Skip to main content
SpringerLink
Log in

Ethical and legal challenges of informed consent applying artificial intelligence in medical diagnostic consultations

  • Open Forum
  • Published:
AI & SOCIETY Aims and scope Submit manuscript

Abstract

This paper inquiries into the complex issue of informed consent applying artificial intelligence in medical diagnostic consultations. The aim is to expose the main ethical and legal concerns of the New Health phenomenon, powered by intelligent machines. To achieve this objective, the first part of the paper analyzes ethical aspects of the alleged right to explanation, privacy, and informed consent, applying artificial intelligence in medical diagnostic consultations. This analysis is followed by a legal analysis of the limits and requirements for the explainability of artificial intelligence. Followed by this analysis, recommendations for action are given in the concluding remarks of the paper.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Academy of Royal Medical Colleges (2019) Artificial intelligence in healthcare. https://www.aomrc.org.uk/wp-content/uploads/2019/01/Artificial_intelligence_in_healthcare_0119.pdf Accessed 8 December 2019

  • Asimov I (1964) Visit to the world’s fair of 2014. New York Times 16. Available at: http://movies2.nytimes.com/books/97/03/23/lifetimes/asi-v-fair.html

  • Bächle TC (2019) On the ethical challenges of innovation in digital health. In: Bachle TC, Wernick A (eds) The futures of health: social, ethical and legal challenges. Alexander von Humboldt Institute for Internet and Society, Berlin

    Google Scholar 

  • Brkan M (2019) Do algorithms rule the world? Algorithmic decision-making and data protection in the framework of the GDPR and beyond. Int J Law Inf Technol 91:110–119

    Google Scholar 

  • Cath C (2018) Governing artificial intelligence: ethical, legal and technical opportunities and challenges. Phil Trans R Soc A 376:20180080

    Article  Google Scholar 

  • Casey B et al (2019) Rethinking explainable machines: the GDPR’s ‘Right to Explanation’ debate and the rise of algorithmic audits in enterprise. Berkeley Technol Law J 145:188

    Google Scholar 

  • Chafee Z (1919) Freedom of speech in war time. Harv L Rev 32(932):957

    Google Scholar 

  • Chan SW, Tulloch E, Cooper ES, Smith A, Wojcik W, Norman JE (2017) Montgomery and informed consent: where are we now? BMJ 357:j2224

    Article  Google Scholar 

  • Char DS, Shah NH, Magnus D (2018) Implementing machine learning in health care–addressing ethical challenges. N Engl J Med 378(11):981–983

    Article  Google Scholar 

  • Council of Europe, Convention for the Protection of Human Rights and of the Human Being with regard to the Application of Biology and Medicine (Convention on Human Rights and Biomedicine or the Oviedo Convention) (CETS n. 164)

  • De Fauw J, Ledsam JR, Romera-Paredes B, Nikolov S, Tomasev N, Blackwell S, van den Driessche G (2018) Clinically applicable deep learning for diagnosis and referral in retinal disease. Nat Med 24(9):1342

    Article  Google Scholar 

  • den Hertog J (2010). Review of economic theories of regulation. Discussion Paper Series, No. 10–18. Utrecht School of Economics. Tjalling C. Koopmans Research Institute

  • Doshi-Velez F, Kortz M, Budish R, Bavitz C, Gershman SJ, O'Brien D, Shieber S, Waldo J, Weinberger D, Wood A (2017) Accountability of AI under the law: The role of explanation. Berkman Center Research Publication Forthcoming; Harvard Public Law Working Paper No. 18–07. Available at Doi: 10.2139/ssrn.3064761

  • Dugdale DC, Epstein R, Pantilant SZ (1999) Time and the patient—physician relationship. J Gen Intern Med 14:34–40

    Article  Google Scholar 

  • Edwards L, Veale M (2017) Slave to the Algorithm? Why a ‘right to an explanation’ is probably not the remedy you are looking for 16. Duke Law Technol Rev 18:81

    Google Scholar 

  • European Commission (2018) Artificial intelligence: Commission outlines a European approach to boost investment and set ethical guidelines IP/18/3362, Brussels. Available at: https://ec.europa.eu/commission/presscorner/detail/en/IP_18_3362

  • European Commission High-Level Expert Group on Artificial Intelligence (2019) Ethics guidelines for trustworthy AI. https://ec.europa.eu/futurium/en/ai-alliance-consultation. Accessed 13 May 2019

