Mr PASCHAL OCHANG Paschal.Ochang@nottingham.ac.uk
Responsible Innovation in AutonomousSystems Research Fellow
Responsible Generative AI for SMEs in the UK and Africa: RAISE guidelines
Ochang, Paschal; Stahl, Bernd; Eke, Damian; Buckley, Matt; Poder, Irma; Hughes, Joshua; Rodrigues, Rowena; Barnard-Wills, David
Authors
Professor BERND STAHL Bernd.Stahl@nottingham.ac.uk
PROFESSOR OF CRITICAL RESEARCH IN TECHNOLOGY
Dr DAMIAN EKE Damian.Eke@nottingham.ac.uk
TRANSITIONAL ASSISTANT PROFESSOR
Matt Buckley
Irma Poder
Joshua Hughes
Rowena Rodrigues
David Barnard-Wills
Abstract
Small to Medium Enterprises (SMEs), including technology start-ups, are driving the development of Generative Artificial Intelligence products and services, whilst some non-technology SMEs are enthusiastically adopting these tools. However, SMEs do not typically have the in-house resources or specialists for responsible AI deployment, particularly in fast-moving areas with uncertain regulation and guidance. Further, SMEs are embedded in commercial ecosystems and therefore can be at the mercy of larger providers. In the case of generative AI, SMEs will often be deploying tools on other parties’ terms and conditions.
Beyond the described challenges experienced within the UK generative AI context, SMEs in Africa operate within diverse languages, cultures, and traditions. How generative AI systems align with or are sensitive to socio-cultural needs, contexts and expectations is critically important to the global discourse on ethical AI.
Explicitly, these guidelines consider:
The lack of control by SMEs over the generative AI tools used, including lack of access to data collection and validation at scale. The developing nature of AI ethics guidance and the lack of its specificity and/or tailoring to the SME research and software development context. The extra effort and time required by SMEs to ensure responsible AI practices. The impact of local culture, norms, and practices on AI use future challenges related to regulatory changes. The pace of developments in generative AI.
Citation
Ochang, P., Stahl, B., Eke, D., Buckley, M., Poder, I., Hughes, J., Rodrigues, R., & Barnard-Wills, D. (2024). Responsible Generative AI for SMEs in the UK and Africa: RAISE guidelines. Responsible AI UK
Report Type | Project Report |
---|---|
Online Publication Date | Mar 1, 2024 |
Publication Date | Mar 1, 2024 |
Deposit Date | Jan 3, 2025 |
Publicly Available Date | Mar 1, 2025 |
DOI | https://doi.org/10.17639/r59s-3w96 |
Keywords | Small and Medium Enterprises (SMEs), AI Guidelines for SMEs, Generative AI, AI Policy Recommendations, Responsible AI in Africa, Generative AI Challenges, Mitigation Strategies |
Public URL | https://nottingham-repository.worktribe.com/output/43682460 |
Publisher URL | https://raise-project.uk/about-raise/ |
Other Repo URL | https://raise-project.uk/wp-content/uploads/2024/03/Raise-Guideliness-V1.pdf |
Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
Build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation
Reduce inequality within and among countries
Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
Strengthen the means of implementation and revitalize the global partnership for sustainable development
Files
Responsible Generative AI for SMEs in UK and Africa (RAISE) Guidelines
(4.9 Mb)
PDF
You might also like
Trustworthy Airspaces of the Future: Hopes and concerns of experts regarding Uncrewed Traffic Management systems
(2024)
Presentation / Conference Contribution
Perceptions on the Ethical and Legal Principles that Influence Global Brain Data Governance
(2024)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search