Patient and Physician Exposure to Artificial Intelligence Hype

Abstract

Both patients and physicians are routinely exposed to the corporate promotion of artificial intelligence (AI) for healthcare products. Hype for AI products may impact both patient behavior and attitudes about healthcare. Corporate AI hype may intentionally overlook the known limitations associated with AI products and focus solely on potential benefits. As AI is increasingly integrated into medicine, physicians are also routinely subject to AI hype. As the promotion and use of AI products have grown dramatically in recent years, physicians should be aware of the potential benefits and risks of AI products despite the hype.

Keywords

artificial intelligence - AI hype - medical hype - hype

Publikationsverlauf

Eingereicht: 06. Januar 2025

Angenommen nach Revision: 10. März 2025

Artikel online veröffentlicht:
12. Mai 2025

• References

• 1 IDC. IDC Forecasts Spending on GenAI solutions will double in 2024 and grow to $151.1 billion in 2027. 2023 https://www.idc.com/getdoc.jsp?containerId=prUS51572023
• 2 Bick A, Blandin A, Deming DJ. The rapid adoption of generative AI. Federal Reserve Bank of St. Louis Working Paper 2024-2027 2024;
• 3 Bourne C. AI hype, promotional culture, and affective capitalism. AI and Ethics 2024; 1-3
• 4 Caulfield T, Condit C. Science and the sources of hype. Public Health Genomics 2012; 15: 209-217
• 5 Marcus GF. Taming silicon valley: How we can ensure that AI works for us. MIT Press; 2024
• 6 Kissinger HA, Schmidt E, Huttenlocher D. The age of AI: And our human future. Hachette UK. 2021
• 7 Narayanan A, Kapoor S. AI snake oil: What artificial intelligence can do, what it can’t, and how to tell the difference. Princeton University Press; 2024
• 8 Bobrowsky M, Krouse S. The Celebrities Lending Their Voices to Meta’s New AI. The Wall Street Journal. 2024 https://www.wsj.com/tech/ai/meta-turns-to-awkwafina-john-cena-to-draw-users-to-ai-7ffc302a
• 9 Kahneman Daniel. Thinking, fast and slow. Macmillan. 2011
• 10 LaGrandeur K. The consequences of AI hype. AI and Ethics 2024; 4: 653-656
• 11 Smil V. Invention and innovation: A brief history of hype and failure. MIT Press; 2023: 156-159
• 12 Smith GN. LLMS can’t be trusted for financial advice. Journal of Financial Planning. 2024 https://www.financialplanningassociation.org/learning/publications/journal/MAY24-journal-may-2024
• 13 Pearson J. Google research shows the fast rise of AI generated misinformation. CBC. 2024 https://www.cbc.ca/news/science/artificial-intelligence-misinformation-google-1.7217275
• 14 Tubaro P. Learners in the loop: Hidden human skills in machine intelligence. Sociologia del Lavoro 2022; 163: 110-129
• 15 Thais S. Misrepresented Technological Solutions in Imagined Futures: The Origins and Dangers of AI Hype in the Research Community. In: Proceedings of the AAAI/ACM conference on AI, ethics, and society 2024; 7: 1455-1465
• 16 Funk J. Unicorns, hype, and bubbles: A guide to spotting, avoiding, and exploiting investment bubbles in tech. Hampshire: Harriman House. 2024 9.
• 17 Tan R, Cabato R. Behind the AI boom, an army of overseas workers in ‘digital sweatshops’. The Washington Post. 2023 https://www.washingtonpost.com/world/2023/08/28/scale-ai-remotasks-philippines-artificial-intelligence/
• 18 Vadde A. Inside and outside the Language Machines. PMLA 2024; 139: 553-558
• 19 Stanford. Getting beyond the hype: A guide to AI’s potential 2024 https://online.stanford.edu/getting-beyond-hype-guide-ais-potential
• 20 IBM. AI in action 2024 https://www.ibm.com/think/reports/ai-in-action
• 21 Strange M. Three different types of AI hype in healthcare. AI and Ethics. 2024: 1-8
• 22 Princeton. AI may be as effective as medical specialists at diagnosing disease 2024 https://www.cs.princeton.edu/~sayashk/ai-hype/cnn/cnn.html
• 23 Doctronic. 2024 https://www.doctronic.ai/?matchtype=p
