AI vs Humans Rewriting the Rules of Success
summary
History-first survey traces myths to modern systems and argues current success metrics fail, proposing multi‑axis evaluation instead of a single intelligence score. Cites milestones Deep Blue (1997), AlphaGo (2016) and the Transformer (2017) → ChatGPT public interface as the democratizing inflection. Flags concrete harms today: bias, privacy, job displacement, weak multimodal reasoning. Recommends interdisciplinary engineering plus policy and gives a practical healthcare program using education, executive advisory and process/tooling to deploy ethical AI.
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chapters (13)
- 0:00🚀 Build Stuff Conference – Get Your Tickets!
- 0:23Introduction: The Ethics of AI
- 5:10Historical Foundations of AI
- 10:45AI and Frankenstein: Lessons from Creation
- 14:00The Role of Innovation vs. Regulation in AI
- 20:00Lessons from AI’s Evolution: From Automata to Modern Tech
- 24:10How AI Challenges Our Definitions of Intelligence
- 28:35Measuring AI Success: Is It Human Replication?
- 32:50The Turing Test and Its Modern Relevance
- 36:20Ethical and Existential Fears Around AI
- 40:30AI and Human Fairness: A Social Issue
- 43:00Interdisciplinary Approach to AI: Why It’s Crucial
- 45:10Current Risks of AI and the Future of Humanity
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