Australian public understandings of artificial intelligence

Selwyn, Neil; Cordoba, Beatriz Gallo

doi:10.1007/s00146-021-01268-z

Cited by 43 publications

(53 citation statements)

References 37 publications

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“…Concerning AI issues, the most frequent mentions were connected to workplace issues such as job opportunities or job losses due to AI. Regarding Figure 1: Concerns about AI among the German Population technical issues, AI was frequently connected to robotics, which is in line with the study of Selwyn and Gallo Cordoba (2021). Only a small portion of respondents name ethical aspects as the most salient issues.…”

Section: Resultssupporting

confidence: 76%

“…Research on public opinion on AI found that, while many people have heard about the term, usually, only some of the surveyed people suggest to have an idea of what AI is and what AI entails, or claim to be somewhat knowledgeable about AI, respectively (Cave, Coughlan, & Dihal, 2019;Selwyn & Gallo Cordoba, 2021). Thereby, AI is mostly associated with technical terms, foremost robots or computers (Cave et al, 2019;Kelley et al, 2021;Selwyn & Gallo Cordoba, 2021). All in all, when surveyed, current AI technology is perceived rather positively in various countries (Fietta, Zecchinato, Di Stasi, Polato, & Monaro, 2021;Kelley et al, 2021;Zhang & Dafoe, 2019).…”

Section: Public Opinion On Aimentioning

confidence: 99%

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Ever heard of ethical AI? Investigating the salience of ethical AI issues among the German population

Kieslich¹,

Lünich²,

Dosenovic³

2022

Preprint

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Building and implementing ethical AI systems that benefit the whole society is cost-intensive and a multi-faceted task fraught with potential problems. While computer science focuses mostly on the technical questions to mitigate social issues, social science addresses citizens' perceptions to elucidate social and political demands that influence the societal implementation of AI systems. Thus, in this study, we explore the salience of AI issues in the public with an emphasis on ethical criteria to investigate whether it is likely that ethical AI is actively requested by the population. Between May 2020 and April 2021, we conducted 15 surveys asking the German population about the most important AI-related issues (total of N=14,988 respondents). Our results show that the majority of respondents were not concerned with AI at all. However, it can be seen that general interest in AI and a higher educational level are predictive of some engagement with AI. Among those, who reported having thought about AI, specific applications (e.g., autonomous driving) were by far the most mentioned topics. Ethical issues are voiced only by a small subset of citizens with fairness, accountability, and transparency being the least mentioned ones. These have been identified in several ethical guidelines (including the EU Commission's proposal) as key elements for the development of ethical AI. The salience of ethical issues affects the behavioral intentions of citizens in the way that they 1) tend to avoid AI technology and 2) engage in public discussions about AI. We conclude that the low level of ethical implications may pose a serious problem for the actual implementation of ethical AI for the Common Good and emphasize that those who are presumably most affected by ethical issues of AI are especially unaware of ethical risks. Yet, once ethical AI is top of the mind, there is some potential for activism.

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Section: Resultssupporting

confidence: 76%

Section: Public Opinion On Aimentioning

confidence: 99%

Ever heard of ethical AI? Investigating the salience of ethical AI issues among the German population

Kieslich¹,

Lünich²,

Dosenovic³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…3 a). This low awareness about when, where, and how data are being gathered by and used in AI systems—even in the context of familiar everyday applications such as email filters and ride-sharing apps—is broadly consistent with prior surveys [ 31 , 32 ]. We note trends in AI awareness were broadly similar among the five countries, and people generally reported less awareness of AI use in embedded technologies (e.g.…”

Section: Conditions Heightening the Risk Of Harm From Ai Systemssupporting

confidence: 76%

AI-deploying organizations are key to addressing ‘perfect storm’ of AI risks

2022

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We argue that a perfect storm of five conditions heightens the risk of harm to society from artificial intelligence: (1) the powerful, invisible nature of AI, (2) low public awareness and AI literacy, (3) rapid scaled deployment of AI, (4) insufficient regulation, and (5) the gap between trustworthy AI principles and practices. To prevent harm, fit-for-purpose regulation and public AI literacy programs have been recommended, but education and government regulation will not be sufficient: AI-deploying organizations need to play a central role in creating and deploying trustworthy AI in line with the principles of trustworthy AI, and taking accountability to mitigate the risks.

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“…59–63 A recent study by Monash University explored public attitudes towards AI technologies in Australia and found that survey participants changed their initial opinions and preconceptions about AI when provided with education. 64 Research into undergraduate, postgraduate and specialised medical professionals’ knowledge of AI has begun, in an effort to build a framework for education in the future. 35,65–67 These studies acknowledge that understanding of AI is limited amongst medical students and that deciding on the content of education is challenging, but training will be necessary to realise the full capacity of this technology.…”

Section: Discussionmentioning

confidence: 99%

Exploring healthcare professionals’ perceptions of artificial intelligence: Validating a questionnaire using the e-Delphi method

et al. 2021

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Objective The aim of this study was to draw upon the collective knowledge of experts in the fields of health and technology to develop a questionnaire that measured healthcare professionals’ perceptions of Artificial Intelligence (AI). Methods The panel for this study were carefully selected participants who demonstrated an interest and/or involvement in AI from the fields of health or information technology. Recruitment was accomplished via email which invited the panel member to participate and included study and consent information. Data were collected from three rounds in the form of an online survey, an online group meeting and email communication. A 75% median threshold was used to define consensus. Results Between January and March 2019, five healthcare professionals and three IT experts participated in three rounds of study to reach consensus on the structure and content of the questionnaire. In Round 1 panel members identified issues about general understanding of AI and achieved consensus on nine draft questionnaire items. In Round 2 the panel achieved consensus on demographic questions and comprehensive group discussion resulted in the development of two further questionnaire items for inclusion. In a final e-Delphi round, a draft of the final questionnaire was distributed via email to the panel members for comment. No further amendments were put forward and 100% consensus was achieved. Conclusion A modified e-Delphi method was used to validate and develop a questionnaire to explore healthcare professionals’ perceptions of AI. The e-Delphi method was successful in achieving consensus from an interdisciplinary panel of experts from health and IT. Further research is recommended to test the reliability of this questionnaire.

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Australian public understandings of artificial intelligence

Cited by 43 publications

References 37 publications

Ever heard of ethical AI? Investigating the salience of ethical AI issues among the German population

Ever heard of ethical AI? Investigating the salience of ethical AI issues among the German population

AI-deploying organizations are key to addressing ‘perfect storm’ of AI risks

Exploring healthcare professionals’ perceptions of artificial intelligence: Validating a questionnaire using the e-Delphi method

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