Spotify - https://open.spotify.com/show/5m3Gta5MtIYdk59pb2GJ7M?si=b33232eae67b4126 Subscribe on youtube and follow on Spotify so you don’t miss the next neuroscience podcast, I hope you enjoy! My Startup weeve - https://www.weeve.ie/ My Socials X - https://twitter.com/evan_mcgl LinkedIn - https://www.linkedin.com/in/evan-mcgloughlin/ Instagram - https://www.instagram.com/evan_mcgloughlin/ The brain's decision-making process is still not fully understood, but there are some guiding principles that have been established. One principle is the evidence accumulation process, where the brain samples and weighs different pieces of information before making a decision. Expectations and biases also play a role in decision making, as they shape the thresholds for accepting evidence. Biases can be difficult to overcome, but education and critical thinking can help. Effective communication is crucial in addressing biases and promoting a better understanding of complex issues. The concept of free will is subjective and depends on individual definitions and perspectives. In this conversation, Redmond O'Connell discusses the concept of free will and its relationship to neural activity and decision-making. He challenges the idea that neural activity preceding conscious decisions negates free will, arguing that it is a matter of quantity rather than a binary concept. O'Connell also explores the limitations of large language models like ChatGPT, highlighting their inability to reason and their reliance on statistical associations. He suggests that mimicking the human brain and incorporating embodied cognition may be key to developing more intelligent AI. O'Connell emphasizes the importance of understanding consciousness and the potential ethical concerns surrounding AI and misinformation. Key Podcast Takeaways: The brain engages in an evidence accumulation process when making decisions. Expectations and biases shape the thresholds for accepting evidence. Education and critical thinking can help overcome biases in decision making. Effective communication is crucial in addressing biases and promoting understanding. The concept of free will is subjective and depends on individual perspectives. The concept of free will is not a binary concept but a matter of quantity, with neural activity preceding conscious decisions reflecting an emerging decision-making process. Large language models like ChatGPT have limitations in reasoning and lack the ability to act on the world, making them fundamentally different from human intelligence. Mimicking the human brain and incorporating embodied cognition may be crucial in developing more intelligent AI. Understanding consciousness and its neural signatures is important in testing the potential consciousness of AI. The next decade in science holds the potential for exciting advances in disease cures, but also raises concerns about the impact of AI on society, including CO2 emissions and the spread of misinformation.