#297 - Brian Christian - The Alignment Problem: AI's Scary Challenge
Brian Christian is a programmer, researcher and an author.
You have a computer system, you want it to do X, you give it a set of examples and you say "do that" - what could go wrong? Well, lots apparently, and the implications are pretty scary.
Expect to learn why it's so hard to code an artificial intelligence to do what we actually want it to, how a robot cheated at the game of football, why human biases can be absorbed by AI systems, the most effective way to teach machines to learn, the danger if we don't get the alignment problem fixed and much more...
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Making Machines More Human: Best-Selling Author Brian Christian on the Alignment Problem - Ep. 135
Not many can claim to be a computer programmer, nonfiction author and poet, but Brian Christian has established himself as all three.
Christian has just released his newest book, The Alignment Problem, which delves into the disparity that occurs when AI models don’t do exactly what they’re intended to do.
The book follows on the success of Christian’s previous work, "The Most Human Human and Algorithms to Live By." Now a visiting scholar at UC Berkeley, Christian joined AI Podcast host Noah Kravitz to talk about the alignment problem and some new techniques being used to address the issue.
The alignment problem can be caused by a range of reasons — such as data bias, or datasets used incorrectly and out of context. As AI takes on a variety of tasks, from medical diagnostics to parole sentencing decisions, machine learning researchers are expressing concern over the problem.
Listen to the full podcast to hear about this and more — including Christian’s book club experience with Elon Musk and why he chose to double major in philosophy and computer science.
Brian Christian – How to Live with Computers - [Invest Like the Best, EP.140]
My guest this week is Brian Christian, the author of two of my favorite recent books: Algorithms to Live By and The Most Human Human. Our conversation covers the present and future of how humans interact with and use computers. Brian’s thoughts on the nature of intelligence and what it means to be human continue to make me think about what works, and life, will be like in the future. I hope you enjoy our conversation.
For more episodes go to InvestorFieldGuide.com/podcast.
Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub.
Follow Patrick on Twitter at @patrick_oshag
Show Notes
1:11 - (First Question) – Summarizing his collection of interests that led to his three books
2:59 – Biggest questions in AI
3:43 – Defining AGI (Artificial General Intelligence) and its history
5:18 – Computing Machinery and Intelligence
7:54 – The idea of the most human human
9:59 – Tactics that have changed the most in learning to be the most human human
16:10 –Tests for measuring AGI and updates made to them
20:12 – Concerns for once we have AGI
26:06 – Self-awareness as a threshold for AGI
31:58 – Skeptics’ take on AGI
37:14 – Advice for people building careers and how AGI will impact work
38:16 – Explore/Exploit trade-off
44:57 – How to explore/exploit applies to business concepts
49:16 – Impacts of AGI on the economy
52:40 – Highlights from his second book
57:39 – Kindest thing anyone has done for Brian
Learn More
For more episodes go to InvestorFieldGuide.com/podcast.
Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub
Follow Patrick on twitter at @patrick_oshag