Trustworthy Artificial Intelligence and the European Union AI Act

" Adopting a risk-based approach towards AI, the EU chose to understand trustworthiness of AI in terms of the acceptability of its risks. This conflation of trustworthiness with acceptability of risk invites further reflection. Based on a narrative systematic literature review on institutional trust and the use of AI in the public sector, this paper argues that the EU adopted a simplistic conceptualisation of trust and is overselling its regulatory ambition."

Using Knowledge Distillation to improve interpretable models in a retail banking context

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" Predictive machine learning algorithms used in banking environments, especially in risk and control functions, are generally subject to regulatory and technical constraints limiting their complexity. Knowledge distillation gives the opportunity to improve the performances of simple models without burdening their application, using the results of other - generally more complex and better-performing - models."

Can We Nudge Insurance Demand by Bundling Natural Disaster Risks with Other Risks?

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"Our findings show that demand is overall higher to insure separate risks than to cover all risks together in a bundled insurance policy in the UK, whereas no significant difference is found between demand for bundled insurance and single policy insurance in the Netherlands. This difference in preference across the two countries is partly associated with whether individuals have been flooded in the past, which is more often the case in the UK than the Netherlands."

Tackling Problems, Harvesting Benefits - A Systematic Review of the Regulatory Debate around AI

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"... we contribute both empirically and conceptually to a better understanding of the nexus of AI and regulation and the underlying normative decisions. A comparison of the scientific proposals with the proposed European AI regulation illustrates the specific approach of the regulation, its strengths and weaknesses."