• 24 Mayo Clinic Press. AI in healthcare: The future of patient care and health management 2024 https://mcpress.mayoclinic.org/healthy-aging/ai-in-healthcare-the-future-of-patient-care-and-health-management/
• 25 Caulfield T. Spinning the genome: Why science hype matters. Perspect Biol Med 2018; 61: 560-571
• 26 Dierickx L, Slavkovik M. Talking to journalists about AI. 2024 https://www.researchgate.net/profile/Laurence-Dierickx/publication/385086106_Talking_to_journalists_about_AI/links/6715243509ba2d0c760eae3b/Talking-to-journalists-about-AI.pdf
• 27 Glassock RJ. Artificial intelligence in medicine and nephrology: hope, hype, and reality. Clin Kidney J 2024; 17: sfae074
• 28 Omiye JA, Gui H, Rezaei SJ. et al. Large language models in medicine: The potentials and pitfalls: a narrative review. Ann Intern Med 2024; 177: 210-220
• 29 Silcox C, Zimlichmann E, Huber K. et al. The potential for artificial intelligence to transform healthcare: Perspectives from international health leaders. NPJ Digit Med 2024; 7: 88
• 30 Robeznikes A. AI is already reshaping care. Here's what it means for doctors. AMA. 2024 https://www.ama-assn.org/practice-management/digital/ai-already-reshaping-care-heres-what-it-means-doctors
• 31 Marcus G. LLMs don’t do formal reasoning - and that is a HUGE problem. 2024b https://garymarcus.substack.com/p/llms-dont-do-formal-reasoning-and
• 32 Mirzadeh I, Alizadeh K, Shahrokhi H. et al. Gsm-symbolic: Understanding the limitations of mathematical reasoning in large language models. arXiv preprint arXiv. 2024 2410.05229
• 33 Lowe D. AI and biology. Science. 2024 https://www.science.org/content/blog-post/ai-and-biology
• 34 Xu Z, Biswas B, Li L. et al. AI/ML in precision medicine: A look beyond the hype. Ther Innov Regul Sci 2023; 57: 957-962
• 35 Burke G, Schellmann H. Researchers say an AI-powered transcription tool used in hospitals invents things no one said. AP. https://www.ap.org/news-highlights/best-of-the-week/honorable-mention/2024/researchers-say-an-ai-powered-transcription-tool-used-in-hospitals-invents-things-no-one-said/
• 36 Finlayson SG, Subbaswamy A, Singh K. et al. The clinician and dataset shift in artificial intelligence. N Engl J Med 2021; 385: 283-286
• 37 Monteith S, Glenn T, Geddes JR. et al. Differences between human and artificial/augmented intelligence in medicine. Computers in Human Behavior: Artificial Humans 2024; 2: 100084
• 38 Perry TS. Andrew Ng. X-rays the AI hype. IEEE Spectrum 2021 https://spectrum.ieee.org/andrew-ng-xrays-the-ai-hype
• 39 Kapoor S, Narayanan A. A checklist of eighteen pitfalls in AI journalism. 2022 https://www.cs.princeton.edu/~sayashk/ai-hype/ai-reporting-pitfalls.pdf
• 40 Ramkumar PN, Pang M, Polisetty T. et al. Meaningless applications and misguided methodologies in artificial intelligence–related orthopaedic research propagates hype over hope. Arthroscopy 2022; 38: 2761-2766
• 41 Bohr A, Memarzadeh K. The rise of artificial intelligence in healthcare applications. In: Artificial Intelligence in healthcare. Academic Press; 2020: 25-60
• 42 Chen IY, Joshi S, Ghassemi M. Treating health disparities with artificial intelligence. Nat Med 2020; 26: 16-17
• 43 Moons P, Van Bulck L. Using ChatGPT and Google Bard to improve the readability of written patient information: A proof of concept. Eur J Cardiovasc Nurs 2024; 23: 122-126
• 44 Kirchner GJ, Kim RY, Weddle JB. et al. Can artificial intelligence improve the readability of patient education materials?. Clin Orthop Relat Res 2023; 481: 2260-2267
• 45 Alowais SA, Alghamdi SS, Alsuhebany N. et al. Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Med Educ 2023; 23: 689
• 46 Mello MM, Guha N. Understanding liability risk from using health care artificial intelligence tools. N Engl J Med 2024; 390: 271-278
• 47 Liu X, Glocker B, McCradden MM. et al. The medical algorithmic audit. Lancet Digit Health 2022; 4: e384-e397