Restricted accessResearch articleFirst published online 2026
A new age for (generative) sports reporting: Testing the effect of AI ethics policies on the perceived trustworthiness and financial value of AI-generated sports news
It is becoming more common for established news organizations to begin using generative AI for the production of news. How do readers respond to these news organizations when AI has first been introduced, and can AI news disclosures be used to improve the trustworthiness and financial value of AI content? An online experiment (N = 713) was conducted in the immediate aftermath of ESPN introducing AI generated news to their web site. Study results found that exposure to an AI disclosure before exposure to sports news written by AI improved perceptions of news trustworthiness relative to sports news without preceding AI disclosure. Mediation analyses reveal that perceptions of AI disclosure, supervision, helpfulness and ethicality mediated effects of the AI disclosure on message trustworthiness and the perceived financial value of AI-written news. Theoretical and practical implications are discussed.
AllenMIliescuDGreiffS (2022) Single item measures in psychological science: a call to action. European Journal of Psychological Assessment38(1): 1–5. https://doi.org/10.1027/1015-5759/a000699
2.
BergkvistLRossiterJR (2007) The predictive validity of multiple-item versus single-item measures of the same constructs. Journal of Marketing Research44(2): 175–184. https://doi.org/10.1509/jmkr.44.2.175
BlomJNHeiselbergLvan DalenA, et al. (2025) “I think it’s exciting and frightening at the same time”: audience sentiments toward the use and labeling of generative AI in journalism. Journalism & Mass Communication Quarterly10776990251385943. Available at: https://doi.org/10.1177/10776990251385943
5.
BurgoonJK (2015) Expectancy violations theory. In: BergerCRRoloffMEWilsonSR, et al. (eds) The International Encyclopedia of Interpersonal Communication. Wiley, Vol. 26, pp. 1–9. https://doi.org/10.1002/9781118540190.wbeic102
6.
ChenWThorsonE (2024) News subscription motivation: why audiences pay for news. Journalism & Communication Monographs26(4): 264–323. https://doi.org/10.1177/15226379241279644
CloudyJBanksJBowmanND (2021) The str(AI)ght scoop: artificial intelligence cues reduce perceptions of hostile media bias. Digital Journalism11: 1–20. https://doi.org/10.1080/21670811.2021.1969974
9.
CummingsJJReevesB (2022) Stimulus sampling and research integrity. In: JussimLKrosnickJAStevensST (eds). Research Integrity: Best Practices for the Social and Behavioral Sciences. Oxford University Press, 203.
10.
DeVellisRFThorpeCT (2021) Scale Development: Theory and Applications. Sage Publications.
11.
DobberTHameleersMStarkeC, et al. (2025) A beacon of trustworthiness in a sea of disinformation: does news coverage about the dangers of generative AI cause people to flock to journalism?International Journal of Communication19: 21.
12.
FletcherRAndiSBadrinathanS, et al. (2025) The link between changing news use and trust: longitudinal analysis of 46 countries. Journal of Communication75(1): 1–15. https://doi.org/10.1093/joc/jqae044
GraefeAHaimMHaarmannB, et al. (2018) ‘readers’ perception of computer-generated news: credibility, expertise, and readability. Journalism19(5): 595–610. https://doi.org/10.1177/1464884916641269
15.
HenestrosaALGrevingHKimmerleJ (2023) Automated journalism: the effects of AI authorship and evaluative information on the perception of a science journalism article. Computers in Human Behavior138. Available at: https://doi.org/10.1016/j.chb.2022.107445
16.
HenkeJHoltrupSMöhringW (2023) The more, the better? Effects of transparency tools and moderators on the perceived credibility of news articles. Journalism24(6): 1301–1321. https://doi.org/10.1177/14648849211060692
17.
HongJChangHHTewksburyD (2024) Can AI become walter cronkite? Testing the machine heuristic, the hostile media effect, and political news written by artificial intelligence. Digital Journalism13: 845–868. https://doi.org/10.1080/21670811.2024.2323000
18.
JangWChunJWKimS, et al. (2023) The effects of anthropomorphism on how people evaluate algorithm-written news. Digital Journalism11(1): 103–124. https://doi.org/10.1080/21670811.2021.1976064
19.
