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

arXiv: https://arxiv.org/abs/2504.13979 · HTML: https://mlsanity.com/paper/2504.13979/

## 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.

## Builds on (most cited first, 17 of 17)

- [A Survey on Bias and Fairness in Machine Learning](https://mlsanity.com/paper/1908.09635/) (2019)
- [Towards A Rigorous Science of Interpretable Machine Learning](https://mlsanity.com/paper/1702.08608/) (2017)
- [Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR](https://mlsanity.com/paper/1711.00399/) (2017)
- [Audio Adversarial Examples: Targeted Attacks on Speech-to-Text](https://mlsanity.com/paper/1801.01944/) (2018)
- [Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims](https://mlsanity.com/paper/2004.07213/) (2020)
- [Fairness in Machine Learning: Lessons from Political Philosophy](https://mlsanity.com/paper/1712.03586/) (2017)
- [Research Priorities for Robust and Beneficial Artificial Intelligence](https://mlsanity.com/paper/1602.03506/) (2016)
- [Trustworthy AI](https://mlsanity.com/paper/2011.02272/) (2020)
- [ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review](https://mlsanity.com/paper/2305.03123/) (2023)
- [Ethics-Based Auditing to Develop Trustworthy AI](https://mlsanity.com/paper/2105.00002/) (2021)
- [Ethics of AI: A Systematic Literature Review of Principles and Challenges](https://mlsanity.com/paper/2109.07906/) (2021)
- [Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkits](https://mlsanity.com/paper/2403.00145/) (2024)
- [The Ethics of AI in Education](https://mlsanity.com/paper/2406.11842/) (2024)
- [Actionable Principles for Artificial Intelligence Policy: Three Pathways](https://mlsanity.com/paper/2102.12406/) (2021)
- [Using Case Studies to Teach Responsible AI to Industry Practitioners](https://mlsanity.com/paper/2407.14686/) (2024)
- [A Manifesto for a Pro-Actively Responsible AI in Education](https://mlsanity.com/paper/2407.05423/) (2024)
- [Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework](https://mlsanity.com/paper/2408.00965/) (2024)

## 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.