Consumer Trust in AI–Human News Collaborative Continuum: Preferences and Influencing Factors by News Production Phases

Heim, Steffen; Chan-Olmsted, Sylvia

doi:10.3390/journalmedia4030061

Cited by 2 publications

(1 citation statement)

References 44 publications

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“…Trust in news media, a cornerstone of consumer engagement and a reflection of societal values, emerges as a critical lens through which the implications of AI integration must be viewed [26,27]. The dual imperatives of maintaining societal trust while navigating financial sustainability render the integration of AI into news processes a complex endeavour [28,29].…”

Section: Literature Reviewmentioning

confidence: 99%

Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry

Żywiołek

2024

Management Systems in Production Engineering

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The incorporation of artificial intelligence (AI) into industrial processes has seen substantial development, characterized by the shift from Industry 4.0 to the future concept of Industry 5.0. The article identifies a significant gap in knowledge regarding how openness in AI engagement influences consumer trust and confidence in news media. This gap highlights the need for further exploration into the relationship between transparency in AI processes and consumer perceptions. The research utilises a combination of qualitative and quantitative approaches, gathering insights from academic literature, industry viewpoints, and actual data. We conduct an extensive analysis of existing literature to investigate the process of incorporating artificial intelligence into news creation and its influence on the level of confidence consumers have in the news. We have identified a significant lack of knowledge about the impact of openness in AI engagement on consumer views and trust in news media. Expanding on this discrepancy, we suggest a systematic methodology that incorporates controlled experiments and surveys to evaluate the influence of different degrees of openness on consumer trust and involvement with AI-generated news content. In addition, the paper examines the difficulties in establishing confidence in artificial intelligence (AI) inside the European Union, including several aspects such as technological, ethical, social, and legal considerations. The document presents a thorough plan to guarantee the secure development and execution of AI, with a focus on the significance of transparency, ethics, and teamwork. The study’s results provide vital insights for politicians, news organisations, and industrial businesses as they navigate the intricate process of integrating AI. Comprehensive Plan for Secure AI Development, to address the challenges outlined, the article presents a thorough plan for ensuring the secure development and execution of AI within the European Union. This plan emphasizes the significance of transparency, ethics, and collaboration in building trust and confidence in AI technologies.

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Section: Literature Reviewmentioning

confidence: 99%

Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry

Żywiołek

2024

Management Systems in Production Engineering

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The general attitudes towards artificial intelligence (GAAIS): A meta-analytic reliability generalization study

Şahin,

Yıldırım

2024

International Journal of Assessment Tools in Education

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This study aims to generalize the reliability of the GAAIS, which is known to perform valid and reliable measurements, is frequently used in the literature, aims to measure one of today's popular topics, and is one of the first examples developed in the field. Within the meta-analytic reliability generalization study, moderator analyses were also conducted on some categorical and continuous variables. Cronbach's α values for the overall scale and the positive and negative subscales, and McDonald's ω coefficients for positive and negative subscales were generalized. Google Scholar, WOS, Taylor & Francis, Science Direct, and EBSCO databases were searched to obtain primary studies. As a result of the screening, 132 studies were found, and these studies were reviewed according to the inclusion criteria. Reliability coefficients obtained from 19 studies that met the criteria were included in the meta-analysis. While meta-analytic reliability generalization was performed according to the random effects model, moderator analyses were performed according to the mixed effect model based on both categorical variables and continuous variables. As a result of the research pooled, Cronbach's α was 0.881, 0.828, and 0.863 for total, the negative, and positive subscales respectively. Also, McDonald's ω was 0.873 and 0.923 for negative and positive subscales respectively. It was found that there were no significant differences between the reliability coefficients for all categorical variables. On the other hand, all continuous moderator variables (mean age, standard deviation age, and rate of female) had a significant effect.

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Consumer Trust in AI–Human News Collaborative Continuum: Preferences and Influencing Factors by News Production Phases

Cited by 2 publications

References 44 publications

Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry

Building Trust in AI-Human Partnerships: Exploring Preferences and Influences in the Manufacturing Industry

The general attitudes towards artificial intelligence (GAAIS): A meta-analytic reliability generalization study

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