Practical Fairness - Achieving Fair and Secure Data Models

"Fairness is becoming a paramount consideration for data scientists. Mounting evidence indicates that the widespread deployment of machine learning and AI in business and government is reproducing the same biases we're trying to fight in the real world. But what does fairness mean when it comes to code? This practical book covers basic concerns related to data security and privacy to help data and AI professionals use code that's fair and free of bias." -- Back cover.

About the author

Aileen Nielsen is a software engineer who has analyzed data in a variety of settings from a physics laboratory to a political campaign to a healthcare startup. She also has a law degree and splits her time between a deep learning startup and research as a Fellow in Law and Technology at ETH Zurich. She has given talks around the world on fairness issues in data and modeling.

Product details

• Authors: Aileen Nielsen
• Publisher: O'Reilly
• Languages: English
• Product format: Paperback / Softback
• Released: 31.12.2020
• EAN: 9781492075738
• ISBN: 978-1-4920-7573-8
• Dimensions: 178 mm x 233 mm x 19 mm
• Weight: 606 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Artificial Intelligence, BUSINESS & ECONOMICS / Business Ethics, COMPUTERS / System Administration / Storage & Retrieval, COMPUTERS / Machine Theory, Artificial Intelligence (AI), COMPUTERS / Human-Computer Interaction (HCI), COMPUTERS / Artificial Intelligence / General, COMPUTERS / Data Science / Machine Learning, COMPUTERS / Data Science / Neural Networks