Étiquette : AI

Need for Artificial Intelligence (Ai) to Be Explainable in Banking and Finance: Review of Ai Applications, Ai Black Box, Xai Tools and Principles

The essential role of #ai in #banking holds promise for efficiency, but faces challenges like the opaque “black box” issue, hindering #fairness and #transparency in #decisionmaking #algorithms. Substituting AI with Explainable AI (#xai) can mitigate this problem, ensuring #accountability and #ethical standards. Research on XAI in finance is extensive but often limited to specific cases […]

AI Regulations in the Context of Natural Language Processing Research

Recent #ai developments, particularly in Natural Language Processing (#nlp) like #gpt3, are widely used. Ensuring safety and trust with increasing NLP use requires robust guidelines. Global AI #regulations are evolving through initiatives like the #euaiact, #unesco recommendations, #us AI Bill of Rights, and others. The EU AI Act’s comprehensive regulation sets a potential global benchmark. […]

Lessons from GDPR for AI Policymaking

The introduction of #ai #chatgpt has stirred discussions about AI regulation. The controversy over classifying systems like ChatGPT as “high-risk” AI under #euaiact has sparked concerns. This paper explores how Large Language Models (#llms) such as ChatGPT are shaping AI policy debates and delves into potential lessons from the #gdpr for effective regulation. Lire

Regulation of (Generative) AI Requires Continuous Oversight

The submission suggests strategies for regulating #ai in #australia, including examining the rate of take-up of #automated #decisionmaking systems, and regulating specific applications of underlying AI technologies. It also suggests altering the definition of AI, creating a set of guiding principles, and adopting a #risk-based approach to #regulation. Lire

Acceptable Risks in Europe’s Proposed AI Act: Reasonableness and Other Principles for Deciding How Much Risk Management Is Enough

This paper critically assesses the proposed #euaiact regarding #riskmanagement and acceptability of #highrisk #ai systems. The Act aims to promote trustworthy AI with proportionate #regulations but its criteria, “as far as possible” (AFAP) and “state of the art,” are deemed unworkable and lacking in proportionality and trustworthiness. The Parliament’s proposed amendments, introducing “reasonableness” and cost-benefit […]

Building a Culture of Safety for AI: Perspectives and Challenges

The paper explores the challenges of building a #safetyculture for #ai, including the lack of consensus on #risk prioritization, a lack of standardized #safety practices, and the difficulty of #culturalchange. The authors suggest a comprehensive strategy that includes identifying and addressing #risks, using #redteams, and prioritizing safety over profitability. Lire

A Rumsfeldian Framework for Understanding How to Employ Generative AI Models for Financial Analysis

This paper explores the use of #generativeai models in financial analysis within the Rumsfeldian framework of “known knowns, known unknowns, and unknown unknowns.” It discusses the advantages of using #ai #models, such as their ability to identify complex patterns and automate processes, but also addresses the #uncertainties associated with generative AI, including #accuracy concerns and #ethical considerations.    Lire

Measuring Ai Safety

This paper addresses the challenges associated with the adoption of #machinelearning (#ml) in #financialinstitutions. While ML models offer high predictive accuracy, their lack of explainability, robustness, and fairness raises concerns about their trustworthiness. Furthermore, proposed #regulations require high-risk #ai systems to meet specific #requirements. To address these gaps, the paper introduces the Key AI Risk Indicators (KAIRI) framework, tailored to the #financialservices industry. The framework […]

Ethical Challenges of Using Artificial Intelligence in Cybersecurity

“… the combinatorial approach of #ai and #cybersecurity is beneficial but still the associated danger persist owing to its manipulation by #cyberattackers. This chapter highlights the recent AI techniques deployed in cybersecurity and identifies the #ethical challenges thereof.” Lire

ChatGPT and Generative AI: The New Barbarians at the Gate

#ethical dilemmas and #regulatory considerations associated with #ai and #chatgpt adoption in financial analysis are … addressed, emphasizing the need for responsible AI usage and human oversight in critical #financial judgments. Lire

Regulating AI at work: labour relations, automation, and algorithmic management

These papers examine the role of #collectivebargaining and #governmentpolicy in shaping strategies to deploy new #digital and #ai-based technologies at work. The authors argue that efforts to better #regulate the use of AI and #algorithms at work are likely to be most effective when underpinned by social dialogue and collective #labourrights. The articles suggest specific lessons for #unions and policymakers seeking to develop broader strategies to engage with AI […]

Rationalizing AI Governance: A Cross-Disciplinary Perspective

The study emphasizes the need for a better understanding of #ai to avoid policies that may hinder its benefits. It argues for a cross-disciplinary approach to AI #governance and clarifying its core concepts to build trust. The paper addresses two key questions: 1) What is the best way to safely introduce AI to maximize well-being and #sustainability in light of its […]