Nos derniers articles

The article delves into #ethical concerns with #aitools in #legal and #tax research, addressing #output #quality, #bias, #verifiability, #liability, and #privacy #risks. It explores #regulatory, #tech, and professional solutions, offering practical advice for tax professionals to safely navigate AI's challenges with #riskmitigation.

The paper promotes better #riskmanagement and the fair allocation of #liability in #ai-related accidents.

This article highlights the importance of #cybersecurity in contemporary business models and the need for #legal practitioners and #it professionals to work together to assess the extent to which #privacy and #security measures qualify as "appropriate" in the context of #liability #claims and actions for #damages. The article provides guidance on how to move from technical insight to legal #compliance.

This paper discusses the relationship between standards and private law in the context of #liability #litigation and #tortlaw for damage caused by #ai systems. The paper highlights the importance of #standards in supporting policies and legislation of the #eu, particularly in the #regulation of #artificialintelligence. The paper assesses the role of AI standards in private law and argues that they contribute to defining the duty of care expected from developers and professional operators of AI systems.

This paper discusses the limitations of traditional #asset#liability#management (#alm) techniques in #riskmanagement, particularly in high-interest rate environments, and proposes the application of #deep#reinforcement#learning (#drl) to overcome these limitations. The paper defines the components of #reinforcementlearning (#rl) that can be optimized for ALM, including the RL Agent, Environment, Actions, States, and Reward Functions. The study shows that implementing DRL provides a superior approach compared to traditional ALM, as it allows for increased #automation, flexibility, and multi-objective #optimization in ALM.

This article discusses the need for #regulation of #robots and #ai in #europe, focusing on the issue of #civil #liability. Despite multiple attempts to harmonize #eu#tort #law, only the liability of producers for defective products has been successfully harmonized so far. The #aiact, published by the #europeancommission in 2021, aims to #regulate AI at the European level by classifying #smartrobots as "high risk systems", but does not address liability rules. This article explores liability issues related to AI and robots, particularly when using #deeplearning #machinelearning techniques that challenge the traditional liability paradigm.

In #corporategovernance, where boards are being held liable for #misconduct based on #operationalrisk. Operational misconduct is a critical source of #director#liability and should be given the same attention as #financial#mismanagement. Operational risk marks a fundamental shift in the way boards monitor the firm. Judicial doctrine is changing the way boards manage operational risk, avoid liability, and protect stakeholders' lives and the society at large.

"... if enacted as foreseen, AI liability in the EU will primarily rest on disclosure of evidence mechanisms and a set of narrowly defined presumptions concerning fault, defectiveness and causality."

"This paper analyzes how governments support insurance markets to maintain insurability and limit risks to society. We propose a new conceptual framework grouping government interventions into three dimensions: regulation of risky activity, public investment in risk reduction, and co-insurance."

"We propose a new conceptual framework grouping government interventions into three dimensions: regulation of risky activity, public investment in risk reduction, and co-insurance."