FOLLOWUS
1. Clinical Center, the National Scientific Data Sharing Platform for Population and Health
2. Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China;
*,gjpumch@126.com
Published:07 June 2019,
Published Online:07 June 2019,
Received:05 May 2019,
Accepted:2019-5-31
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GUAN JIAN. Artificial Intelligence in Healthcare and Medicine: Promises, Ethical Challenges and Governance. [J]. Chinese medical sciences journal;chinese medical sciences journal, 2019, 34(2): 76-83.
GUAN JIAN. Artificial Intelligence in Healthcare and Medicine: Promises, Ethical Challenges and Governance. [J]. Chinese medical sciences journal;chinese medical sciences journal, 2019, 34(2): 76-83. DOI: 10.24920/003611.
人工智能正迅速地应用于包括医学在内的广泛领域
并被认为是一种可以在初级医疗保健中增强或替代专业医务人员的方法。然而
人工智能也同时引发了一些挑战和伦理问题的关注。本文作者从人工智能在医学和健康照护领域应用和前景、人工智能在一些前沿领域的特殊伦理关注、以及一些有参考价值的伦理治理体系三个方面进行了调查和探讨。尽管前沿人工智能在医疗领域的研究与开发具有很大潜力
但其应用所引发的伦理挑战对治理提出了新的要求。为确保医疗和医学领域的人工智能应用“值得信赖”
建议建立全球的伦理治理框架和体系以及医学领域前沿人工智能应用的专门指南。而其中最重要的方面
是应发挥政府在伦理监管中的作用和明确利益相关者在伦理治理体系中的责任。
Artificial intelligence (AI) is rapidly being applied to a wide range of fields
including medicine
and has been considered as an approach that may augment or substitute human professionals in primary healthcare. However
AI also raises several challenges and ethical concerns. In this article
the author investigates and discusses three aspects of AI in medicine and healthcare: the application and promises of AI
special ethical concerns pertaining to AI in some frontier fields
and suggestive ethical governance systems. Despite great potentials of frontier AI research and development in the field of medical care
the ethical challenges induced by its applications has put forward new requirements for governance. To ensure “trustworthy” AI applications in healthcare and medicine
the creation of an ethical global governance framework and system as well as special guidelines for frontier AI applications in medicine are suggested. The most important aspects include the roles of governments in ethical auditing and the responsibilities of stakeholders in the ethical governance system.
人工智能医学伦理学伦理治理机器学习脑-机交互类脑智能机器人“生物杂交”
artificial intelligencemedical ethicsethical governancemachine learningbrain-computer interactionbrain-inspired computerrobotsbiohybrids
Sniecinski I, Seghatchian J . Artificial intelligence: a joint narrative on potential use in pediatric stem and immune cell therapies and regenerative medicine. Transfus Apher Sci 2018; 57(3):422-4. doi: DOI:10.1016/j.transci.2018.05.004http://doi.org/10.1016/j.transci.2018.05.004https://linkinghub.elsevier.com/retrieve/pii/S1473050218301721https://linkinghub.elsevier.com/retrieve/pii/S1473050218301721
Tran BX, Vu GT, Ha GH , et al. Global evolution of research in artificial intelligence in health and medicine: a bibliometric study. J Clin Med 2019; 8(3):360. doi: DOI:10.3390/jcm8030360http://doi.org/10.3390/jcm8030360https://www.mdpi.com/2077-0383/8/3/360https://www.mdpi.com/2077-0383/8/3/360
Crigger E, Khoury C . Making policy on augmented intelligence in health care. AMA J Ethics 2019; 21(2):E188-91. doi: DOI:10.1001/amajethics.2019.188http://doi.org/10.1001/amajethics.2019.188https://journalofethics.ama-assn.org/article/making-policy-augmented-intelligence-health-care/2019-02https://journalofethics.ama-assn.org/article/making-policy-augmented-intelligence-health-care/2019-02
