Ethical machines : your concise guide to totally unbiased, transparent, and respectful AI / Reid Blackman.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- text
- unmediated
- volume
- 9781647822811
- 174/.90063 23/eng20220322
- Q334.7
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|
Book | Högskolan Väst Entréplan (2nd floor) | 174 Blackman | Available | 6004300074149 |
Includes bibliographical references (pages 191-193) and index.
Introduction: AI for Good Not Bad -- Here's How You Should Think About Ethics -- Bias: In Search of Fair AI -- Explainability: The Space Between the Inputs and the Outputs -- Privacy: Ascending the Five Ethical Levels -- AI Ethics Statements that Actually Do Something -- Conclusions Executives Should Come To -- AI Ethics by Developers -- Conclusion: Two Surprises.
"The promise of artificial intelligence is automated decision-making at scale, but that means it also automates risk at scale. Are you prepared for that risk? Already, many companies have suffered real damage when their algorithms led to discriminatory, privacy-invading, and even deadly outcomes. Self-driving cars have hit pedestrians; HR algorithms have precluded women from job searches; mortgage systems have denied loans to qualified minorities. And often the companies who deployed the AI couldn't explain why the black box made the decision it did. In this environment, AI ethics isn't merely an academic curiosity, it's a business necessity. In Ethical Machines, Reid Blackman gives you all you need to understand AI ethics as a risk management challenge, then to build, procure, and deploy AI in an ethically (and thus reputationally, regulatory, and legally) safe way, and do it at scale. And don't worry, we're here to get work done, not to ponder deep and existential questions about ethics and technology. Blackman's clear and accessible writing helps make a complex and often misunderstood concept like ethics easy to grasp. You will understand ethical concepts while barely knowing you are taking them on. More importantly, Blackman makes ethics actionable. He tackles the big three ethical risks with AI-bias, explainability, and privacy-and tells you what to do (and what not to do) to mitigate ethical risks. With practical approaches to everything from how to write a strong statement of AI ethics principles to how to create teams that effectively evaluate ethical risks, Ethical Machines is the one guide you need to ensure you're using utterly unbiased, totally transparent, and remarkably respectful artificial intelligence"-- Provided by publisher.
Imported from: lx2.loc.gov:210/LCDB (Do not remove)