Nos derniers articles

The latest #ai-#cybersecurity-#knowledgemanagement practices advance the future of #riskmanagement practices. The article highlights the importance of risk management and #cyberresilience in a dynamic world characterized by #uncertainty and complexity.

This paper advocates for the use of #sandbox#regulation to complement a strict #liabilityregime in regulating #artificialintelligence (#ai). The #eu#regulators have already embraced this concept.

The paper discusses the risks posed by #artificialintelligence (#ai) systems, from biased lending algorithms to chatbots that spew violent #hatespeech. The author argues that policymakers have a responsibility to consider broader, longer-term #risks from #aitechnology, such as #systemicrisk and the potential for misuse. While #regulatory proposals like the #eu #aiact and the #whitehouse AI Bill of Rights focus on immediate risks, they do not fully address the need for #algorithmicpreparedness. It proposes a roadmap for algorithmic preparedness, which includes five forward-looking principles to guide the development of regulations that confront the prospect of algorithmic black swans and mitigate the harms they pose to society. This approach is particularly important for general purpose systems like #chatgpt, which can be used for a wide range of applications, including ones that may have unintended consequences. The article emphasizes the need for #governance and #regulation to ensure that #aisystems are developed and used in ways that minimize risk and maximize benefit, and it references the #nist AI #riskmanagement Framework as a potential tool for achieving this goal.

"By employing Big Data and Artificial Intelligence (AI), personal data that is categorized as sensitive data according to the GDPR Art. 9 can often be extracted. Art. 9(1) GDPR initially forbids this kind of processing. Almost no industrial control system functions without AI, even when considering the broad definition of the EU AI Regulation (EU AI Regulation-E)."

"This study proposes a comprehensive method (with representative AI-Technologies as a data basis) for the structured and targeted categorization and classification of AI under the risk-based audit approach. Initial feedback received by AI-Experts regarding the design and development of the artifact is collected. With the developed method, the study contributes to the descriptive and prescriptive knowledge base regarding the categorization and classification of AI within the auditing and accounting profession."

"... the AI Act risks delivering insufficient levels of both product safety or fundamental rights protection."

"... 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."

"As often in new regulatory domains, there is a tendency both of re-inventing the wheel – by disregarding insights from neighboring policy domains (e.g. nano-technology or aviation) – and of creating silos of research – by failing to link up and systematize existing accounts in a wider context of regulatory scholarship."

"The article addresses challenges for adequate risk regulation that arise primarily from the specific type of risks involved, i.e. risks to the protection of fundamental rights and fundamental societal values. They result mainly from the normative ambiguity of the fundamental rights and societal values in interpreting, specifying or operationalising them for risk assessments."

"This paper reviews the use of AI in the ESG field: textual analysis to measure firms’ ESG incidents or verify the credibility of companies’ concrete commitments, satellite and sensor data to analyse companies’ environmental impact or estimate physical risk exposures, machine learning to fill missing corporate data (GHG emissions etc.)."