Large Language Models (LLMs) such as ChatGPT and Copilot are a central topic in the ongoing discourse surrounding the philosophical dilemma of artificial intelligence. In Daniel Dennett’s article, Kinds of Minds, he delves into whether or not he deems artificial intelligences to have a mind, ultimately asserting that they do not. That being said, when he refers to AI, he refers specifically to computer functions such as screen readers and speech to text, which isn’t quite the same as how LLMs work.<\/p>\n\n\n\n
Does the difference matter? Well, we can talk about it. <\/p>\n\n\n\n
Screen readers and text to speech programs operate through their Traditional Programming. What that means is that in the development of their program, their developers write explicit rules (coding) for them to follow. In doing so, they differ from LLMs, which are created through another form of programming called Machine Learning (ML). The way ML works is by inputting large amounts of data into a computer and having it learn\/process that data by adjusting its internal settings. The provided data functions as its own neural network, which is a specific ML model that is loosely modeled after the human brain. <\/p>\n\n\n\n
Let’s tie this back to Dennett.<\/p>\n\n\n\n
While I am still skeptical about whether or not LLMs have minds, ML does counter Dennett’s argument on why they don’t. Dennett’s claim was that screen readers don’t actually know the data they’re relaying to their audience, that they simply translate the visual words into their corresponding audio. The implications of ML and Neural Networks on LLMs are that they have learned the data itself, in addition to generating new text in response to a prompt. This difference does offer some compelling evidence in support of AI having a mind of its own. While I can’t say for sure whether or not this is true, I can say that no matter where we stand on the AI debate, we need to take all these variables into account if we ever hope to reach a consensus. <\/p>\n","protected":false},"excerpt":{"rendered":"
A response to Daniel Dennett’s article. <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1","post","type-post","status-publish","format-standard","hentry","category-uncategorized","entry"],"_links":{"self":[{"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=\/wp\/v2\/posts\/1","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1"}],"version-history":[{"count":2,"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=\/wp\/v2\/posts\/1\/revisions"}],"predecessor-version":[{"id":11,"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=\/wp\/v2\/posts\/1\/revisions\/11"}],"wp:attachment":[{"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/philai.ryansandson.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}