33
Accepted
Require AI model developers to summarise bias mitigation and report output bias levels.
Conclusion
Model developers and deployers should be required to summarise what steps they have taken to account for bias in datasets used to train models, and to statistically report on the levels of bias present in outputs produced using AI tools. This data should be routinely disclosed in a similar way to company pay gap reporting.
Government Response Summary
The government states the Algorithmic Transparency Recording Standard (ATRS) is now mandatory for government departments and includes fields for reporting bias mitigations and training data. DSIT is actively developing robust fairness tests, has provided grant funding for bias-related solutions, and is developing a Responsible AI Toolkit for bias testing and reporting.
Paragraph Reference
141
Government Response
Accepted
Government Response
Accepted
HM Government
Accepted
The Algorithmic Transparency Recording Standard (ATRS) is now mandatory for all Government departments, with an intent to extend to the broader public sector over time. It includes fields on risks and appropriate mitigations taken to ensure that tools perform appropriately and fairly, including impact assessments. The ATRS also includes fields requiring algorithmic tool deployers to summarise the data used to train the models underpinning their tools, including steps taken to ensure clean and complete data. DSIT is working with industry and academia to develop robust tests for fairness and bias in AI systems. The Responsible Technology Adoption Unit, alongside the Information Commissioner’s Office and the Equality and Human Rights Commission, is running the Fairness Innovation Challenge. This is a grant challenge that has given over £465,000 of Government funding to support the development of socio-technical solutions to address bias and discrimination in AI systems. We are thrilled to have funded four projects to develop sociotechnical solutions to improve fairness in AI systems across four different sectors. Grant funding has been awarded to: The Open University (Higher Education); The Alan Turing Institute (Finance); King’s College London (Healthcare); and Coefficient Systems Ltd (Recruitment). DSIT is also developing the AI Management Essentials tool, a self- assessment tool for SMEs and startups to achieve baseline “responsible AI” practices in their organisation. The tool distils key principles from existing AI-related frameworks and standards including ISO/IEC 42001, the NIST Risk Management framework, and the EU AI Act. The tool will provide an open access, simplified baseline of requirements for responsible and trustworthy AI development and deployment, including requirements related to bias testing and reporting. In addition, the Public Sector Equality Duty in the Equality Act 2010 requires public authorities, and those carrying out public functions, to have due regard to the need to eliminate discrimination, advance equality of opportunity, and foster good relations between different people. This includes when using AI to exercise public functions. This Government is committed to protecting and upholding the Public Sector Equality Duty, including in relation to AI. Government response to Committee recommendations 34 – 35
Source
Report
Third Report - Governance of artificial intelligence (AI)
28 May 2024
HC 38
Addressee Bodies
Department for Science, Innovation and Technology
Timeline
Recommendation age
2.0 yrs
Report published
28 May 2024