I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale.
Over the past decade, AI technologies have advanced by leaps and bounds. Progress has been so fast, voluminous, and varied that it can be a challenge even for experts to make sense of it all. In this essay, I propose a framework for thinking about AI systems, specifically the idea that they are ulti...
| Published in: | Daedalus: Journal of the American Academy of Arts & Sciences Vol. 151; no. 2; pp. 75 - 85 |
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| Format: | Article |
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MIT Press
Spring2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=156497244&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 156497244 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00115266 DED jtl: Daedalus: Journal of the American Academy of Arts & Sciences issn: 00115266 maglogo: N pubinfo: dt: Spring2022 vid: 151 iid: 2 pid: 776 pub: MIT Press artinfo: ui: 156497244 10.1162/daed_a_01901 ppf: 75 ppct: 10 formats: tig: atl: I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale. aug: au: Scott, Kevin su: Artificial intelligence Physical sciences Natural history Video coding sug: subj: Artificial intelligence Physical sciences Natural history Video coding ab: Over the past decade, AI technologies have advanced by leaps and bounds. Progress has been so fast, voluminous, and varied that it can be a challenge even for experts to make sense of it all. In this essay, I propose a framework for thinking about AI systems, specifically the idea that they are ultimately tools developed by humans to help other humans perform an increasing breadth of their cognitive work. Our AI systems for assisting us with our cognitive work have become more capable and general over the past few years. This is in part due to a confluence of novel AI algorithms and the availability of massive amounts of data and compute. From this, researchers and engineers have been able to construct large, general models that serve as flexible and powerful building blocks that can be composed with other software to drive breakthroughs in the natural and physical sciences, to solve hard optimization and strategy problems, to perform perception tasks, and even to assist with complex cognitive tasks like coding. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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