Machine Data, Personal Data, Sensitive Data and Artificial Intelligence. the Interplay of Privacy Enhancing Technologies with the GDPR
“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 […]
Artificial Intelligence Technologies within the Risk-based Audit Approach – A Categorization and Classification Method
“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 […]
Using an Interactive Artificial Intelligence System to Augment Auditor Judgment in a Complex Task
“… this study experimentally examines whether using an artificial intelligence system with interactive and structured information processing features augments auditor judgment when performing a fraud risk assessment.” Lire
The EU AI Act: Between Product Safety and Fundamental Rights
“… the AI Act risks delivering insufficient levels of both product safety or fundamental rights protection.” Lire
A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection
“We here propose a novel XAI [eXplainable AI] technique for deep learning methods (DL) which preserves and exploits the natural time ordering of the data. Simple applications to financial data illustrate the potential of the new approach in the context of risk-management and fraud-detection.” Lire
The Politics of Regulating Artificial Intelligence Technologies: A Competition State Perspective
“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.” Lire
Normative Challenges of Risk Regulation of Artificial Intelligence and Automated Decision-Making
“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.” Lire
Hidden Depths: the Effects of Extrinsic Data Collection on Consumer Insurance Contracts
“We argue that datafication of insurer processes may fuel excessive data collection in the context of insurance contracts, generating a substantial risk of harm to consumers, especially in terms of discrimination, exclusion, and unaffordability of insurance. “ Lire
European AI Regulation: Brussels Effect versus Human Dignity?
“After shortly summarising the origin, context and main characteristics of the prospective regulation, this article explores whether the ‘Brussels Effect’ will manifest in ground-breaking AI regulation, or whether the Union and its Member States run the risk of hastily adopting an incapable legal framework for a technology whose effects on society are still insufficiently understood.” Lire
Trustworthy Artificial Intelligence and the European Union AI Act: On the Conflation of Trustworthiness and the Acceptability of Risk
” 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 […]
AI Audit Washing and Accountability
“This paper first reports on proposed and enacted transatlantic AI or algorithmic audit provisions. It then draws on the technical, legal, and sociotechnical literature to address the who, what, why, and how of algorithmic audits, contributing to the literature advancing algorithmic governance.” Lire
Tackling Problems, Harvesting Benefits – A Systematic Review of the Regulatory Debate around AI
“… 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.” Lire
Comparative Analysis Regulatory of AI and Algorithm in UK, EU and USA
“The European Artificial Intelligence Board (EAIB) would be established as a new enforcement authority at the Union level. National supervisors will flank EAIB at the Member State level. Fines of up to ‘6% of global turnover, or 30 million euros for individual corporations’ can be imposed.” Lire
Artificial Intelligence Regulation in the United Kingdom: A Path to Global Leadership?
“… a growing domestic emphasis from the central government on promoting innovation through weakening checks will undermine the efficacy and ethical permissibility of initiatives. Likewise, the success of AI governance initiatives will be heavily influenced by decisions made in other jurisdictions, including the European Union. If left unaddressed, these factors risk transforming the UK into a reluctant […]
Regulating the Risks of AI
“This Article is the first to examine and compare a number of recently proposed and enacted AI risk regulation regimes. It asks whether risk regulation is, in fact, the right approach.” Lire
The AI ESG Protocol: Evaluating and Disclosing the ESG Implications of AI Capabilities, Assets, and Activities
“There is currently limited information on and a lack of a unified approach to AI and ESG, and a need for tools for systematically assessing and disclosing the ESG related impacts of AI and data capabilities. I here propose the AI ESG protocol, which is a flexible high-level tool for evaluating and disclosing such impacts…” […]
Prediction Machines, Insurance, and Protection: An Alternative Perspective on AI’s Role in Production
“We provide a formal model evaluating the impact of AI and how risk management, stakes, and inter-related tasks affect AI adoption. The broad conclusion is that AI adoption can be stymied by existing processes designed to address uncertainty.” Lire
From Transparency to Justification: Toward Ex Ante Accountability for AI
“The EU’s GDPR and proposed AI Act tend toward a sustainable environment of AI systems. However, they are still too lenient and the sanction in case of non-conformity with the Regulation is a monetary sanction, not a prohibition. This paper proposes a pre-approval model in which some AI developers, before launching their systems into the […]
Outlook on the Future Regulatory Requirements for AI in Europe
“… the report first assesses the concepts of fairness, bias and discrimination and illustrates the differences between these terms. In a next step, the existing legal framework is examined with regard to regulations that are already relevant for AI. Building on this analysis, special consideration is given to the Proposal of the European Commission on […]
Explainable Artificial Intelligence (Xai) in Insurance: A Systematic Review
“Explainable Artificial Intelligence (XAI) models allow for a more transparent and understandable relationship between humans and machines. The insurance industry represents a fundamental opportunity to demonstrate the potential of XAI, with the industry’s vast stores of sensitive data on policyholders and centrality in societal progress and innovation.” Lire