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Awareness and perception of artificial intelligence operationalized integration in news media industry and society

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Abstract

This study attempts to determine a correlation effect between people’s perception and awareness of the operationalization of artificial intelligence in their everyday lives and in the production, presentation, and publication of news media in the U.S. By looking at the effect individual characteristics may have on a person’s perception and awareness of AI operationalized for news media and looking at whether perception and/or awareness of AI operationalized in a person’s daily life affects their perception and awareness of AI operationalized for news media, we seek to find correlation between these two factors. The research relies on Actor-network theory, the MAIN (Modality, Agency, Interactivity, Navigability) Model, and utilizes a convenience sample survey method using the MTurk participant platform.

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Data availability statement

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Notes

  1. As early as 2006, Thompson Reuters began using algorithms to automatically generate financial news content to free up human journalists for more nuanced reporting that computers were incapable of producing (Dalen 2012). Other news organizations have begun to rely on AI to produce similar news content (e.g., sports articles, elections, and earnings reports). Xinhua news agency, in collaboration with Sogu search company, produced the first male and female AI broadcast news anchors. Thompson Reuters is now in expanded development of similar technology to generate a male persona AI news anchor.

  2. The intermediary refers to a ‘thing’ as a ‘mean’ or ‘tool’ and is defined as an entity capable of transporting meaning without transformation (i.e., a computer) (Latour 2005).

  3. A mediator is defined as an entity capable of transforming, distorting, and/or modifying meaning (Latour 2005).

  4. Researchers found that MTurk exhibited concerns regarding demographic mapping to U.S. census data. According to Buhrmester et al. (2018), the pool is not representative of the U.S. population. Sheehan (2018) notes in her findings that workers on MTurk are generally younger than the U.S. population overall, better educated, predominately Caucasian, and mostly male.

  5. According to the Nielsen Total Audience Report: Q1 2019, adults age 18–34 are a targeted interest group for marketers, the 35–49 age group is the “key” market, and people age 50–64 have been consistently the largest group of media consumers (The Nielsen Total Audience Report 2019).

  6. MTurk workers accounted for more than 40% of studies published from 2012 to 2017 in the Journal of Consumer Research, and many other fields, such as psychology and political science, rely on MTurk for data collection (Sheehan 2018).

  7. To facilitate participant payment, four separate instances of the survey were initiated on the Qualtrics platform. An attention check asking for the respondent’s age-limited responses to meet the desired amount of participation to satisfy a 95% confidence level per age group.

  8. Tesla reached a global vehicle distribution level of 367,000–368,000 in 2019 (Wagner, 2020).

  9. Autopilot, the system Tesla has designed for their autonomous vehicles has been in development since at least 2014 (White 2014). In an article for Wired Magazine in 2015, Musk was quoted as stating he believed “full autonomy will be here from Tesla in 3 years” (McHugh 2015 para. 24).

  10. Artificial Narrow Intelligence (ANI) is the weakest level of the three classifications: narrow, general, and super (Kaplan and Haenlein, 2019). It is below human level intelligence, and contains all known AI systems currently in operation (Kaplan and Haenlein 2019). ANI is considered weaker than human intelligence because an ANI system cannot borrow intelligence or knowledge from memories or experiences outside of its programmed operation (Kaplan and Haenlein 2019). Within its programmed operationalization, an ANI will outperform a human assigned the same task, however, an ANI is incapable of adaptation beyond its specific program (Kaplan and Haenlein 2019).

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The authors received no financial support for the research, authorship, and/or publication of this article.

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All the authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by CSO. The first draft of the manuscript was written by CSO, and all the authors commented on previous versions of the manuscript. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Chad S. Owsley.

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Owsley, C.S., Greenwood, K. Awareness and perception of artificial intelligence operationalized integration in news media industry and society. AI & Soc 39, 417–431 (2024). https://doi.org/10.1007/s00146-022-01386-2

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  • DOI: https://doi.org/10.1007/s00146-022-01386-2

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