ReviewFrontiers in pharmacology2023
Liability for harm caused by AI in healthcare: an overview of the core legal concepts.
Review in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI in Medical Questionnaires: Scoping ReviewJournal of medical Internet research · 2025Pooled it
- Liability and Standard of Care in AI-Driven Psychiatric Practice: European Viewpoint.Journal of medical Internet research · 2026Article
- Is Digital Healthcare Better Than None? The Digital Health Technology Dilemma in Low-Income Countries.Asian bioethics review · 2026Article
- Legal and ethical responsibility for AI-assisted diagnostic and referral errors: a scoping review of comparative approaches with implications for Saudi healthcare.BMC medical ethics · 2026Article
- Forecasting the Impacts of Artificial Intelligence Assistance in Virtual Consultations for Chronic Obstructive Pulmonary Disease: Exploratory Futures Wheel Study.Journal of medical Internet research · 2026Article
- Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Review
- Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
- AI-powered tools in family medicine: Bridging technology and practice.Journal of family medicine and primary care · 2026Article
- From pilot to policy: why AI health interventions fail to scale in developing countries.Frontiers in digital health · 2026Article
- CostWorld journal of gastrointestinal oncology · 2025Article
- Artificial Intelligence in Drug-Coated Cardiovascular Devices: A Narrative Review.Reviews in cardiovascular medicine · 2025Review
- Artificial Intelligence in Anesthesia: Enhancing Precision, Safety, and Global Access Through Data-Driven Systems.Journal of clinical medicine · 2025Review
- The Next Frontiers in Preventive and Personalized Healthcare: Artificial Intelligent-powered Solutions.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2025Review
- Turkish adaptation of the artificial intelligence ethics scale (EAI): a validity and reliability study for nursing students.BMC psychology · 2025Article
- Evaluating large language models for renal colic imaging recommendations: a comparative analysis of Gemini, copilot, and ChatGPT-4.0.International journal of emergency medicine · 2025Article
- Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare.Nanomaterials (Basel, Switzerland) · 2025Review
- Artificial Intelligence in Dentistry: A Narrative Review of Diagnostic and Therapeutic Applications.Medical science monitor : international medical journal of experimental and clinical research · 2025Review
- Bridging the gap: The role of technological advances in shaping gastrointestinal oncological outcomes.World journal of gastrointestinal oncology · 2025Article
- Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review.Frontiers in public health · 2025Article
- The I-KAPCAM-AI-Q: a novel instrument for evaluating health care providers' AI awareness in Italy.Frontiers in public health · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
Abstract
The integration of artificial intelligence (AI) into healthcare in Africa presents transformative opportunities but also raises profound legal challenges, especially concerning liability. As AI becomes more autonomous, determining who or what is responsible when things go wrong becomes ambiguous. This article aims to review the legal concepts relevant to the issue of liability for harm caused by AI in healthcare. While some suggest attributing legal personhood to AI as a potential solution, the feasibility of this remains controversial. The principal-agent relationship, where the physician is held responsible for AI decisions, risks reducing the adoption of AI tools due to potential liabilities. Similarly, using product law to establish liability is problematic because of the dynamic learning nature of AI, which deviates from static products. This fluidity complicates traditional definitions of product defects and, by extension, where responsibility lies. Exploring alternatives, risk-based determinations of liability, which focus on potential hazards rather than on specific fault assignments, emerges as a potential pathway. However, these, too, present challenges in assigning accountability. Strict liability has been proposed as another avenue. It can simplify the compensation process for victims by focusing on the harm rather than on the fault. Yet, concerns arise over the economic impact on stakeholders, the potential for unjust reputational damage, and the feasibility of a global application. Instead of approaches based on liability, reconciliation holds much promise to facilitate regulatory sandboxes. In conclusion, while the integration of AI systems into healthcare holds vast potential, it necessitates a re-evaluation of our legal frameworks. The central challenge is how to adapt traditional concepts of liability to the novel and unpredictable nature of AI-or to move away from liability towards reconciliation. Future discussions and research must navigate these complex waters and seek solutions that ensure both progress and protection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.