Building Human Systems of Trust in an Accelerating Digital and AI-Driven World

Walter, Yoshija

doi:10.3389/fhumd.2022.926281

Cited by 4 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yet, this study has shown that more must be done to increase public trust in AI and encourage the adoption of new technologies. For instance, Walter (2022) has suggested that certifications can be awarded to trustworthy technology by agencies that are deemed to uphold the public good. Public confidence in the Singaporean government have remained consistently high throughout the years (Ho, 2021), presenting a unique opportunity to mitigate unwarranted perceptions of AI-related risks: the government can award certifications to deserving products.…”

Section: Discussionmentioning

confidence: 99%

Understanding user interactions and perceptions of AI risk in Singapore

Neyazi,

Ng,

Hobbs

et al. 2023

Big Data & Society

View full text Add to dashboard Cite

Artificial Intelligence (AI) is becoming increasingly prevalent and its application highly sophisticated. Concerns about AI's vulnerabilities and future threats have, however, long been debated among scientists and the tech community. By integrating Beck's theory of risk society with an audience-centered sense-making approach, we seek to understand the effects of AI on the general public's daily lives and their concerns when they adopt AI technology. Five focus groups with 36 participants from Singapore, a technologically advanced country, were conducted to investigate their risk perceptions of AI and AI-powered technology. We found that participants were not passive consumers of content showing up on their news feeds; indeed, some participants attempted to outsmart the algorithms. They were aware that tech companies often tweak algorithms to personalize content and drive consumers into rabbit holes. Nevertheless, despite a certain level of awareness and sporadic attempts to “outsmart” the system, many users might still be influenced by these algorithms, underscoring the extent to which consumers are often manipulated by smart tech powered by AI. We discuss the theoretical and policy implications of our findings by looking at the contextual factors.

show abstract

Section: Discussionmentioning

confidence: 99%

Understanding user interactions and perceptions of AI risk in Singapore

Neyazi,

Ng,

Hobbs

et al. 2023

Big Data & Society

View full text Add to dashboard Cite

show abstract

“…The first deals with the problem of AI misalignment, the second with the problem of human abuse, and the third with the problem of information control (cf. [127]).…”

Section: Risks Of Ai Competitionmentioning

confidence: 99%

“…But as soon as people could access these technologies more broadly, they also would have the potential to abuse them if they wanted to. And just with anything else, there will surely be some people who will want to use these technologies with harmful intentions [28,75,127].…”

Section: Risks Of Ai Competitionmentioning

confidence: 99%

“…These rapid AI developments harbor their own economic dynamics, which raises the question of how the associated risks can be managed and mitigated. The risks deal with an underrepresentation of AI safety concerns [127]. The main question, then, is how to ensure that the focus on trustworthiness remains a pivotal concern, both in the books of large incumbents as well as when it comes to newcomers entering the field.…”

Section: Managing the Risksmentioning

confidence: 99%

See 1 more Smart Citation

The rapid competitive economy of machine learning development: a discussion on the social risks and benefits

Walter

2023

AI Ethics

Self Cite

View full text Add to dashboard Cite

Research in artificial intelligence (AI) has started in the twentieth century but it was not until 2012 that modern models of artificial neural networks aided the machine learning process considerably so that in the past ten years, both computer vision as well as natural language processing have become increasingly better. AI developments have accelerated rapidly, leaving open questions about the potential benefits and risks of these dynamics and how the latter might be managed. This paper discusses three major risks, all lying in the domain of AI safety engineering: the problem of AI alignment, the problem of AI abuse, and the problem of information control. The discussion goes through a short history of AI development, briefly touching on the benefits and risks, and eventually making the case that the risks might potentially be mitigated through strong collaborations and awareness concerning trustworthy AI. Implications for the (digital) humanities are discussed.

show abstract

Artificial influencers and the dead internet theory

Walter

2024

AI & Soc

View full text Add to dashboard Cite

Building Human Systems of Trust in an Accelerating Digital and AI-Driven World

Cited by 4 publications

References 29 publications

Understanding user interactions and perceptions of AI risk in Singapore

Understanding user interactions and perceptions of AI risk in Singapore

The rapid competitive economy of machine learning development: a discussion on the social risks and benefits

Artificial influencers and the dead internet theory

Contact Info

Product

Resources

About