Book contents
- AI in eHealth
- Cambridge Bioethics and Law
- AI in eHealth
- Copyright page
- Contents
- Contributors
- Preface
- Acronyms
- 1 Mapping the Digital Healthcare Revolution
- Part I Platforms, Apps and Digital Health
- Part II Trust and Design
- Part III Knowledge, Risk and Control
- 8 The Principle of Transparency in Medical Research
- 9 The Next Challenge for Data Protection Law
- 10 A Global Human Rights Approach to Medical Artificial Intelligence
- Part IV Balancing Regulation, Innovation and Ethics
- Index
- Cambridge Bioethics and Law
- References
9 - The Next Challenge for Data Protection Law
AI Revolution in Automated Scientific Research
from Part III - Knowledge, Risk and Control
Published online by Cambridge University Press: 08 September 2022
Book contents
- AI in eHealth
- Cambridge Bioethics and Law
- AI in eHealth
- Copyright page
- Contents
- Contributors
- Preface
- Acronyms
- 1 Mapping the Digital Healthcare Revolution
- Part I Platforms, Apps and Digital Health
- Part II Trust and Design
- Part III Knowledge, Risk and Control
- 8 The Principle of Transparency in Medical Research
- 9 The Next Challenge for Data Protection Law
- 10 A Global Human Rights Approach to Medical Artificial Intelligence
- Part IV Balancing Regulation, Innovation and Ethics
- Index
- Cambridge Bioethics and Law
- References
Summary
A considerable amount of literature has been published on autonomous vehicles, robotics in healthcare, and the danger of losing jobs and human control as a result of automation. However, there has been relatively little discussion about how AI might change scientific research. AI-assisted scientific research is already offering a significant boost to the process of scientific discovery. Not surprisingly, this radical change in scientific research will have significant consequences. First, if the research process becomes automated, it may be conducted by anyone, which puts citizen science in a new context. Just as developments in hardware and software made personal computers feasible for individual use, automated research may affect science in the future. Second, unlike researchers, AI and neural networks cannot explain their thinking yet. The fully automated research expands the ‘black box’, making oversight and ethical review problematic in systems opaque to outside scrutiny. Automated research raises many further questions about regulation, safety, funding and patentability. This chapter will focus on the issues connected with privacy and data protection, from the EU GDPR point of view.
- Type
- Chapter
- Information
- AI in eHealthHuman Autonomy, Data Governance and Privacy in Healthcare, pp. 251 - 276Publisher: Cambridge University PressPrint publication year: 2022
References
Act No. 78-17 of 6 January 1978 on Information Technology, Data Files and Civil Liberties, France, www.ssi.ens.fr/textes/a78-17-text.html, accessed 24 February 2021.Google Scholar
Article 29 Working Party, ‘Guidelines on Automated Individual Decision-Making and Profiling for the Purposes of Regulation 2016/679’, 2018 as last Revised and Adopted on 6 February 2018, https://ec.europa.eu/newsroom/article29/items/612053, accessed 24 February 2021.Google Scholar
C-311/18 Data Protection Commissioner V Facebook Ireland and Maximillian Schrems (2020).Google Scholar
Ceccaroni, L and others, ‘Opportunities and Risks for Citizen Science in the Age of Artificial Intelligence’ (2019) 4(1) Citizen Science: Theory and Practice 1–14.Google Scholar
Clarke, R, ‘Regulatory Alternatives for AI’ (2019) 35(4) Computer Law and Security Review.Google Scholar
Corrales Compagnucci, M and others, ‘Homomorphic Encryption: The “Holy Grail” for Big Data Analytics & Legal Compliance in the Pharmaceutical and Healthcare Sector?’ (2019) 3(4) European Pharmaceutical Law Review 144–55.CrossRefGoogle Scholar
Corrales Compagnucci, M, Big Data, Databases and ‘Ownership’ Rights in the Cloud’ (Springer 2020).Google Scholar
