Evidence map›Paper›PMID 42422721›Full record

ArticleFrontiers in artificial intelligence2026

AI product liability under EU and Canadian laws.

Jawahitha Sarabdeen

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jawahitha SarabdeenCollege of Law, Prince Sultan University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI and AI-enabled product-related liability have been a concern for the industries and consumers. They would like clarity on the liability for defective AI systems or products to mitigate risks. Laws in many countries provide tort or strict liability to address product liability. Some countries are amending or seeking to amend existing product liability legislation to address new issues related to AI. The EU has passed new directives and amended existing ones to address AI product liability, while Canada has drafted a new law to address this issue. The article aimed to assess the available literature and identify gaps in AI product liability. It also investigates the rules in the EU and Canada regarding AI product liability. By doing so, it intended to suggest improvements to the Canadian law on AI product liability. To achieve the objective, the researcher utilized a systematic literature review, legal doctrinal research, and comparative legal method. The finding showed that proving fault in an AI environment is challenging. Therefore, strict liability or a rebuttable presumption of causation could effectively protect end users. It will also ensure that various parties involved in AI take necessary safety measures to meet the legal presumption of their liability. It further revealed that the EU regulatory framework addresses AI product liability more effectively, although it has a few weaknesses that need to be addressed. The article suggested improvements to Canadian law regarding proof of fault, personal remedies, the role of the court, and the parties' liability.

Indexed as

AI productsCanadaEUlawsstrict liabilitytort liability

Identifiers

PMID42422721
PMCPMC13341826

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.