JiaHAppelmanAWuM, et al. (2024) News bylines and perceived AI authorship: effects on source and message credibility. Computers in Human Behavior: Artificial Humans2(2): 100093. https://doi.org/10.1016/j.chbah.2024.10009
JungJSongHKimY, et al. (2017) Intrusion of software robots into journalism: the public’s and journalists’ perceptions of news written by algorithms and human journalists. Computers in Human Behavior71: 291–298. https://doi.org/10.1016/j.chb.2017.02.022
22.
KarlssonM (2021) Transparency and Journalism: A Critical Appraisal of a Disruptive Norm. 1st edition. Routledge. https://doi.org/10.4324/9780429340642
23.
KarlssonMClerwallC (2018) Transparency to the Rescue? Evaluating citizens’ views on transparency tools in journalism. Journalism Studies19(13): 1923–1933. https://doi.org/10.1080/1461670X.2018.1492882
24.
KoliskaM (2021) Transparency in journalismOxford Research Encyclopedia of Communication. Oxford University Press, pp. 1488–1508.
25.
KunertJ (2025) Perception of nonhuman-versus human-written news by recipients. In: SarısakaloğluALöffelholzM (eds). The Handbook of Artificial Intelligence and Journalism, Chapter 20. Wiley. Available at: https://doi.org/10.1002/9781394250424.ch20
26.
LeeJ (2015) The double-edged sword: the effects of journalists' social media activities on audience perceptions of journalists and their news products. Journal of Computer-Mediated Communication20(3): 312–329. https://doi.org/10.1111/jcc4.12113
27.
LeeDCJhangJBaekTH (2025) AI-Generated news content: the impact of AI writer identity and perceived AI human-likeness. International Journal of Human-Computer Interaction41(21): 13862–13874. https://doi.org/10.1080/10447318.2025.2477739
28.
LeuppertRWeinmannCEidenJ (2025) AI-reporters as the future of journalism? Investigating recipients’ credibility evaluations of AI-authored news. Journalism14648849251382484. Available at: https://doi.org/10.1177/14648849251382484
MakslAAshleySCraftS (2015) ‘Measuring news media literacy’, Journal of Media Literacy Education6(3): 29–45.
31.
MarkovČMinY (2023) Unpacking public animosity toward professional journalism: a qualitative analysis of the differences between media distrust and cynicism. Journalism24(10): 2136–2154. https://doi.org/10.1177/14648849221122064
32.
MasulloGMCurryALWhippleKN, et al. (2021) The story behind the story: examining transparency about the journalistic process and news outlet credibility. Journalism Practice15(10): 1287–1305. https://doi.org/10.1080/17512786.2020.1870529
MatthewsRAPineaultLHongYH (2022) Normalizing the use of single-item measures: validation of the single-item compendium for organizational psychology. Journal of Business and Psychology37(4): 639–673. https://doi.org/10.1007/s10869-022-09813-3
MetzgerMJFlanaginAJEyalK, et al. (2003) Credibility for the 21st century: integrating perspectives on source, message, and media credibility in the contemporary media environment. Annals of the International Communication Association27(1): 293–335. https://doi.org/10.1080/23808985.2003.11679029
39.
MolinaMDSundarSS (2022) When AI moderates online content: effects of human collaboration and interactive transparency on user trust. Journal of Computer-Mediated Communication27(4): zmac010. https://doi.org/10.1093/jcmc/zmac010
40.
MorosoliSResendezVNaudtsL, et al. (2025) “I resist”. A study of individual attitudes towards generative AI in journalism and acts of resistance, risk perceptions, trust and credibility. Digital Journalism1–20. Available at: https://doi.org/10.1080/21670811.2024.2435579
41.
NanzABinderAMatthesJ (2025) AI in the newsroom: does the public trust automated journalism and will they pay for it?Journalism Studies26(14): 1745–1764. https://doi.org/10.1080/1461670X.2025.2547301
SunYLiaoMMSundarSS, et al. (2026) Does transparency matter when an AI system meets performance expectations? An experiment with an online dating site. Computers in Human Behavior17: 108875. https://doi.org/10.1016/j.chb.2025.108875
45.
SundarSS (2008) The MAIN model: a heuristic approach to understanding technology effects on credibility. In: MetzgerMJFlanaginAJ (eds) Digital Media, Youth, and Credibility. MIT Press, pp. 73–100.
