TY - JOUR
T1 - Artificial intelligence and illusions of understanding in scientific research
AU - Messeri, Lisa
AU - Crockett, M. J.
N1 - Publisher Copyright:
© Springer Nature Limited 2024.
PY - 2024/3/7
Y1 - 2024/3/7
N2 - Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of scientists’ visions for AI, observing that their appeal comes from promises to improve productivity and objectivity by overcoming human shortcomings. But proposed AI solutions can also exploit our cognitive limitations, making us vulnerable to illusions of understanding in which we believe we understand more about the world than we actually do. Such illusions obscure the scientific community’s ability to see the formation of scientific monocultures, in which some types of methods, questions and viewpoints come to dominate alternative approaches, making science less innovative and more vulnerable to errors. The proliferation of AI tools in science risks introducing a phase of scientific enquiry in which we produce more but understand less. By analysing the appeal of these tools, we provide a framework for advancing discussions of responsible knowledge production in the age of AI.
AB - Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of scientists’ visions for AI, observing that their appeal comes from promises to improve productivity and objectivity by overcoming human shortcomings. But proposed AI solutions can also exploit our cognitive limitations, making us vulnerable to illusions of understanding in which we believe we understand more about the world than we actually do. Such illusions obscure the scientific community’s ability to see the formation of scientific monocultures, in which some types of methods, questions and viewpoints come to dominate alternative approaches, making science less innovative and more vulnerable to errors. The proliferation of AI tools in science risks introducing a phase of scientific enquiry in which we produce more but understand less. By analysing the appeal of these tools, we provide a framework for advancing discussions of responsible knowledge production in the age of AI.
UR - http://www.scopus.com/inward/record.url?scp=85186618597&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85186618597&partnerID=8YFLogxK
U2 - 10.1038/s41586-024-07146-0
DO - 10.1038/s41586-024-07146-0
M3 - Article
C2 - 38448693
AN - SCOPUS:85186618597
SN - 0028-0836
VL - 627
SP - 49
EP - 58
JO - Nature
JF - Nature
IS - 8002
ER -