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Framework, Standards, Applications and Best practices of Responsible AI : A Comprehensive Survey

arXiv 2504.13979 ↗First posted 18 Apr 2025cs.CY cs.AIcited by 0

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Abstract (arXiv)

Responsible Artificial Intelligence (RAI) is a combination of ethics associated with the usage of artificial intelligence aligned with the common and standard frameworks. This survey paper extensively discusses the global and national standards, applications of RAI, current technology and ongoing projects using RAI, and possible challenges in implementing and designing RAI in the industries and projects based on AI. Currently, ethical standards and implementation of RAI are decoupled which caters each industry to follow their own standards to use AI ethically. Many global firms and government organizations are taking necessary initiatives to design a common and standard framework. Social pressure and unethical way of using AI forces the RAI design rather than implementation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 104 references that are in the map. First posted on arXiv 18 Apr 2025.

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17 of 104 references.

References · 17

  1. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,917
  2. 2017Towards A Rigorous Science of Interpretable Machine Learningcited by 1,416
  3. 2017Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPRcited by 1,089
  4. 2018Audio Adversarial Examples: Targeted Attacks on Speech-to-Textcited by 274
  5. 2020Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claimscited by 165
  6. 2017Fairness in Machine Learning: Lessons from Political Philosophycited by 149
  7. 2016Research Priorities for Robust and Beneficial Artificial Intelligencecited by 74
  8. 2020Trustworthy AIcited by 62
  9. 2023ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Reviewcited by 28
  10. 2021Ethics-Based Auditing to Develop Trustworthy AIcited by 23
  11. 2021Ethics of AI: A Systematic Literature Review of Principles and Challengescited by 18
  12. 2024Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkitscited by 10
5 more
  1. 2024The Ethics of AI in Educationcited by 7
  2. 2021Actionable Principles for Artificial Intelligence Policy: Three Pathwayscited by 5
  3. 2024Using Case Studies to Teach Responsible AI to Industry Practitionerscited by 3
  4. 2024A Manifesto for a Pro-Actively Responsible AI in Educationcited by 2
  5. 2024Integrating ESG and AI: A Comprehensive Responsible AI Assessment Frameworkcited by 2

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