Abstract
Artificial Intelligence (AI) is attracting a great deal of attention and it is important to investigate the public perceptions of AI and their impact on the perceived credibility of research evidence. In the literature, there is evidence that people overweight research evidence when framed in neuroscience findings. In this paper, we present the findings of the first investigation of the impact of an AI frame on the perceived credibility of educational research evidence. In an experimental study, we allocated 605 participants including educators to one of three conditions in which the same educational research evidence was framed within one of: AI, neuroscience, or educational psychology. The results demonstrate that when educational research evidence is framed within AI research, it is considered as less credible in comparison to when it is framed instead within neuroscience or educational psychology. The effect is still evident when the subjects’ familiarity with the framing discipline is controlled for. Furthermore, our results indicate that the general public perceives AI to be: less helpful in assisting us to understand how children learn, lacking in adherence to scientific methods, and to be less prestigious compared to neuroscience and educational psychology. Considering the increased use of AI technologies in Educational settings, we argue that there should be significant attempts to recover the public image of AI being less scientifically robust and less prestigious than educational psychology and neuroscience. We conclude the article suggesting that AI in Education community should attempt to be more actively engaged with key stakeholders of AI and Education to help mitigate such effects.
Highlights
Within the last decade, the private sector has invested heavily in large scale projects to develop Artificial Intelligence (AI) that can interact with humans (Hall and Pesenti 2017)
We explored the public perceptions of AI and their perceived credibility of research evidence about education framed to different areas of scientific research, : educational psychology, neuroscience, and AI
When we looked at the particular group of educators to see if the results we observed for the general public would obtain for teachers, we found similar results that AI framed articles were considered statistically significantly less credible than educational psychology and neuroscience framed ones by educators
Summary
The private sector has invested heavily in large scale projects to develop AI that can interact with humans (Hall and Pesenti 2017). In healthcare for example, where deep learning algorithms have been trained to identify pathology automatically from optical coherence tomography (OCT) scans to enable early detection and triage of sight-threatening diabetic retinopathy and age-related macular degeneration, to advise doctors, and interpret fMRI scans (De Fauw et al 2018). These technologies are developing at a rapid pace and they are increasingly entering our everyday lives. A similar phenomenon was noted in the early 2000s and 2010s when the term ‘neuroscience’ was popular and its ‘seductive allure’ was noted by some researchers (McCabe and Castel 2008; Im et al 2017)
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