This book argues that our growing distrust of science is fuelled by tools scientists themselves created, as technological advances and developments in data analysis have led to disinformation, data torturing, and data mining. Smith examines these issues and offers solutions for restoring the credibility of the scientific community.
This book argues that our growing distrust of science is fuelled by tools scientists themselves created, as technological advances and developments in data analysis have led to disinformation, data torturing, and data mining. Smith examines these issues and offers solutions for restoring the credibility of the scientific community.
Gary Smith is the Fletcher Jones Professor of Economics at Pomona College. He received his Ph.D. in Economics from Yale University and was an Assistant Professor there for seven years. He has won two teaching awards and written (or co-authored) more than 100 academic papers and 15 books. He is the author of The AI Delusion (OUP 2018) and co-author with Jay Cordes of The 9 Pitfalls of Data Science (OUP 2019), which won the 2020 Prose Award for Excellence in Popular Science & Popular Mathematics by the Association of American Publishers.
Inhaltsangabe
Introduction: Disinformation, Data Torturing, and Data Mining Part I - Disinformation 1: The Paranormal Is Normal 2: Flying Saucers and Space Tourists 3: Elite Conspiracies 4: A Post-Fact World Part II - Data Torturing 5: Squeezing Blood from Rocks 6: Most Medicines Disappoint 7: Provocative, but Wrong Part III - Data Mining 8: Looking for Needles in Haystacks 9: Beat the Market 10: Too Much Data Part IV - The Real Promise and Peril of AI 11: Overpromising and Underdelivering 12: Artificial Unintelligence Part V - The Crisis 13: Irreproducible Research 14: The Replication Crisis 15: Restoring the Luster of Science
Introduction: Disinformation, Data Torturing, and Data Mining Part I - Disinformation 1: The Paranormal Is Normal 2: Flying Saucers and Space Tourists 3: Elite Conspiracies 4: A Post-Fact World Part II - Data Torturing 5: Squeezing Blood from Rocks 6: Most Medicines Disappoint 7: Provocative, but Wrong Part III - Data Mining 8: Looking for Needles in Haystacks 9: Beat the Market 10: Too Much Data Part IV - The Real Promise and Peril of AI 11: Overpromising and Underdelivering 12: Artificial Unintelligence Part V - The Crisis 13: Irreproducible Research 14: The Replication Crisis 15: Restoring the Luster of Science
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