  • European Group on Ethics in Science and New Technologies (2018) Statement on artificial intelligence, robotics and autonomous systems. Brussels, https://ec.europa.eu/research/ege/pdf/ege_ai_statement_2018.pdf. Accessed 9 April 2019

  • European Parliament (2017) Resolution of February 16 with recommendations to the Commission on Civil Law Rules on Robotics (2015/2103(INL)). https://www.europarl.europa.eu/doceo/document/TA-8-2017-0051_EN.html. Accessed 31 July 2019

  • Faden RR, Beauchamp TL (1986) A history and theory of informed consent. Oxford University Press, Oxford

    Google Scholar 

  • Feldman RC, Aldana E, Stein K (2019) Artificial intelligence in the health care space: how we can trust what we cannot know. Stanf Law Policy Rev 30(2):399–420

    Google Scholar 

  • Ferretti A, Schneider M, Blasimme A (2018) Machine learning in medicine: opening the new data protection black box. Eur Data Protect Law Rev (EDPL) 4(3):320–332

    Article  Google Scholar 

  • Floridi L et al (2018) AI4People—an ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds Mach 28(4):689–707. https://doi.org/10.1007/s11023-018-9482-5

    Article  Google Scholar 

  • Fomin VV (2018) Laying ground for responsible standardization for robotic law. 17th Annual STS Conference Graz 2018—Critical Issues in Science, Technology and Society Studies. TU Graz (Graz)

  • Frey T (2019) Increasing transparency with Google Cloud Explainable AI. https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-ai-explanations-to-increase-fairness-responsibility-and-trust, Accessed 2 May 2020

  • Froomkin A, Kerr I, Pineau J (2019) When AIs outperform doctors: confronting the challenges of tort-induced over-reliance on machine learning. Arizona Law Rev 61(1):33–100

    Google Scholar 

  • Goodman B, Flaxman S (2017) European union regulations on algorithmic decision-making and a right to explanation. AI Mag 38(3):50–57

    Google Scholar 

  • Griffiths S (2016) This AI software can tell if you're at risk from cancer before symptoms appear. Wired, 26 August, 2016. https://www.wired.co.uk/article/cancer-risk-ai-mammograms. Accessed 8 Dec 2019

  • Gulshan V, Peng L, Coram M, Stumpe MC, Wu D, Narayanaswamy A, Venugopalan S, Widner K, Madams T, Cuadros J, Kim R, Raman R, Nelson PS, Mega JL, Webster DR (2016) Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316(22):2402–2410

    Article  Google Scholar 

  • Hacker P, Krestel R, Grundmann S et al (2020) (2020) Explainable AI under contract and tort law: legal incentives and technical challenges. Artif Intell Law. https://doi.org/10.1007/s10506-020-09260-6

    Article  Google Scholar 

  • Hoeren T, Niehoff M (2018) Artificial intelligence in medical diagnoses and the right to explanation. Eur Data Prot L Rev 4:308

    Article  Google Scholar 

  • Ienca M, Wangmo T, Jotterand F, Kressig RW, Elger B (2018) Ethical design of intelligent assistive technologies for dementia: a descriptive review. Sci Eng Ethics 24(4):1035–1055

    Article  Google Scholar 

  • JettenL SS (2016) Selected issues concerning the ethical use of big datahealth analytics. Wash Lee Law Rev Online 72(3):489–501

    Google Scholar 

  • Keane PA, Topol EJ (2018) With an eye to AI and autonomous diagnosis. NPJ Digit Med 1:40

    Article  Google Scholar 

  • Kim TW and Routledge BR (2018) Informational Privacy, A Right to Explanation, and Interpretable AI, 2018 IEEE Symposium on Privacy-Aware Computing (PAC), Washington, DC, 2018, 64-74

  • Kiseleva A (2019) Decisions made by AI versus transparency: who wins in healthcare? In: Bachle TC, Wernick A (eds) The futures of health: social, ethical and legal challenges. Alexander Von Humboldt Institute for Internet and Society, Berlin

    Google Scholar 

  • Konnangath S (2019) Abu Dhabi's new policy on the use of artificial intelligence in the healthcare sector. Ct Uncourt 6:17

    Article  Google Scholar 

  • Kullar D (2018) Do You Trust the Medical Profession? N.Y. Times (Jan. 23, 2018).

