Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Motivators and detractors to integration of the user AI experience
0
Zitationen
1
Autoren
2026
Jahr
Abstract
Abstract Developers and marketers of artificial intelligence (AI) powered innovations have pushed technology to the forefront, well ahead of user experience and ethical implications. This exploratory study used qualitative semi-structured interviews ( N = 21) and then quantitative analysis ( N = 629) to predict user motivators and detractors to AI adaptation. Fifty-eight percent of respondents in this study did not agree that AI will benefit our society. There was a significant difference those identified as highly feminine and the highly masculine. Those politically conservative were less likely to support AI initiatives than those politically liberal. Independent variables were factored into latent themes “Ethical Outcomes”, Social Media Risk vs. Reward”, and “Governmental Constraint.” Ethical Outcomes was the key significant predictor of “trust AI with my personal and business activities.” The effect of Social Media Risk was marginal but significant. Logistic regression with the dependent variable “overall, artificial intelligence will benefit our society” once again captured Ethical Outcomes. The concern for social media implications was 19% more likely to be considered when pondering beneficence of AI in society. Governmental Constraint was 70% more likely to occur. When AI is considered as a future religious entity, users perceive a decrease in benefit to society. A hierarchical decision tree with the target variable “trust related to AI” illustrates users first consider ethical implications of AI in society, and then face dilemmas of copyright infringement and effect on political elections.
Ähnliche Arbeiten
The global landscape of AI ethics guidelines
2019 · 4.626 Zit.
The Limitations of Deep Learning in Adversarial Settings
2016 · 3.876 Zit.
Trust in Automation: Designing for Appropriate Reliance
2004 · 3.443 Zit.
Fairness through awareness
2012 · 3.294 Zit.
Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer
1987 · 3.184 Zit.