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Machine Learning (ML) Platforms Can Contradict Dairy Scientists and Feed Firm Websites Regarding Dairy Cattle Performance from Feeding Seaweed Supplements

Author

Listed:
  • O’Keefe, Siobhan
  • Welsh, Rick
  • Oppong, Mercy
  • Fitzgerald, Ryan
  • Conner, David
  • Tynan, Michelle
  • Price, Nichole
  • Quigle, Charlotte

Abstract

Artificial intelligence through machine learning applications (hereafter ML) is emerging as a tool in evaluating, comparing, and going beyond human capabilities and knowledge. Despite the potential benefits of ML as a resource for answering scientific questions, such as those included in our analysis, some characteristics of ML-generated responses limit the interpretations of these results—such as ML “hallucinations”—of which researchers should be aware (McIntosh et al., 2023). Nonetheless, ML is quickly becoming a source for authoritative and trusted information on many topics (Knight, 2024; McIntosh et al., 2024), as university-based and other more rigorous research may be behind paywalls or otherwise difficult to access and as pay-to-play journals proliferate. Therefore, it is useful to conduct analyses comparing ML-generated information to traditionally trusted information sources, such as scientists’ observations, and to self-interested commercial information available to the public.

Suggested Citation

  • O’Keefe, Siobhan & Welsh, Rick & Oppong, Mercy & Fitzgerald, Ryan & Conner, David & Tynan, Michelle & Price, Nichole & Quigle, Charlotte, 2024. "Machine Learning (ML) Platforms Can Contradict Dairy Scientists and Feed Firm Websites Regarding Dairy Cattle Performance from Feeding Seaweed Supplements," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 39(03), July.
  • Handle: RePEc:ags:aaeach:344751
    DOI: 10.22004/ag.econ.344751
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