  • Liang H, Tsui BY, Ni H, Valentim CC, Baxter SL, Liu G et al (2019) Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence. Nature Med 25(3):433

    Article  Google Scholar 

  • Lipton ZC (2016) The mythos of model interpretability. arXiv preprint arXiv:1606.03490

  • Liu Y, Gadepalli K, Norouzi M, Dahl GE, Kohlberger T, Boyko A, Hipp JD (2017) Detecting cancer metastases on gigapixel pathology images. arXiv preprint arXiv:1703.02442

  • Lupton M (2018) Some ethical and legal consequences of the application of artificial intelligence in the field of medicine. Trends Med 18(4):1–7

    Article  Google Scholar 

  • Mangla M, Cha TD, Dorrwachter JM et al (2018) Increasing the use of patient decision aids in orthopaedic care: results of a quality improvement project. BMJ Qual Saf 2018(27):347–354

    Article  Google Scholar 

  • Matsuzaki T (2018) Ethical issues of artificial intelligence in medicine. Calif West Law Rev 55(1):255–274

    Google Scholar 

  • McKinney SM, Sieniek M, Godbole V et al (2020) International evaluation of an AI system for breast cancer screening. Nature 577:89–94. https://doi.org/10.1038/s41586-019-1799-6

    Article  Google Scholar 

  • Mechanic D (1996) The functions and limitations of trust in the provision of medical care, 23. J Health Pol L 4:661–686

    Google Scholar 

  • Mechanic D, Schlesinger M (1998) The impact of managed care on patients' trust in medical care and their physicians. JAMA 275:1693–1697

    Article  Google Scholar 

  • Mendoza I, Bygrave LA (2017) The Right not to be Subject to Automated Decisions based on Profiling. In: Synodinou TE, Jougleux P, Markou C, Prastitou T (eds) EU Internet Law. Springer, Cham, pp 92–94. https://doi.org/10.1007/978-3-319-64955-9_4

    Chapter  Google Scholar 

  • Meskó BG, Hetényi GZ (2018) Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res 18:545

    Article  Google Scholar 

  • Michalski A, Stopa M, Miśkowiak B (2016) Use of multimedia technology in the doctor-patient relationship for obtaining patient informed consent. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research 22:3994–3999 Retrieved from www.ncbi.nlm.nih.gov/pmc/articles/PMC5085339/. Accessed 18th December 2019

  • Miller FH (1998) Health care information technology and informed consent: computers and the doctor-patient relationship. Ind Rev 31:1019

    Google Scholar 

  • Mittelstadt BD, Allo P, Taddeo M, Wachter S, Floridi L (2016) The ethics of algorithms: mapping the debate. Big Data Soc 3(2):2053951716679679

    Article  Google Scholar 

  • National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. (1979). The Belmont report: Ethical principles and guidelines for the protection of human subjects of research. https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html Accessed 2 May 2020

  • Nebeker C, Torous J, Ellis RJB (2019) Building the case for actionable ethics in digital health research supported by artificial intelligence. BMC Med 17(1):137

    Article  Google Scholar 

  • Obermeyer Z, Emanuel EJ (2016) Predicting the future—big data, machine learning, and clinical medicine. N Engl J Med 375(13):1216–1219

    Article  Google Scholar 

  • Olde Hartman TC, Borghuis MS, Lucassen PL, van de Laar FA, Speckens AE, van Weel C (2009) Medically unexplained symptoms, somatisation disorder and hypochondriasis: course and prognosis. A systematic review. J Psychosomat Res 66:363–377

    Article  Google Scholar 

  • Pagallo U (2017) Algo-Rhythms and the beat of the legal drum. Philos Technol 31(4):507–524

    Article  Google Scholar 

  • Pasquale F (2015) The black box society. The secret algorithms behind money and information. Harvard University Press, Cambridge

    Google Scholar 

  • Porsdam MS, Savulescu J, Sahakian BJ (2016) Facilitating the ethical use of health data for the benefit of society: electronic health records, consent and the duty of easy rescue. Philos Trans Royal Soc A Math Phys Eng Sci 374(2083):20160130

    Article  Google Scholar 

  • Price N (2015) Black-box medicine. Harv J Law Tech 28(2):425

    Google Scholar 

  • PricewaterhouseCoopers (2017) What Doctor? Why AI and robotics will define new health.https://www.pwc.com/gx/en/industries/healthcare/publications/ai-robotics-new-health.html. Accessed 30th November 2019

  • Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (Text with EEA relevance)

  • Robbins SA (2019) Misdirected principle with a catch: explicability for AI. Mind Mach 29:495–514. https://doi.org/10.1007/s11023-019-09509-3

