Fr. 47.90

Distrust - Big Data, Data-Torturing, and the Assault on Science

Inglese · Copertina rigida

Spedizione di solito entro 1 a 3 settimane (non disponibile a breve termine)

Descrizione

Ulteriori informazioni

Sommario










  • 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



Info autore

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.

Riassunto

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.

Testo aggiuntivo

Distrust: Big Data, Data-Torturing, and the Assault on Science is a highly recommended book for anyone interested about current, and future, issues related to what science is and how it is done.

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