*Licensing high-risk artificial intelligence: Toward ex ante
justification for a disruptive technology
*
Gianclaudio Malgieri, Frank Pasquale
https://doi.org/10.1016/j.clsr.2023.105899
/Under a Creative Commons license/
The regulation of artificial intelligence (AI) has heavily relied on ex
post, reactive tools. This approach has proven inadequate, as numerous
foreseeable problems arising out of commercial development and
applications of AI have harmed vulnerable persons and communities, with
few (and sometimes no) opportunities for recourse. Worse problems are
highly likely in the future. By requiring quality control measures
before AI is deployed, an ex ante approach would often mitigate and
sometimes entirely prevent injuries that AI causes or contributes to.
Licensing is an important tool of ex ante regulation, and should be
applied in many high-risk domains of AI. Indeed, policymakers and even
some leading AI developers and vendors are calling for licensure in the
area.
To substantiate licensing proposals, this article specifies optimal
terms of licensure for AI necessary to justify its use. Given both
documented and potential harms arising out of high-risk AI systems,
licensing agencies should require firms to demonstrate that their AI
meets clear requirements for security, non-discrimination, accuracy,
appropriateness, and correctability before being deployed. Under this ex
ante model of regulation, AI developers would bear the burden of proof
to demonstrate that their technology is not discriminatory, not
manipulative, not unfair, not inaccurate, and not illegitimate in its
lawful bases and purposes. While the European Union's General Data
Protection Regulation (GDPR) can provide key benchmarks here for ex post
regulation, the proposed AI Act (AIA) offers a first regulatory attempt
towards an ex ante licensure regime in high-risk areas, but it should be
strengthened through an expansion of its scope and substantive content
and through greater transparency of the ex ante justification process.
https://www.sciencedirect.com/science/article/pii/S0267364923001097
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