Are Current Tort Liability Doctrines Adequate for Addressing Injury Caused by AI
Bibliographic Data
| ID | 15745992 |
|---|---|
| Authors | Hannah Sullivan (0009-0001-9698-8177, American Medical Association, corresponding author), Scott J Schweikart (American Medical Association) |
| Year | 2019 |
| Volume | 21 |
| Issue | 2 |
| Pages | E160-166 |
| Publication date | 2019-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The AMA Journal of Ethic (JOURNAL) |
| Journal identifiers | ISSN: 2376-6980 • E-ISSN: 2376-6980 |
| Publisher | American Medical Association (PUBLISHER • US) |
| DOI | 10.1001/amajethics.2019.160 |
| PMID | 30794126 |
| OpenAlex | W2921072211 |
| Language | EN |
| Citations received | 14 |
| References cited | 1 |
As capabilities of predictive algorithms improve, machine learning will become an important element of physician practice and patient care. Implementation of artificial intelligence (AI) raises complex legal questions regarding health care professionals' and technology manufacturers' liability, particularly if they cannot explain recommendations generated by AI technology. The limited literature on liability for innovation provides opportunities to consider possible implications of AI for medical malpractice and products liability and new legal solutions for addressing liability issues surrounding "black-box" medicine
Actuarial science · Business · Engineering ethics · Health care · Liability · Malpractice · Medical malpractice · Political science · Tort · Artificial Intelligence in Healthcare and Education · Autopsy Techniques and Outcomes · Engineering · Law · Medical Imaging and Analysis · Finance
Medical AI and Human Dignity
International migration management in the age of artificial intelligence
Responsibility beyond design
Legal dispositionism and artificially-intelligent attributions
Efficacy and pitfalls of digital technologies in healthcare services
Epistemic (in)justice, social identity and the Black Box problem in patient care
Technological Answerability and the Severance Problem
Physician assessment, comparative abilities and artificial intelligence
Artificial Intelligence‐Generated Synthetic Data in Healthcare
Investigating the barriers towards adoption and implementation of open innovation in healthcare
Transparency and accountability in AI systems
(De)troubling transparency
Are Current Tort Liability Doctrines Adequate for Addressing Injury Caused by AI
The ethics of AI in health care
| Unique citing works | 14 |
|---|---|
| Citations per year | 2 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 13 |