Generative AI is already widespread in the public sector: evidence from a survey of UK public sector professionals
Generative AI has the potential to transform how public services are delivered by enhancing productivity and reducing time spent on bureaucracy. But to what extent is the technology already in use? Our survey of UK public service professionals (in education, health, social work, and emergency services) seeks to answer this question. We find that use of generative AI is widespread: 45% of respondents were aware of colleagues using generative AI, while 22% use it themselves. Respondents were positive about its potential to enhance their efficiency and reduce their bureaucratic workload. For example, those working in the health service thought that time spent on bureaucracy could drop by the equivalent of one day per week, an enormous potential impact. Our survey also found a high amount of trust (61%) in generative AI and a low fear of replacement (16%). However, only a minority of respondents (32%) felt like there was clear guidance on generative AI usage in their workplaces. In other words, it is clear that generative AI is already coming into the public sector, but uptake is happening in a disorganised fashion without clear guidelines. The UK’s public sector urgently needs to develop more systematic methods for taking advantage of the technology.
Authors
- Youmna Hashem (ORCID: https://orcid.org/0009-0008-2339-1805)
- Saba Esnaashari (ORCID: https://orcid.org/0009-0004-5874-8270)
- Florence E. Enock (ORCID: https://orcid.org/0000-0003-2108-4891)
- Jonathan Bright (ORCID: https://orcid.org/0000-0002-1248-9275)
- John Francis (ORCID: https://orcid.org/0000-0003-1405-4408)
- Deborah Morgan (ORCID: https://orcid.org/0000-0002-0142-9736)
Institutions
- The Alan Turing Institute (GB)
Publication Details
- Journal
- Digital Government Research and Practice
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1145/3700140
- Citations
- 21
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 11.05