    Article  Google Scholar 

  • Rossi F (2016) Artificial intelligence: potential benefits and ethical considerations. European Parliament: Policy Department C (PE 571.380), available at: https://www.europarl.europa.eu/RegData/etudes/BRIE/2016/571380/IPOL_BRI(2016)571380_EN.pdf

  • Selbst AD, Powles J (2017) Meaningful information and the right to explanation. Int Data Priv Law 7(4):233–242

    Article  Google Scholar 

  • Sepucha KR, Breslin M, Graffeo C et al (2016) (2016) State of the science: tools and measurement for shared decision making. Acad Emerg Med 23:1325–1331

    Article  Google Scholar 

  • Schiff D, Borenstein J (2019) How should clinicians communicate with patients about the roles of artificially intelligent team members? AMA J Ethics 21(2):E138–145

    Article  Google Scholar 

  • Schönberger D (2019) Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications. Int J Law Info Tech 27(2):171–203

    Article  Google Scholar 

  • Sion G (2019) Big data and machine learning in medicine: enhancing the quality of patient care in clinical practice. Am J Med Biol Res 6(1):55–60

    Google Scholar 

  • Spatz ES, Krumholz HM, Moulton BW (2016) The new era of informed consent: getting to a reasonable-patient standard through shared decision making. JAMA 315(19):2063–2064

    Article  Google Scholar 

  • Spina A (2018) New regulation or new medicine: the complex governance of personal data in medicine. EDPL 4(3):280–283

    Google Scholar 

  • Stacey D, Légaré F, Lewis KB (2017) Patient decision aids to engage adults in treatment or screening decisions. JAMA 318(7):657–658

    Article  Google Scholar 

  • Stiefel S (2019) The chatbot will see you now: protecting mental health confidentiality in software applications. Colum Sci Tech L Rev 20(2):333–387

    Google Scholar 

  • The Nuremberg Code (1949). https://history.nih.gov/research/downloads/nuremberg.pdf. Accessed 2 May 2020

  • Thom DH, Hall MA, Pawlson LG (2004) Measuring patients’ trust in physicians when assessing quality of care. Health Aff 23(4):124–132

    Article  Google Scholar 

  • Thompson DF (1980) Moral responsibility of public officials: the problem of many hands. Ame Political Sci Rev 74(4):905–916

    Article  Google Scholar 

  • Vayena E, Blasimme A, Cohen IG (2018) Machine learning in medicine: addressing ethical challenges. PLoSMed 15(11):e1002689

    Google Scholar 

  • Wachter S, Mittelstadt B, Floridi L (2017) Why a right to explanation of automated decision-making does not exist in the general data protection regulation. Int Data Priv L7(2):76–99

    Article  Google Scholar 

  • Williamson OE (1984) The economics of governance: framework and implications. Zeitschrift Für Die Gesamte Staatswissenschaft / JITE 140(1):195–223

    Google Scholar 

  • Wolf SM, Clayton EW, Lawrenz F (2018) The past, present, and future of informed consent in research and translational medicine. J Law Med Ethics 46:7–11

    Article  Google Scholar 

  • World Medical Association Declaration of Helsinki (1964). https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/. Accessed 2 May 2020

  • Yu KH, Beam AL, Kohane IS (2018) Artificial intelligence in healthcare. Nat Biomed Eng 2(10):719–731

    Article  Google Scholar 

Download references

Acknowledgements

This research is part of the project “Integration study of future law, ethics and intelligent technologies” (project No. 09.3.3-LMT-K-712-01-0173), executed at Vytautas Magnus University. The research is funded by the European Social Fund under Measure No. 09.3.3-LMT-K-712 “Improvement of the qualification of researchers through high-level R&D projects”.

Author information

Authors and Affiliations

  1. Lithuanian University of Health Sciences, A. Mickevičiaus g. 9, 44307, Kaunas, Lithuania

    Kristina Astromskė & Eimantas Peičius

  2. Vytautas Magnus University, K. Donelaičio g. 58, 44248, Kaunas, Lithuania

    Kristina Astromskė & Paulius Astromskis

Authors
  1. Kristina Astromskė
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eimantas Peičius
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paulius Astromskis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kristina Astromskė.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Astromskė, K., Peičius, E. & Astromskis, P. Ethical and legal challenges of informed consent applying artificial intelligence in medical diagnostic consultations. AI & Soc 36, 509–520 (2021). https://doi.org/10.1007/s00146-020-01008-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00146-020-01008-9

Keywords

Search

Navigation