How Humans Judge Machines, Hardcover
INR 5145
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M.R.P. INR 5145
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Using hard science, How Humans Judge Machines reveals the biases that permeate human-machine interactions.
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What Stands Out
Product Details
| Manual & guide type | Instruction Manual |
| Book format | Hardcover |
| Edition | 1 |
| Pages | 256 |
| Language | English |
| Brand | Cesar A Hidalgo |
| Pub date | 2021-02-02 |
| Author | MIT Press |
| Subgenre | Ethics |
| Genre | Textbooks |
| Bisac subject heading | Science |
| Series title | No Series |
| Height | 9.1 in (23.1 cm) |
| Age group | Adult |
| Retail packaging | Single Piece |
| Original languages | English |
| Item Weight | 1.1 lbs (500 grams) |
Who Should Buy?
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AI Researchers
Ideal for those studying human interaction with machines and AI development, offering insight into user perspectives and feedback.
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Technology Enthusiasts
Perfect for individuals interested in the evolving relationship between humans and technology, exploring how we interpret machine behavior.
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Ethics Scholars
Useful for researchers focusing on the ethical implications of AI judgment by humans, enhancing discussions on machine accountability.
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Casual Readers
Not suitable for those seeking light reading; the content requires engagement with complex ideas and theories.
Product Description
How Humans Judge Machines, Hardcover
Customer Questions & Answers
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Question:
What topics does the book cover?
Answer: The book covers topics such as human judgment of machines in disasters, policing, algorithmic bias, and much more. -
Question:
What kind of research is included?
Answer: The book includes original research and data from randomized experiments to explore biases in human-machine interactions. -
Question:
Who are the authors of the book?
Answer: The book is authored by César Hidalgo and colleagues from MIT Press.
Cesar A Hidalgo All Manuals & Guides Editorial Review
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INR 5145
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Features & Benefits
- Explores how humans judge machines differently in critical scenarios.
- Analyzes reactions to machines in contexts like job displacement and surveillance.
- Utilizes data from experiments to identify biases in human-machine interactions.
- Investigates the influence of moral dimensions on judgments of machines.
- Discusses demographic factors like education and gender in the judgment of AI.
- Offers insights into the ethical consequences of artificial intelligence.
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