Modha DS. Introducing a brain-inspired computer TrueNorth’s neurons to revolutionize system architecture.http://www.research.ibm.com/articles/brain-chip.shtml . Accessed May 02, 2019. http://www.research.ibm.com/articles/brain-chip.shtmlhttp://www.research.ibm.com/articles/brain-chip.shtml
Dutton T. An overview of national AI strategies. . Published June 28, 2018; updated July 13, 2018; accessed April 28, 2019.https://toinformistoinfluence.com/2018/07/14/an-overview-of-national-ai-strategies https://toinformistoinfluence.com/2018/07/14/an-overview-of-national-ai-strategieshttps://toinformistoinfluence.com/2018/07/14/an-overview-of-national-ai-strategies
Reuters . France to spend 1.8 billion on AI to compete with U.S., China.http://scientists.trendolizer.com/2018/04/france-to-spend-18-billion-on-ai-to-compete-with-us-china.html . Published March 29, 2018; accessed April 19, 2019. http://scientists.trendolizer.com/2018/04/france-to-spend-18-billion-on-ai-to-compete-with-us-china.htmlhttp://scientists.trendolizer.com/2018/04/france-to-spend-18-billion-on-ai-to-compete-with-us-china.html
Bini SA . Artificial intelligence, machine learning, deep learning, and cognitive computing: what do these terms mean and how will they impact health care? J Arthroplasty 2018; 33(8):2358-61. doi: DOI:10.1016/j.arth.2018.02.067http://doi.org/10.1016/j.arth.2018.02.067https://linkinghub.elsevier.com/retrieve/pii/S0883540318302158https://linkinghub.elsevier.com/retrieve/pii/S0883540318302158
Kapoor R, Walters SP, Al-Aswad LA . The current state of artificial intelligence in ophthalmology. Surv Ophthalmol 2019; 64(2):233-40. doi: DOI:10.1016/j.survophthal.2018.09.002http://doi.org/10.1016/j.survophthal.2018.09.002https://linkinghub.elsevier.com/retrieve/pii/S0039625718300882https://linkinghub.elsevier.com/retrieve/pii/S0039625718300882
Williams AM, Liu Y, Regner KR , et al. Artificial intelligence, physiological genomics, and precision medicine. Physiol Genomics 2018; 50(4):237-43. doi: DOI:10.1152/physiolgenomics.00119.2017http://doi.org/10.1152/physiolgenomics.00119.2017http://www.physiology.org/doi/10.1152/physiolgenomics.00119.2017http://www.physiology.org/doi/10.1152/physiolgenomics.00119.2017
Parola C, Neumeier D, Reddy ST . Integrating high‐throughput screening and sequencing for monoclonal antibody discovery and engineering. Immunology 2018; 153(1):31-41. doi: DOI:10.1111/imm.12838http://doi.org/10.1111/imm.12838http://doi.wiley.com/10.1111/imm.12838http://doi.wiley.com/10.1111/imm.12838
Hammond R, Athanasiadou R, Curado S , et al. Predicting childhood obesity using electronic health records and publicly available data. PLoS One 2019; 14(4):e0215571. doi: DOI:10.1371/journal.pone.0215571http://doi.org/10.1371/journal.pone.0215571http://dx.plos.org/10.1371/journal.pone.0215571http://dx.plos.org/10.1371/journal.pone.0215571
Shen R, Martin A, Ni A , et al. Harnessing clinical sequencing data for survival stratification of patients with metastatic lung adenocarcinomas. JCO Precis Oncol 2019; 3:1-9. doi: DOI:10.1200/PO.18.00307http://doi.org/10.1200/PO.18.00307.
Retson TA, Besser AH, Sall S , et al. Machine learning and deep neural networks in thoracic and cardiovascular imaging. J Thorac Imaging 2019; 34(3):192-201. doi: DOI:10.1097/RTI.0000000000000385http://doi.org/10.1097/RTI.0000000000000385http://Insights.ovid.com/crossref?an=00005382-201905000-00008http://Insights.ovid.com/crossref?an=00005382-201905000-00008
Hamet P, Tremblay J . Artificial intelligence in medicine. Metabolism 2017; 69S:S36-S40. doi: DOI:10.1016/j.metabol.2017.01.011http://doi.org/10.1016/j.metabol.2017.01.011.
