<story><title>Artificial Intelligence Is Stupid and Causal Reasoning Will Not Fix It</title><url>https://www.frontiersin.org/articles/10.3389/fpsyg.2020.513474/full</url></story><parent_chain></parent_chain><comment><author>kmeisthax</author><text>&amp;gt;In other words, unless we are content to “bite the bullet” of panpsychism, then no machine, however complex, can ever realize phenomenal consciousness purely in virtue of the execution of a particular computer program.&lt;p&gt;Ok, but why are biological neurons exempted from this argument? I mean, aside from the obvious conflict of interest that the person who wrote this article is made out of them, and they would much rather not be ontologically dissolved into a soulless zombie.&lt;p&gt;I&amp;#x27;m not sure you actually have to bite the panpsychism bullet either (or I&amp;#x27;m misunderstanding what that word means). Adding a Putnam mapping to an FSA or giving you a book that maps Chinese characters to other Chinese characters doesn&amp;#x27;t necessarily make the FSA conscious or you a literate Chinese reader. It just makes the sum total of those things conscious. Likewise, each individual neuron in your head does not need to be totally conscious. Consciousness is an emergent property of your whole body, not just something attributable to parts of it.</text></comment>
<story><title>Artificial Intelligence Is Stupid and Causal Reasoning Will Not Fix It</title><url>https://www.frontiersin.org/articles/10.3389/fpsyg.2020.513474/full</url></story><parent_chain></parent_chain><comment><author>abetusk</author><text>I&amp;#x27;ve only skimmed but it seems like the general idea is sound, that neural networks are good at pattern matching and that shallow pattern matching is only one aspect of &amp;quot;deep thought&amp;quot;, logical reasoning being the other one.&lt;p&gt;I&amp;#x27;m confused though, they give examples of Go and Chess but, as far as I understand, this is exactly what the author is saying doesn&amp;#x27;t exist. AlphaGo, Deep Blue, etc, all use neural networks to weight how to traverse the minimax tree [0]. The minimax algorithm&amp;#x2F;tree is precisely the &amp;quot;logical reasoning&amp;quot;. The neural network is &amp;quot;just&amp;quot; prioritizing the path to take.&lt;p&gt;Anyway, like I said, the reasoning is sound. I just read a paper specifically about this breakdown, called &amp;quot;On the Paradox of Learning to Reason from Data&amp;quot; by Zhang, et all [1] where they construct a synthetic data set based on some simple logical rules and then try to train a neural network to recapture the underlying logic (spoiler alter, it fails). From their paper:&lt;p&gt;&amp;quot;&amp;quot;&amp;quot;
Our study provides an explanation for this paradox: instead of learning to emulate the correct reasoning function, BERT has, in fact, learned statistical features that inherently exist in logical reasoning problems. We also show that it is infeasible to jointly remove statistical features from data, illustrating the difficulty of learning to reason in general.
&amp;quot;&amp;quot;&amp;quot;&lt;p&gt;[0] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;en.wikipedia.org&amp;#x2F;wiki&amp;#x2F;Minimax&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;en.wikipedia.org&amp;#x2F;wiki&amp;#x2F;Minimax&lt;/a&gt;&lt;p&gt;[1] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;abs&amp;#x2F;2205.11502&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;abs&amp;#x2F;2205.11502&lt;/a&gt;</text></comment>