The risks of risk-based AI regulation: taking liability seriously
- URL: http://arxiv.org/abs/2311.14684v1
- Date: Fri, 3 Nov 2023 12:51:37 GMT
- Title: The risks of risk-based AI regulation: taking liability seriously
- Authors: Martin Kretschmer, Tobias Kretschmer, Alexander Peukert, Christian
Peukert
- Abstract summary: The development and regulation of AI seems to have reached a critical stage.
Some experts are calling for a moratorium on the training of AI systems more powerful than GPT-4.
This paper analyses the most advanced legal proposal, the European Union's AI Act.
- Score: 46.90451304069951
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The development and regulation of multi-purpose, large "foundation models" of
AI seems to have reached a critical stage, with major investments and new
applications announced every other day. Some experts are calling for a
moratorium on the training of AI systems more powerful than GPT-4. Legislators
globally compete to set the blueprint for a new regulatory regime. This paper
analyses the most advanced legal proposal, the European Union's AI Act
currently in the stage of final "trilogue" negotiations between the EU
institutions. This legislation will likely have extra-territorial implications,
sometimes called "the Brussels effect". It also constitutes a radical departure
from conventional information and communications technology policy by
regulating AI ex-ante through a risk-based approach that seeks to prevent
certain harmful outcomes based on product safety principles. We offer a review
and critique, specifically discussing the AI Act's problematic obligations
regarding data quality and human oversight. Our proposal is to take liability
seriously as the key regulatory mechanism. This signals to industry that if a
breach of law occurs, firms are required to know in particular what their
inputs were and how to retrain the system to remedy the breach. Moreover, we
suggest differentiating between endogenous and exogenous sources of potential
harm, which can be mitigated by carefully allocating liability between
developers and deployers of AI technology.
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