The EU AI Act is a good start but falls short
- URL: http://arxiv.org/abs/2411.08535v3
- Date: Mon, 09 Dec 2024 08:01:13 GMT
- Title: The EU AI Act is a good start but falls short
- Abstract summary: The EU AI Act was created to ensure ethical and safe AI development and deployment across the EU.<n>This study aims to identify key challenges and strategies for helping enterprises focus on resources effectively.
- Score: 3.4632900249241874
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The EU AI Act was created to ensure ethical and safe Artificial Intelligence (AI) development and deployment across the EU. This study aims to identify key challenges and strategies for helping enterprises focus on resources effectively. To achieve this aim, we conducted a Multivocal Literature Review (MLR) to explore the sentiments of both the industry and the academia. From 130 articles, 56 met the criteria. Our key findings are three-fold. First, liability. Second, discrimination. Third, tool adequacy. Additionally, some negative sentiments were expressed by industry and academia regarding regulatory interpretations, specific requirements, and transparency issues. Next, our findings are three essential themes for enterprises. First, risk-based regulatory compliance. Second, ethical frameworks and principles in technology development. Third, policies and systems for regulatory risk management. These results identify the key challenges and strategies and provide less commonly discussed themes, enabling enterprises to align with the requirements and minimize their distance from the EU market.
Related papers
- Towards a Framework for Supporting the Ethical and Regulatory Certification of AI Systems [8.633165810707315]
CERTAIN project aims to integrate regulatory compliance, ethical standards, and transparency into AI systems.<n>We outline the methodological steps for building the core components of this framework.<n>CERTAIN aims to advance regulatory compliance and to promote responsible AI innovation aligned with European standards.
arXiv Detail & Related papers (2025-09-30T08:54:02Z) - Never Compromise to Vulnerabilities: A Comprehensive Survey on AI Governance [211.5823259429128]
We propose a comprehensive framework integrating technical and societal dimensions, structured around three interconnected pillars: Intrinsic Security, Derivative Security, and Social Ethics.<n>We identify three core challenges: (1) the generalization gap, where defenses fail against evolving threats; (2) inadequate evaluation protocols that overlook real-world risks; and (3) fragmented regulations leading to inconsistent oversight.<n>Our framework offers actionable guidance for researchers, engineers, and policymakers to develop AI systems that are not only robust and secure but also ethically aligned and publicly trustworthy.
arXiv Detail & Related papers (2025-08-12T09:42:56Z) - Media and responsible AI governance: a game-theoretic and LLM analysis [61.132523071109354]
This paper investigates the interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems.
Using evolutionary game theory and large language models (LLMs), we model the strategic interactions among these actors under different regulatory regimes.
arXiv Detail & Related papers (2025-03-12T21:39:38Z) - Between Innovation and Oversight: A Cross-Regional Study of AI Risk Management Frameworks in the EU, U.S., UK, and China [0.0]
This paper conducts a comparative analysis of AI risk management strategies across the European Union, United States, United Kingdom (UK), and China.
The findings show that the EU implements a structured, risk-based framework that prioritizes transparency and conformity assessments.
The U.S. uses a decentralized, sector-specific regulations that promote innovation but may lead to fragmented enforcement.
arXiv Detail & Related papers (2025-02-25T18:52:17Z) - Robustness and Cybersecurity in the EU Artificial Intelligence Act [1.433758865948252]
The EU Artificial Intelligence Act (AIA) establishes different legal principles for different types of AI systems.
While prior work has sought to clarify some of these principles, little attention has been paid to robustness and cybersecurity.
We identify legal challenges and shortcomings in provisions related to robustness and cybersecurity for high-risk AI systems.
arXiv Detail & Related papers (2025-02-22T11:12:20Z) - Unlocking the Black Box: Analysing the EU Artificial Intelligence Act's Framework for Explainability in AI [0.0]
The need for eXplainable AI (XAI) is evident in fields such as healthcare, credit scoring, policing and the criminal justice system.
At the EU level, the notion of explainability is one of the fundamental principles that underpin the AI Act.
This paper explores various approaches and techniques that promise to advance XAI, as well as the challenges of implementing the principle of explainability in AI governance and policies.
arXiv Detail & Related papers (2025-01-24T16:30:19Z) - From Principles to Practice: A Deep Dive into AI Ethics and Regulations [13.753819576072127]
The article thoroughly analyzes the ground-breaking AI regulatory framework proposed by the European Union.
Considering the technical efforts and strategies undertaken by academics and industry to uphold these principles, we explore the synergies and conflicts among the five ethical principles.
arXiv Detail & Related papers (2024-12-06T00:46:20Z) - The Fundamental Rights Impact Assessment (FRIA) in the AI Act: Roots, legal obligations and key elements for a model template [55.2480439325792]
Article aims to fill existing gaps in the theoretical and methodological elaboration of the Fundamental Rights Impact Assessment (FRIA)
This article outlines the main building blocks of a model template for the FRIA.