46.
ThomasRJ (2019) Helpfulness as journalism’s normative anchor: addressing blind spots and going back to basics. Journalism Studies20(3): 364–380. https://doi.org/10.1080/1461670X.2017.1377103
47.
ThurmanNStaresSKoliskaM (2024) Audience evaluations of news videos made with various levels of automation: a population-based survey experiment. Journalism26(1): 3–23. https://doi.org/10.1177/14648849241243189
48.
ToffBSimonFM (2024) Or they could just not use it? the dilemma of AI disclosure for audience trust in news. International Journal of Press/Politics30: 881–903. https://doi.org/10.1177/19401612241308697
49.
TsfatiYCappellaJN (2003) Do people watch what they do not trust? Exploring the association between news media skepticism and exposure. Communication Research30(5): 504–529. https://doi.org/10.1177/0093650203253371
50.
TsfatiYPeriY (2006) Mainstream media skepticism and exposure to sectorial and extranational news media: the case of Israel. Mass Communication & Society9(2): 165–187. https://doi.org/10.1207/s15327825mcs0902_3
51.
TulinMPantaziMStarkeC, et al. (2025) Echoes of doubt: exposure to information about generative AI decreases believability of news. International Journal of Communication19: 3712–3735.
52.
Van DalenA (2019) Journalism, trust, and credibilityThe Handbook of Journalism Studies. Routledge, pp. 356–371.
WaddellTF (2019a) Attribution practices for the man-machine marriage: how perceived human intervention, automation metaphors, and byline location affect the perceived bias and credibility of purportedly automated content. Journalism Practice13(10): 1255–1272. https://doi.org/10.1080/17512786.2019.1585197
55.
WaddellTF (2019b) Can an algorithm reduce the perceived bias of news? Testing the effect of machine attribution on news readers’ evaluations of bias, anthropomorphism, and credibility. Journalism & Mass Communication Quarterly96(1): 82–100. https://doi.org/10.1177/1077699018815891
56.
WaddellTF (2025) The effects of AI attribution, source priming, and story topic polarization on news credibility. Digital Journalism1–18. Available at: https://doi.org/10.1080/21670811.2025.2551628
57.
WaddellTF (2026) The How and Why of Generative AI: The Effect of AI Disclosure Policies on the Perceived Trustworthiness and Financial Value of Automated News. Mass Communication & Society.
58.
WaddellTFSparksJ (2025) Analyzing automated news: a review of experimental evidence across 20 years of research. Review of Communication1–15. Available at: https://doi.org/10.1080/15358593.2025.2569434
59.
WangSHuangG (2024) The impact of machine authorship on news audience perceptions: a meta-analysis of experimental studies. Communication Research51(7): 815–842. https://doi.org/10.1177/0093650224122
60.
WangROphirY (2024) Behind the Black box: the moderating role of the machine heuristic on the effect of transparency information about automated journalism on hostile media bias perception. Journalism27: 103–121. https://doi.org/10.1177/14648849241284575
61.
WangROphirY (2025) Can professional or AI fact-checking protect trust in journalism from political attacks? The complex roles of source, transparency, ideology, and the machine heuristic. Computers in Human Behavior176: 108872. https://doi.org/10.1016/j.chb.2025.108872
62.
WangROphirY (2026) Behind the black box: The moderating role of the machine heuristic on the effect of transparency information about automated journalism on hostile media bias perception. Journalism27(1): 103–121.
63.
WardSJA (2014) The magical concept of transparency. In: ZionLCraigD (eds) Ethics for Digital Journalists: Emerging Best Practices. Routledge, pp. 45–58.
64.
WischnewskiMKrämerN (2025) Does polarizing news become less polarizing when written by an AI? Investigating the perceived credibility of news attributed to a machine in the light of the confirmation bias. Journal of Media Psychology: Theories, Methods, and Applications37(6): 388–399. https://doi.org/10.1027/1864-1105/a000441
65.
ZhaoSZhouJWangT (2025) When the news comes from a bot: how AI authorship and emotion shape cognitive, affective, and behavioral responses. Journalism14648849251381218. Available at: https://doi.org/10.1177/14648849251381218
