In plain language
Artificial intelligence has moved, in only a few years, from a niche research topic to a technology that touches nearly every human activity. How will it reshape science, and what does it mean for society? This review brings together 25 scientists — physicists, computer scientists, psychologists, neuroscientists, lawyers, mathematicians and physicians — from the Advisory Board of the Universal Scientific Education and Research Network (USERN) and invited AI experts to lay out a shared, interdisciplinary vision.
The article first works to establish clear definitions of intelligence and consciousness, then surveys the state of the art of AI systems (including large language models) and their applications. It examines the implications, opportunities and liabilities of AI in representative fields of science, and then turns to AI's potential risks for modern society, including scenarios the authors argue deserve serious attention even if some would today dismiss them as alarmist.
Beyond diagnosis, the authors propose remedies. They suggest a qualitative “Torino scale for AI” — modelled on the scale astronomers use to rank asteroid impact threats — that maps the likelihood of AI-related threats against their severity, so the research community can prioritise attention where the combined risk is greatest. They also argue that scientists have a moral obligation to inform society about impending threats and to help raise concerns to a level where policy changes can be proposed and supported.
Key findings
- Presents a collective, interdisciplinary vision from 25 USERN Advisory Board members and AI experts on how AI is transforming both scientific research and society at large.
- Attempts to establish clear working definitions of intelligence and consciousness before assessing what current AI systems can and cannot do.
- Reviews the state of the art of AI — notably the exponential growth in performance and diffusion of large language models — and its impact across representative scientific fields.
- Identifies areas of concern, up to and including potential global existential threats, and argues these require serious, careful consideration rather than dismissal.
- Proposes a “Torino scale for AI”, analogous to the asteroid-impact scale, mapping the perceived likelihood of AI threats against their severity over 10-, 30-, and longer-year horizons to guide research and policy priorities.
- Concludes that scientists have a moral obligation to inform society about AI risks and to foster discussion at multiple levels so that effective policy responses can emerge.
How to cite
APA
Dorigo, T., Brown, G. D., Casonato, C., Cerdà, A., Ciarrochi, J., Da Lio, M., D'Souza, N., Gauger, N. R., Hayes, S. C., Hofmann, S. G., Johansson, R., Liwicki, M., Lotte, F., Nieto, J. J., Olivato, G., Parnes, P., Perry, G., Plebe, A., Rao, I. M., ... Yazdanpanah, N. (2025). Artificial intelligence in science and society: The vision of USERN. IEEE Access, 13, 15993–16054. https://doi.org/10.1109/ACCESS.2025.3529357
BibTeX
@article{dorigo2025artificial,
title = {Artificial Intelligence in Science and Society: The Vision of {USERN}},
author = {Dorigo, Tommaso and Brown, Gary D. and Casonato, Carlo and Cerd{\`a}, Artemi and Ciarrochi, Joseph and Da Lio, Mauro and D'Souza, Nicole and Gauger, Nicolas R. and Hayes, Steven C. and Hofmann, Stefan G. and Johansson, Robert and Liwicki, Marcus and Lotte, Fabien and Nieto, Juan J. and Olivato, Giulia and Parnes, Peter and Perry, George and Plebe, Alice and Rao, Idupulapati M. and Rezaei, Nima and Sandin, Fredrik and Ustyuzhanin, Andrey and Vallortigara, Giorgio and Vischia, Pietro and Yazdanpanah, Niloufar},
journal = {IEEE Access},
year = {2025},
volume = {13},
pages = {15993--16054},
doi = {10.1109/ACCESS.2025.3529357}
}
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Author: Joseph Ciarrochi (ORCID 0000-0003-0471-8100). Free copy hosted with permission for scholarly use. Please cite the published version via the DOI above.