Ye JJ . Artificial intelligence for pathologists is not near-it is here: description of a prototype that can transform how we practice pathology tomorrow. Arch Pathol Lab Med 2015; 139(7):929-35. doi: DOI:10.5858/arpa.2014-0478-OAhttp://doi.org/10.5858/arpa.2014-0478-OAhttp://www.archivesofpathology.org/doi/10.5858/arpa.2014-0478-OAhttp://www.archivesofpathology.org/doi/10.5858/arpa.2014-0478-OA
Ho CWL, Soon D, Caals K , et al. Governance of automated image analysis and artificial intelligence analytics in healthcare. Clin Radiol 2019; 74(5):329-37. doi: DOI:10.1016/j.crad.2019.02.005http://doi.org/10.1016/j.crad.2019.02.005https://linkinghub.elsevier.com/retrieve/pii/S0009926019301151https://linkinghub.elsevier.com/retrieve/pii/S0009926019301151
Vandemeulebroucke T , Dierckx de Casterlé B, Gastmans C. The use of care robots in aged care: a systematic review of argument-based ethics literature. Arch Gerontol Geriatr 2018; 74:15-25. doi: DOI:10.1016/j.archger.2017.08.014http://doi.org/10.1016/j.archger.2017.08.014https://linkinghub.elsevier.com/retrieve/pii/S0167494317302790https://linkinghub.elsevier.com/retrieve/pii/S0167494317302790
Sullivan LS, Klein E, Brown T , et al. Keeping disability in mind: a case study in implantable brain-computer interface research. Sci Eng Ethics 2018; 24(2):479-504. doi: DOI:10.1007/s11948-017-9928-9http://doi.org/10.1007/s11948-017-9928-9.
Nam CS, Woo J, Bahn S . Severe motor disability affects functional cortical integration in the context of brain-computer interface (BCI) use. Ergonomics 2012; 55(5):581-91. doi: DOI:10.1080/00140139.2011.647095http://doi.org/10.1080/00140139.2011.647095https://www.tandfonline.com/doi/full/10.1080/00140139.2011.647095https://www.tandfonline.com/doi/full/10.1080/00140139.2011.647095
Tidoni E, Abu-Alqumsan M, Leonardis D , et al. Local and remote cooperation with virtual and robotic agents: a P300 BCI study in healthy and people living with spinal cord injury. IEEE Trans Neural Syst Rehabil Eng 2017; 25(9):1622-32. doi: DOI:10.1109/TNSRE.2016.2626391http://doi.org/10.1109/TNSRE.2016.2626391http://ieeexplore.ieee.org/document/7797151/http://ieeexplore.ieee.org/document/7797151/
Hochberg LR, Serruya MD, Friehs GM , et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 2006; 442(7099):164-171. doi: DOI:10.1038/nature04970http://doi.org/10.1038/nature04970 . DOI:10.1038/nature04970http://doi.org/10.1038/nature04970
Schettini F, Riccio A, Simione L , et al. Assistive device with conventional, alternative, and brain-computer interface inputs to enhance interaction with the environment for people with amyotrophic lateral sclerosis: a feasibility and usability study. Arch Phys Med Rehabil 2015; 96(3):S46-S53. doi: DOI:10.1016/j.apmr.2014.05.027http://doi.org/10.1016/j.apmr.2014.05.027https://linkinghub.elsevier.com/retrieve/pii/S0003999314010132https://linkinghub.elsevier.com/retrieve/pii/S0003999314010132
Hassabis D, Kumaran D, Summerfield C , et al. Neuroscience-inspired artificial intelligence. Neuron 2017; 95(2):245-58. doi: DOI:10.1016/j.neuron.2017.06.011http://doi.org/10.1016/j.neuron.2017.06.011https://linkinghub.elsevier.com/retrieve/pii/S0896627317305093https://linkinghub.elsevier.com/retrieve/pii/S0896627317305093
Boyle JM . Towards understanding the principle of double effect. Ethics 1980; 90:527-38. doi: DOI:10.1086/292183http://doi.org/10.1086/292183https://www.journals.uchicago.edu/doi/10.1086/292183https://www.journals.uchicago.edu/doi/10.1086/292183
Petrini C . Bioethics of clinical applications of stem cells. Int J Mol Sci 2017; 18(4):814. doi: DOI:10.3390/ijms18040814http://doi.org/10.3390/ijms18040814http://www.mdpi.com/1422-0067/18/4/814http://www.mdpi.com/1422-0067/18/4/814
Winfield AFT, Jirotka M . Ethical governance is essential to building trust in robotics and artificial intelligence systems. Philos Trans A Math Phys Eng Sci 2018; 376(2133):20180085. doi: DOI:10.1098/rsta.2018.0085http://doi.org/10.1098/rsta.2018.0085http://rsta.royalsocietypublishing.org/lookup/doi/10.1098/rsta.2018.0085http://rsta.royalsocietypublishing.org/lookup/doi/10.1098/rsta.2018.0085
Burwell S, Sample M, Racine E . Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics 2017; 18(1):60. doi: DOI:10.1186/s12910-017-0220-yhttp://doi.org/10.1186/s12910-017-0220-yhttps://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-017-0220-yhttps://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-017-0220-y
Beauchamp TL, Childress JF. Principles of biomedical ethics. 7th ed. New York, NY, USA: Oxford University Press; 2013.
