Abstract
Abstract
Artificial intelligence (AI) is rapidly transforming various sectors, raising concerns about its ethical implications and potential risks. AI audits have emerged as a crucial tool for organizations to ensure responsible AI development and deployment. This research report provides a comprehensive guide to conducting AI audits, covering key aspects such as how to conduct an audit, how to use AI audit toolkits, types of AI audits, legal and regulatory requirements, ethical considerations, and available resources. By utilizing this toolkit, organizations can effectively assess and mitigate risks associated with AI, promoting fairness, transparency, and accountability in their AI systems.
Appendix - Key areas include bias identification and mitigation, transparency, fairness metrics, adversarial auditing, and documentation best practices. The guide also outlines steps for evaluating AI systems during pre-processing, in-processing, and post-processing stages, offering robust methodologies to promote accountability and continual improvement.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Bharathan, Ramkumar, "ARTIFICIAL INTELLIGENCE - Comprehensive Guide for Effective Algorithm Evaluation and SOX – ITGC And Business Audit Toolkit and examples", Technical Disclosure Commons, (January 06, 2025)
https://www.tdcommons.org/dpubs_series/7699