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| − | | + | #REDIRECT [[AI and Humans]] |
| − | =AI in Education=
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| − | ==AI improves learning/education==
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| − | * Mollick, Ethan R. and Mollick, Lilach and Bach, Natalie and Ciccarelli, LJ and Przystanski, Ben and Ravipinto, Daniel, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4871171 AI Agents and Education: Simulated Practice at Scale] (June 17, 2024). The Wharton School Research Paper. [http://dx.doi.org/10.2139/ssrn.4871171 doi: 10.2139/ssrn.4871171]
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| − | ** Can enable personalized education.
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| − | ==AI harms learning==
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| − | * [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305354 A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study] ** Current grading systems cannot detect AI.
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| − | * Bastani, Hamsa and Bastani, Osbert and Sungu, Alp and Ge, Haosen and Kabakcı, Özge and Mariman, Rei, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895486 Generative AI Can Harm Learning] (July 15, 2024). The Wharton School Research Paper.[http://dx.doi.org/10.2139/ssrn.4895486 doi: 10.2139/ssrn.4895486]
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| − | ** Access to ChatGPT harmed math education outcomes.
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| − | ==Software/systems==
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| − | * [https://devpost.com/software/gptutor GPTutor] ([https://github.com/mynamegabe/GPTutor code])
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| − | =AI/human=
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| − | ==AI out-performs humans==
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| − | ===Tests===
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| − | * 2024-06: [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305354 A real-world test of artificial intelligence infiltration of a university examinations system: A “Turing Test” case study]
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| − | ** AI scores higher than median students.
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| − | ===Creativity===
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| − | * 2023-09: [https://www.nature.com/articles/s41598-023-40858-3 Best humans still outperform artificial intelligence in a creative divergent thinking task]
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| − | ** Best humans out-perform AI at creativity. (By implication, median humans may not.)
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| − | * 2024-02: [https://www.nature.com/articles/s41598-024-53303-w The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks]
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| − | * 2024-02: Felin, Teppo and Holweg, Matthias, [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4737265 Theory Is All You Need: AI, Human Cognition, and Causal Reasoning] (February 24, 2024). [http://dx.doi.org/10.2139/ssrn.4737265 doi: 10.2139/ssrn.4737265]
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| − | ** Argues that human "theory-based" creativity is better than AI "data-based".
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| − | * 2024-07: [https://arxiv.org/abs/2407.01119 Pron vs Prompt: Can Large Language Models already Challenge a World-Class Fiction Author at Creative Text Writing?]
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| − | ** Top human (professional author) out-performs GPT4.
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| − | * 2024-09: [https://arxiv.org/abs/2409.04109 Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers]
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| − | ** LLMs can be creative
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| − | ===Professions===
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| − | * 2024-03: [https://www.medrxiv.org/content/10.1101/2024.03.12.24303785v1 Influence of a Large Language Model on Diagnostic Reasoning: A Randomized Clinical Vignette Study]
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| − | ** GPT4 improves medical practitioner work; surprisingly, GPT4 alone scored better than a human with GPT4 as aid (on selected tasks).
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| − | ==AI improves human work==
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| − | * TBD
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| − | | |
| − | =Uptake=
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| − | TBD
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