[SEQ RERUN] Abstraction, Not Analogy

[MinibearRex]

Today’s post, Abstraction, Not Analogy was originally published on November 19, 2008. A summary:

Describing certain arguments as analogies misses much of the point of those arguments. In order to generate predictions, we often ignore certain information in favor of more relevant information. These sorts of abstractions succeed or fail based on whether or not they successfully capture the important details.

Discuss the post here (rather than in the comments to the original post).

This post is part of the Rerunning the Sequences series, where we’ll be going through old posts in order so that people who are interested can (re-)read and discuss them. This post is the first official post in the rerun of the AI-FOOM Debate. The previous post was A Few Background Posts by Robin Hanson, and you can use the sequence_reruns tag or rss feed to follow the rest of the series.

Sequence reruns are a community-driven effort. You can participate by re-reading the sequence post, discussing it here, posting the next day’s sequence reruns post, or summarizing forthcoming articles on the wiki. Go here for more details, or to have meta discussions about the Rerunning the Sequences series.

[buybuydandavis]

My quoted summary:

I’m not that happy with framing our analysis choices here as “surface analogies” versus “inside views.” …

The issue is what abstractions are [ed. remove - “how”] useful for what purposes, not what features are “deep” vs. “surface.” …

I claim academic studies of innovation and economic growth offer relevant abstractions for understanding the future creation of machine minds, and that in terms of these abstractions the previous major singularities, such as humans, farming, and industry, are relevantly similar. Eliezer prefers “optimization” abstractions.