<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Brian Christian and Tom Griffiths on SummaryShelf</title><link>https://summaryshelf.app/authors/brian-christian-and-tom-griffiths/</link><description>Recent content in Brian Christian and Tom Griffiths on SummaryShelf</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 22 May 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://summaryshelf.app/authors/brian-christian-and-tom-griffiths/index.xml" rel="self" type="application/rss+xml"/><item><title>Algorithms to Live By: The Computer Science of Human Decisions</title><link>https://summaryshelf.app/algorithms-to-live-by/</link><pubDate>Mon, 11 Sep 2023 00:00:00 +0000</pubDate><guid>https://summaryshelf.app/algorithms-to-live-by/</guid><description>&lt;p&gt;Most of life&amp;rsquo;s hardest decisions aren&amp;rsquo;t hard because you&amp;rsquo;re bad at thinking. They&amp;rsquo;re hard because you&amp;rsquo;re solving problems that have no perfect answer: too many options, too little information, too little time. Computer scientists have spent decades on exactly these problems, and the strategies they worked out for machines turn out to be good advice for people. An algorithm is just a finite sequence of steps for solving a problem. Following a recipe is one, and so is making a pros-and-cons list, only less precise. The trick is knowing which algorithm fits which decision.&lt;/p&gt;</description></item></channel></rss>