It can serve as a blueprint for other national and international regulatory initiatives to ensure that AI is fully consistent with human rights.
arXiv Detail & Related papers (2024-11-07T11:55:55Z) - Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks [55.2480439325792]
This paper critically examines the European Union's Artificial Intelligence Act (EU AI Act)
Uses insights from Alignment Theory (AT) research, which focuses on the potential pitfalls of technical alignment in Artificial Intelligence.
As we apply these concepts to the EU AI Act, we uncover potential vulnerabilities and areas for improvement in the regulation.
arXiv Detail & Related papers (2024-10-10T17:38:38Z) - Ethical and Scalable Automation: A Governance and Compliance Framework for Business Applications [0.0]
This paper introduces a framework ensuring that AI must be ethical, controllable, viable, and desirable.
Different case studies validate this framework by integrating AI in both academic and practical environments.
arXiv Detail & Related papers (2024-09-25T12:39:28Z) - Towards Responsible AI in Banking: Addressing Bias for Fair
Decision-Making [69.44075077934914]
"Responsible AI" emphasizes the critical nature of addressing biases within the development of a corporate culture.
This thesis is structured around three fundamental pillars: understanding bias, mitigating bias, and accounting for bias.
In line with open-source principles, we have released Bias On Demand and FairView as accessible Python packages.
arXiv Detail & Related papers (2024-01-13T14:07:09Z) - Report of the 1st Workshop on Generative AI and Law [78.62063815165968]
This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw)
A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal, and policy challenges presented by law for Generative AI.
arXiv Detail & Related papers (2023-11-11T04:13:37Z) - The risks of risk-based AI regulation: taking liability seriously [46.90451304069951]
The development and regulation of AI seems to have reached a critical stage.
Some experts are calling for a moratorium on the training of AI systems more powerful than GPT-4.
This paper analyses the most advanced legal proposal, the European Union's AI Act.
arXiv Detail & Related papers (2023-11-03T12:51:37Z) - A Review of the Ethics of Artificial Intelligence and its Applications
in the United States [0.0]
The paper highlights the impact AI has in every sector of the US economy and the resultant effect on entities spanning businesses, government, academia, and civil society.
Our discussion explores eleven fundamental 'ethical principles' structured as overarching themes.
These encompass Transparency, Justice, Fairness, Equity, Non- Maleficence, Responsibility, Accountability, Privacy, Beneficence, Freedom, Autonomy, Trust, Dignity, Sustainability, and Solidarity.
arXiv Detail & Related papers (2023-10-09T14:29:00Z) - Regulation and NLP (RegNLP): Taming Large Language Models [51.41095330188972]
We argue how NLP research can benefit from proximity to regulatory studies and adjacent fields.
We advocate for the development of a new multidisciplinary research space on regulation and NLP.
arXiv Detail & Related papers (2023-10-09T09:22:40Z) - Artificial Intelligence across Europe: A Study on Awareness, Attitude
and Trust [39.35990066478082]
The aim of the study is to gain a better understanding of people's views and perceptions within the European context.
We design and validate a new questionnaire (PAICE) structured around three dimensions: people's awareness, attitude, and trust.
We highlight implicit contradictions and identify trends that may interfere with the creation of an ecosystem of trust.
arXiv Detail & Related papers (2023-08-19T11:00:32Z) - Tackling problems, harvesting benefits -- A systematic review of the
regulatory debate around AI [0.0]
How to integrate an emerging and all-pervasive technology such as AI into the structures and operations of our society is a question of contemporary politics, science and public debate.
This article analyzes the academic debate around the regulation of artificial intelligence (AI)
The analysis concentrates on societal risks and harms, questions of regulatory responsibility, and possible adequate policy frameworks.
arXiv Detail & Related papers (2022-09-07T11:29:30Z) - Fairness in Agreement With European Values: An Interdisciplinary
Perspective on AI Regulation [61.77881142275982]
This interdisciplinary position paper considers various concerns surrounding fairness and discrimination in AI, and discusses how AI regulations address them.
We first look at AI and fairness through the lenses of law, (AI) industry, sociotechnology, and (moral) philosophy, and present various perspectives.
We identify and propose the roles AI Regulation should take to make the endeavor of the AI Act a success in terms of AI fairness concerns.
arXiv Detail & Related papers (2022-06-08T12:32:08Z) - Ethics of AI: A Systematic Literature Review of Principles and
Challenges [3.7129018407842445]
Transparency, privacy, accountability and fairness are identified as the most common AI ethics principles.
Lack of ethical knowledge and vague principles are reported as the significant challenges for considering ethics in AI.
arXiv Detail & Related papers (2021-09-12T15:33:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.