2026-09-19T01:28:48Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1456022022-10-04T03:01:36Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Malone, Thomas W.
Tenenbaum, Joshua B.
Campero Nuñez, Andres
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
2022-09-27T20:16:33Z
2022-09-27T20:16:33Z
2022-05
2022-09-27T16:55:15.150Z
https://hdl.handle.net/1721.1/145602
Artificial Intelligence algorithms never operate in isolation but are always part of broader processes that often involve humans, other computer algorithms, incentive structures, and interfaces which modulate the interaction between them. This thesis takes this perspective and considers these broader processes by studying specific combinations of three forms of intelligence: symbolic artificial intelligence, neural artificial intelligence, and human intelligence. First, diverse forms of Neuro-Symbolic AI through three pipelines consisting respectively of neural perception with symbolic reasoning, symbolic inputs with neural reasoning, and a dual-integration that learns representations which are simultaneously symbolic and neural (Chapter 2); second, the AI research community as a Human-Symbolic combination through the presentation of a taxonomy of AI models, tasks and datasets (Chapter 3); and third, a specific form of Human-AI intelligence observing that a human in combination with GPT-3 can perform an HTML code generation task better than either humans or computers alone (Chapter 4).
Ph.D.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
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http://rightsstatements.org/page/InC-EDU/1.0/
Combining Diverse Forms of Human and Machine
Intelligence
Thesis
application/pdf
Doctoral
Doctor of Philosophy
Publication
unknown
unknown
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<Abstract>Artificial Intelligence algorithms never operate in isolation but are always part of broader processes that often involve humans, other computer algorithms, incentive structures, and interfaces which modulate the interaction between them. This thesis takes this perspective and considers these broader processes by studying specific combinations of three forms of intelligence: symbolic artificial intelligence, neural artificial intelligence, and human intelligence. First, diverse forms of Neuro-Symbolic AI through three pipelines consisting respectively of neural perception with symbolic reasoning, symbolic inputs with neural reasoning, and a dual-integration that learns representations which are simultaneously symbolic and neural (Chapter 2); second, the AI research community as a Human-Symbolic combination through the presentation of a taxonomy of AI models, tasks and datasets (Chapter 3); and third, a specific form of Human-AI intelligence observing that a human in combination with GPT-3 can perform an HTML code generation task better than either humans or computers alone (Chapter 4).</Abstract>
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