AI and the Law

Book description

Where is artificial intelligence taking us? Concerns over "responsible" innovation have spawned debates since big data appeared, but apprehension has grown considerably with widespread adoption of AI. This report examines the legal liability related to AI systems, including where responsibility should lie for adverse effects, loss of privacy, and other challenges.

Author Karen Kilroy discusses why society needs to create laws and ethical governance frameworks for AI. Product directors, CIOs, CEOs, and risk officers will explore how AI is interpreted in law and policymaking, including issues such as privacy, negligence, liability, ethics, and entity management. This report also contains ideas for ensuring AI doesn't escape human control--and that people who control it act in a responsible manner.

You'll learn:

  • What AI is: learn its broad range of capabilities and applications, and AI's ability to influence users
  • The trust deficit: understand the uneasiness people have about the prospect of being replaced or devalued by AI's rapid and often stealth introduction to society
  • AI and the legal industry: explore how AI is used in law and explore the liability of autonomous AI
  • Innovating responsibly: examine ways that companies can learn from past mistakes and create frameworks for responsible innovation in the future

Table of contents

  1. 1. Trust Deficit
    1. Background
    2. What Is AI?
      1. AI Systems Are Intelligent Agents
      2. AI and Human Interaction
      3. AI Is Designed to Thrive
    3. How Do Machines Learn?
    4. My Own Machine Learning Case Study
      1. Training Riley
      2. AI Says the Darnedest Things
    5. AI Vulnerabilities
      1. Dependency 1: Data
      2. Dependency 2: Algorithms
      3. Protecting Data and Algorithms
    6. Case Study: Palantir
      1. Palantir Sells Secret Predictive Policing
      2. Palantir Employee Shares Secret Algorithms
      3. Palantir Owners Keep Voting Control
    7. Is the Trust Deficit Justified?
      1. Fear of AI
      2. Misplaced Trust
      3. Building Trust
      4. AI That Codes
      5. Singularity and Program Synthesis
      6. Replaced by Robots
      7. Persuasive AI
      8. Digital Twins, Deepfakes, and GANs
      9. The Art of Seeing
      10. Facial Recognition
    8. Case Study: Clearview AI
      1. Unwanted Press
      2. Mutnick v. Clearview AI
      3. Not Just for Law Enforcement—by a Long Shot
      4. Illinois Biometric Privacy Act
      5. State of Vermont v. Clearview AI
      6. Clearview’s Response: “No Reasonable Expectation of Privacy”
      7. Clearview AI Cameras and Wearables
      8. Canada v. Clearview AI
      9. Letter of Inquiry from U.S. Senator Ed Markey
      10. Choice Between Security and Privacy
    9. Summary
  2. 2. AI and the Legal Industry
    1. How AI Is Used in Law
      1. AI in Courts
      2. AI in Law Firms
      3. AI in Policy Making
    2. Liability of Autonomous AI
      1. Automation in Vehicles
      2. Case Study: Sz Hua Huang v. Tesla Inc.
    3. Summary
  3. 3. Innovate Responsibly
    1. Learn from Past Disasters
      1. Examine Safety Lessons
      2. Understand the Nature of Risk
    2. Prevent AI Disaster
      1. Use AI Only as Needed
      2. Regulate AI Bias
      3. Types of AI Bias
      4. End Win-at-All-Cost Business Models
      5. Build Better Social Media
      6. Amygdala Versus Prefrontal Training Data
      7. Design Better User Interfaces
      8. Usability for Vulnerable Populations First
      9. Monitor and Tether AI
      10. Create a Truth Machine
    3. Establish Controls to Prevent Exposure and Harm
      1. Standards Bodies
      2. AI Watchdogs and Ethical Frameworks
      3. Algorithmic Impact Assessment
      4. Organizational Ethics
    4. Summary

Product information

  • Title: AI and the Law
  • Author(s): Karen Kilroy
  • Release date: February 2021
  • Publisher(s): O'Reilly Media, Inc.
  • ISBN: 9781492091820