SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Three Challenges to Secure AI Systems in the Context of AI Regulations
8 references·1 citing·41 second hop
Three Challenges to Secure AI Systems in the Context of AI Regulations (2024)Three Challenges to Secure AI Systems in …Explanatory memorandum on the updated OECD definition of an AI system (2023)Explanatory memorandum on the…Artificial Intelligence Risk Management Framework (AI RMF 1.0) (2023)Artificial Intelligence Risk …Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database (2021)Preventing Repeated Real Worl…On the Opportunities and Risks of Foundation Models (2021)On the Opportunities and Risk…Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions (2019)Artificial Intelligence Crime…Artificial intelligence : a European perspective (2018)Artificial intelligence : a E…How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)How the machine ‘thinks’: Und…Agnostic Learning with Unknown Utilities (2016)Agnostic Learning with Unknow…Robustness and Cybersecurity in the EU Artificial Intelligence Act (2025)Robustness and Cybersecurity …Fairness through awareness (2012)The second machine age: work, progress, and prosperity in a time of brilliant technologies (2015)The future of employment: How susceptible are jobs to computerisation? (2016)Artificial Intelligence and the Public Sector—Applications and Challenges (2018)“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI (2021)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)I.—COMPUTING MACHINERY AND INTELLIGENCE (1950)Intentionality (1983)Computing Machinery and Intelligence (1950) (2004)Governing Artificial Intelligence to benefit the UN Sustainable Development Goals (2020)Bad machines corrupt good morals (2021)Fooled twice: People cannot detect deepfakes but think they can (2021)The accuracy, fairness, and limits of predicting recidivism (2018)Filling gaps in trustworthy development of AI (2021)Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women * (2022)Artificial intelligence in government: Concepts, standards, and a unified framework (2023)AI auditing: The Broken Bus on the Road to AI Accountability (2024)Big Data's Disparate Impact (2014)The Relevance of Algorithms (2014)The ethics of algorithms: Mapping the debate (2016)Algorithms at Work: The New Contested Terrain of Control (2019)Nature of Prejudice (1954)Transforming Our World: The 2030 Agenda for Sustainable Development (2018)HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case (2019)TruthfulQA: Measuring How Models Mimic Human Falsehoods (2022)Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond (2023)Generative AI at Work (2023)Human Compatible: Artificial Intelligence and the Problem of Control (2019)OECD Framework for the Classification of AI systems (2022)Artificial Intelligence and Entrepreneurship (2024)Digital sovereignty and artificial intelligence: a normative approach (2024)The emergence of artificial intelligence ethics auditing (2024)To Predict and Serve? (2016)Algorithmic Decision Making and the Cost of Fairness (2017)Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)The impact of artificial intelligence on labor productivity (2021)Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union (2022)Mitigation Pathways Compatible with Long-term Goals (2023)"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust (2024)Trust in AI: progress, challenges, and future directions (2024)AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development (2025)
this work references cited by second hop

References

  • 2016How the machine ‘thinks’: Understanding opacity in machine learning algorithms3,179 cited
  • 2021On the Opportunities and Risks of Foundation Models2,670 cited
  • 2016Agnostic Learning with Unknown Utilities1,314 cited
  • 2023Artificial Intelligence Risk Management Framework (AI RMF 1.0)1,275 cited
  • 2019Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions271 cited
  • 2021Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database155 cited
  • 2018Artificial intelligence : a European perspective111 cited
  • 2023Explanatory memorandum on the updated OECD definition of an AI system68 cited

Cited by

  • 2025Robustness and Cybersecurity in the EU Artificial Intelligence Act10 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work