LessWrong (Curated & Popular)

“‘Sharp Left Turn’ discourse: An opinionated review” by Steven Byrnes


Listen Later

Summary and Table of Contents

The goal of this post is to discuss the so-called “sharp left turn”, the lessons that we learn from analogizing evolution to AGI development, and the claim that “capabilities generalize farther than alignment” … and the competing claims that all three of those things are complete baloney. In particular,

  • Section 1 talks about “autonomous learning”, and the related human ability to discern whether ideas hang together and make sense, and how and if that applies to current and future AIs.
  • Section 2 presents the case that “capabilities generalize farther than alignment”, by analogy with the evolution of humans.
  • Section 3 argues that the analogy between AGI and the evolution of humans is not a great analogy. Instead, I offer a new and (I claim) better analogy between AGI training and, umm, a weird fictional story that has a lot to do with the [...]
---

Outline:

(00:06) Summary and Table of Contents

(03:15) 1. Background: Autonomous learning

(03:21) 1.1 Intro

(08:48) 1.2 More on discernment in human math

(11:11) 1.3 Three ingredients to progress: (1) generation, (2) selection, (3) open-ended accumulation

(14:04) 1.4 Judgment via experiment, versus judgment via discernment

(18:23) 1.5 Where do foundation models fit in?

(20:35) 2. The sense in which capabilities generalize further than alignment

(20:42) 2.1 Quotes

(24:20) 2.2 In terms of the (1-3) triad

(26:38) 3. Definitely-not-evolution-I-swear Provides Evidence for the Sharp Left Turn

(26:45) 3.1 Evolution per se isn't the tightest analogy we have to AGI

(28:20) 3.2 The story of Ev

(31:41) 3.3 Ways that Ev would have been surprised by exactly how modern humans turned out

(34:21) 3.4 The arc of progress is long, but it bends towards wireheading

(37:03) 3.5 How does Ev feel, overall?

(41:18) 3.6 Spelling out the analogy

(41:42) 3.7 Just how sharp is this left turn?

(45:13) 3.8 Objection: In this story, Ev is pretty stupid. Many of those surprises were in fact readily predictable! Future AGI programmers can do better.

(46:19) 3.9 Objection: We have tools at our disposal that Ev above was not using, like better sandbox testing, interpretability, corrigibility, and supervision

(48:17) 4. The sense in which alignment generalizes further than capabilities

(49:34) 5. Contrasting the two sides

(50:25) 5.1 Three ways to feel optimistic, and why I'm somewhat skeptical of each

(50:33) 5.1.1 The argument that humans will stay abreast of the (1-3) loop, possibly because they're part of it

(52:34) 5.1.2 The argument that, even if an AI is autonomously running a (1-3) loop, that will not undermine obedient (or helpful, or harmless, or whatever) motivation

(57:18) 5.1.3 The argument that we can and will do better than Ev

(59:27) 5.2 A fourth, cop-out option

The original text contained 3 footnotes which were omitted from this narration.

---

First published:
January 28th, 2025

Source:
https://www.lesswrong.com/posts/2yLyT6kB7BQvTfEuZ/sharp-left-turn-discourse-an-opinionated-review

---

Narrated by
...more
View all episodesView all episodes
Download on the App Store

LessWrong (Curated & Popular)By LessWrong

  • 4.8
  • 4.8
  • 4.8
  • 4.8
  • 4.8

4.8

12 ratings


More shows like LessWrong (Curated & Popular)

View all
Making Sense with Sam Harris by Sam Harris

Making Sense with Sam Harris

26,397 Listeners

Conversations with Tyler by Mercatus Center at George Mason University

Conversations with Tyler

2,424 Listeners

Robert Wright's Nonzero by Nonzero

Robert Wright's Nonzero

590 Listeners

Future of Life Institute Podcast by Future of Life Institute

Future of Life Institute Podcast

107 Listeners

The Good Fight by Yascha Mounk

The Good Fight

905 Listeners

ManifoldOne by Steve Hsu

ManifoldOne

92 Listeners

The Prof G Pod with Scott Galloway by Vox Media Podcast Network

The Prof G Pod with Scott Galloway

5,474 Listeners

Machine Learning Street Talk (MLST) by Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)

90 Listeners

Dwarkesh Podcast by Dwarkesh Patel

Dwarkesh Podcast

491 Listeners

Hard Fork by The New York Times

Hard Fork

5,465 Listeners

Clearer Thinking with Spencer Greenberg by Spencer Greenberg

Clearer Thinking with Spencer Greenberg

132 Listeners

Complex Systems with Patrick McKenzie (patio11) by Patrick McKenzie

Complex Systems with Patrick McKenzie (patio11)

133 Listeners

The Marginal Revolution Podcast by Mercatus Center at George Mason University

The Marginal Revolution Podcast

93 Listeners

Statecraft by Santi Ruiz

Statecraft

35 Listeners

The Last Invention by Longview

The Last Invention

297 Listeners