Putting-Science-Into-Standards
A decade of rapid development of artificial intelligence (AI) resulted in the release of a large diversity of practical applications across sectors. Data play a fundamental role for AI systems, which can be seen as adaptive data processing algorithms that adjust outputs to input training data. This fundamental role of data is reflected in the EU policy agenda where for example guidance on handling the data is specified in the AI Act. A Putting Science Into Standards workshop on data quality requirements for inclusive, nonbiased, and trustworthy artificial intelligence took place on 8 and 9 June 2022, with more than 178 participants from 36 countries gathering for the first time European standardisation experts, legislators, scientists, and societal stakeholders to map pre-normative research and standardisation needs. We highlighted those during the creation and documentation of datasets all along to data quality requirements, bias examination and mitigation during the employment of the AI system. We identified steps to start the process of drafting new standards and recognised that inclusiveness and full representation of all relevant stakeholders, including industry, SMEs representatives, civil society, and academia is crucial. Building a stronger engagement of experts in AI standardisation is essential to contribute to the development of standards that are needed not only to support the market deployment of AI systems in accordance with the AI act but also to support this growing field of research.
Balahur-Dobrescu, A., Jenet, A., Hupont Torres, I., Charisi, V., Ganesh, A., Griesinger, C., Maurer, P., Mian, L., Salvi, M., Scalzo, S., Soler Garrido, J., Taucer, F. and Tolan, S., Data quality requirements for inclusive, non-biased and trustworthy AI, Publications Office of the European Union, Luxembourg, 2022, ISBN 978-92-76-59091-0, doi:10.2760/365479, JRC131097.
2022-12-05
Publications Office of the European Union
JRC131097
978-92-76-59091-0 (online)
OP KJ-03-22-173-EN-N (online)