Jonsen AR, Siegler M , Winslade WJ. Clinical Ethics. New York, NY, USA: McGraw-Hill; 2006.
Poggio T, Shelton CR . Learning in brains and machines. Spat Vis 2000; 13(2-3):287-96. DOI:10.1163/156856800741108http://doi.org/10.1163/156856800741108https://brill.com/view/journals/sv/13/2-3/article-p287_14.xmlhttps://brill.com/view/journals/sv/13/2-3/article-p287_14.xml
Vassanelli S, Mahmud M . Trends and challenges in neuroengineering: toward “Intelligent” neuroprostheses through brain—“Brain Inspired Systems” communication. Front Neurosci 2016; 10:438. doi:DOI:10.3389/fnins.2016.00438http://doi.org/10.3389/fnins.2016.00438.
Eiben AE, Kernbach S, Haasdijk E . Embodied artificial evolution artificial evolutionary systems in the 21st century. Evol Intell 2012; 5:261-72. doi: DOI:10.1007/s12065-012-0071-xhttp://doi.org/10.1007/s12065-012-0071-xhttp://link.springer.com/10.1007/s12065-012-0071-xhttp://link.springer.com/10.1007/s12065-012-0071-x
Ajrawi AS, Bialek H, Sarkar M , et al. Bi-directional channel modeling for implantable UHF-RFID transceivers in brain-computer interface applications. Future Generation Comput Syst 2018; 88:683-92. doi: DOI:10.1016/j.future.2018.03.036http://doi.org/10.1016/j.future.2018.03.036https://linkinghub.elsevier.com/retrieve/pii/S0167739X17327772https://linkinghub.elsevier.com/retrieve/pii/S0167739X17327772
Burwell S, Sample M, Racine E . Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics 2017; 18(1):60. doi: DOI:10.1186/s12910-017-0220-yhttp://doi.org/10.1186/s12910-017-0220-yhttps://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-017-0220-yhttps://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-017-0220-y
Yuste R, Goering S, Arcas BAY , et al. Four ethical priorities for neurotechnologies and AI. Nature 2017; 551:159-63. doi: DOI:10.1038/551159ahttp://doi.org/10.1038/551159a
Richman B . Health regulation for the digital age- correcting the mismatch. N Engl J Med 2018; 379:1694-169. doi: DOI:10.1056/NEJMp1806848http://doi.org/10.1056/NEJMp1806848http://www.nejm.org/doi/10.1056/NEJMp1806848http://www.nejm.org/doi/10.1056/NEJMp1806848
Stilgoe J, Owen R, Macnaghten P . Developing a framework for responsible innovation. Res Policy 2013; 42:1568-80. doi: DOI:10.1016/j.respol.2013.05.008http://doi.org/10.1016/j.respol.2013.05.008https://linkinghub.elsevier.com/retrieve/pii/S0048733313000930https://linkinghub.elsevier.com/retrieve/pii/S0048733313000930
Winfield AFT, Jirotka M . Ethical governance is essential to building trust in robotics and artificial intelligence systems. Philos Trans A Math Phys Eng Sci 2018; 376(2133):20180085. doi: DOI:10.1098/rsta.2018.0085http://doi.org/10.1098/rsta.2018.0085http://rsta.royalsocietypublishing.org/lookup/doi/10.1098/rsta.2018.0085http://rsta.royalsocietypublishing.org/lookup/doi/10.1098/rsta.2018.0085
Palmerini E. Azzarri F, Battaglia F , et al. D6.2—Guidelines on regulating robotics. RoboLaw project.http://www.robolaw.eu/RoboLaw_files/documents/robolaw_d6.2_guidelinesregulatingrobotics_20140922.pdf . Mordified September 22, 2014; accessed April 8, 2019. http://www.robolaw.eu/RoboLaw_files/documents/robolaw_d6.2_guidelinesregulatingrobotics_20140922.pdfhttp://www.robolaw.eu/RoboLaw_files/documents/robolaw_d6.2_guidelinesregulatingrobotics_20140922.pdf
British Standards Institution . BS 8611:2016 Robots and robotic devices. Guide to the ethical design and application of robots and robotic systems. London, UK: BSI; 2016.
The High-Level Expert Group on AI. Ethics guidelines for trustworthy AI. The European Commission. B-1049 Brussels. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai. Published April 8, 2019; accessed April 28, 2019. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-aihttps://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai
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