Bryan Casey

Stanford Medicine

Papers

5

Total Citations

53

H-Index

4

About

Bryan Casey is a leading scholar at the intersection of law, robotics, and artificial intelligence, whose work grapples with the fundamental question of how legal systems should respond when intelligent machines cause harm. His research, which has garnered over 50 citations, focuses on developing a coherent framework for liability and remedies in an age of increasingly autonomous systems. Casey’s most influential paper, “Amoral Machines, Or: How Roboticists Can Learn to Stop Worrying and Love the Law” (2017, 20 citations), challenges engineers to embrace legal thinking as a design constraint rather than an obstacle. In “Remedies for Robots” (2018, 14 citations), he systematically explores what legal recourse exists when AI misbehaves, moving beyond hypotheticals to propose concrete doctrinal solutions. His 2019 piece “Robot Ipsa Loquitur” (8 citations) cleverly adapts the venerable tort doctrine of *res ipsa loquitur* to the robotics context, arguing that the very nature of autonomous systems may shift evidentiary burdens. Casey’s work is notable for its accessibility and wit—titles like “You Might Be a Robot” (2019, 4 citations) invite readers into complex legal debates with humor. For students and researchers, Casey offers a vital roadmap for reconciling centuries of legal precedent with the unprecedented challenges of embodied AI.

Research Focus

Key Achievements

4
H-Index
5
Papers
53
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Amoral Machines, Or: How Roboticists Can Learn to Stop Worrying and Love the Law
20 citations · 2017
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Stanford Medicine

Top Papers

  1. 1
  2. 2
    Remedies for Robots
    14 citations · 2018
  3. 3
    Robot Ipsa Loquitur
    8 citations · 2019
  4. 4
    Remedies for Robots
    7 citations · 2019
  5. 5
    You Might Be a Robot
    4 citations · 2019

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago