
On the path to AI
Law's prophecies and the conceptual foundations of the machine learning age
- English
- ePUB (mobile friendly)
- Available on iOS & Android
On the path to AI
Law's prophecies and the conceptual foundations of the machine learning age
About this book
This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two 'revolutions' in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning ageâprediction based on datasets.
On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data.
Frequently asked questions
- Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
- Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Information
Table of contents
- Cover
- Front Matter
- 1. Two Revolutions
- 2. Getting Past Logic
- 3. Experience and Data as Input
- 4. Finding Patterns as the Path from Input to Output
- 5. Output as Prophecy
- 6. Explanations of Machine Learning
- 7. Juries and Other Reliable Predictors
- 8. Poisonous Datasets, Poisonous Trees
- 9. From Holmes to AlphaGo
- 10. Conclusion
- Back Matter