Rethinking AI literacy education in higher education
Bridging risk perception and responsible adoption
Bibliographic Data
| ID | 22204516 |
|---|---|
| Authors | Shasha Yu (0000-0001-5336-4519, Clark University, corresponding author), Fiona Carroll (0000-0002-9967-2207, Cardiff Metropolitan University), Barry L Bentley (0000-0002-4360-5902, Harvard University) |
| Year | 2026 |
| Volume | 13 |
| Pages | 102751 |
| Publication date | 2026-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Sciences & Humanities Open (JOURNAL) |
| Journal identifiers | ISSN: 2590-2911 • E-ISSN: 2590-2911 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ssaho.2026.102751 |
| OpenAlex | W7154495922 |
| Language | EN |
| References cited | 33 |
As AI becomes increasingly embedded across societal domains, understanding how future AI practitioners—particularly technology students—perceive its risks is essential for responsible development and adoption. This study analyzed responses from 139 students in Computer Science, Data Science/Data Analytics, and other disciplines using both explicit AI risk ratings and scenario-based assessments of risk and adoption willingness. Four key findings emerged: (1) Students expressed substantially higher concern for concrete, explicitly stated risks than for abstract or scenario-embedded risks; (2) Perceived risk and willingness to adopt AI demonstrated a clear inverse relationship; (3) Although technical education narrowed gender differences in risk awareness, male students reported higher adoption willingness; and (4) A form of “risk underappreciation” was observed, wherein students in AI-related specializations showed both elevated explicit risk awareness and higher willingness to adopt AI, despite lower recognition of risks in applied scenarios. These findings underscore the need for differentiated AI literacy strategies that bridge the gap between awareness and responsible adoption and offer valuable insights for educators, policymakers, industry leaders, and academic institutions aiming to cultivate ethically informed and socially responsible AI practitioners
Digital Literacy · Literacy · Perception · Risk perception · Ethics and Social Impacts of AI · Online Learning and Analytics · Teaching and Learning Programming
The effects of over-reliance on AI dialogue systems on students' cognitive abilities
The impact of generative artificial intelligence on socioeconomic inequalities and policy making
Principles alone cannot guarantee ethical AI
A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
Gender Differences in the Perception and Use of E-Mail
Construal-level theory of psychological distance.
The theory of planned behavior
User Acceptance of Information Technology
Perceptions and Use of AI Chatbots among Students in Higher Education
Transparency in artificial intelligence
An artificial intelligence perspective
Ethics of autonomous weapons systems and its applicability to any AI systems
The filter bubble generated by artificial intelligence algorithms and the network dynamics of collective polarization on YouTube
Artificial intelligence vs Covid-19
Transparency and the Black Box Problem
Fake news, disinformation and misinformation in social media
Artificial intelligence, algorithms, and social inequality
Gender differences in risk taking
| Citation velocity | historical |
|---|---|
| Highly cited | No |