Corrales Compagnucci, M and others, ‘Lost on the High Seas Without a Safe Harbor or a Shield? Navigating Cross-Border Data Transfers in the Pharmaceutical Sector After Schrems II Invalidation of the EU-US Privacy Shield’ (2020) 4(3) European Pharmaceutical Law Review 153–60.CrossRefGoogle Scholar
Council of Europe, ‘The Protection of Individuals with Regard to Automatic Processing of Personal Data in the Context of Profiling’ Recommendation CM/Rec (2010)13 and explanatory memorandum, 23 November 2010, https://rm.coe.int/16807096c3, accessed 17 May 2021.Google Scholar
David, PA, ‘The Historical Origins of “Open Science”: An Essay on Patronage, Reputation and Common Agency Contracting in the Scientific Revolution’ (2008) 3(2) Capitalism and Society 5–14.Google Scholar
Deng, D and others, ‘Using Social Media for Collaborative Species Identification and Occurrence: Issues, Methods, and Tools’ in Goodchild, M, Pfoser, D and Sui, D (eds), Proceedings of the 1st ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information (2012), https://dl.acm.org/doi/10.1145/2442952.2442957, accessed 24 February 2021.Google Scholar
Esteva, A and others, ‘Deep Learning-Enabled Medical Computer Vision’ (2021) 4 npj Digital Medicine 5, https://doi.org/10.1038/s41746-020-00376-2, accessed 24 February 2021.CrossRefGoogle ScholarPubMed
EU GDPR, ‘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’ (General Data Protection Regulation), OJ 2016 L 119/1, https://eur-lex.europa.eu/eli/reg/2016/679/oj, accessed 24 February 2021.Google Scholar
European Commission, ‘High-Level Expert Group on Artificial Intelligence’, https://ec.europa.eu/digital-single-market/en/high-level-expert-group-artificial-intelligence, accessed 12 October 2020.Google Scholar
European Commission, Open Innovation, Open Science, Open to the World: A vision for Europe (Publications Office of the European Union 2016).Google Scholar
European Commission, ‘Open Innovation, Open Science, Open to the World – A Vision for Europe’ White Paper, 2016, https://op.europa.eu/en/publication-detail/-/publication/3213b335-1cbc-11e6-ba9a-01aa75ed71a1, accessed 24 February 2021.Google Scholar
European Commission, ‘Standard Contractual Clauses (SCC)’, https://ec.europa.eu/info/law/law-topic/data-protection/international-dimension-data-protection/standard-contractual-clauses-scc_en, accessed 17 May 2021.Google Scholar
European Parliament Committee on Legal Affairs, ‘Report with Recommendations to the Commission on Civil Law Rules on Robotics’ 27 January 2017, www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//NONSGML+REPORT+A8-2017-0005+0+DOC+PDF+V0//EN, accessed 17 May 2021.Google Scholar
European Parliamentary Research Service, ‘How the General Data Protection Regulation Changes the Rules for Scientific Research’ 2019, www.europarl.europa.eu/RegData/etudes/STUD/2019/634447/EPRS_STU(2019)634447_EN.pdf, accessed 17 May 2021.Google Scholar
Flach, P and others, ‘Abduction, Induction, and the Logic of Scientific Knowledge Development’ ECAI ’06 workshop on Abduction and Induction in AI and Scientific Modelling, 2006, www.cs.bris.ac.uk/Publications/pub_master.jsp?id=2000630, accessed 17 May 2021.Google Scholar
High-Level Expert Group on Artificial Intelligence, ‘Ethics Guidelines for Trustworthy AI’ 2018, https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html, accessed 24 February 2021.Google Scholar
Humerick, M, ‘Taking AI Personally: How the E.U. Must Learn to Balance the Interests of Personal Data Privacy & Artificial Intelligence’ (2018) 34(4) Santa Clara High Technology Law Journal 393, https://digitalcommons.law.scu.edu/chtlj/vol34/iss4/3, accessed 24 February 2021.Google Scholar
IMDB, ‘Ghost in the Machine’, www.imdb.com/title/tt0751131/, accessed 15 December 2020.Google Scholar
Information Commissioner’s Office, ‘Security Outcomes’, https://ico.org.uk/for-organisations/security-outcomes/, accessed 11 October 2020.Google Scholar
Irwin, Al, Citizen Science: A Study of People, Expertise, and Sustainable Development (Routledge 1995).Google Scholar
Joppa, LN, ‘The Case for Technology Investments in the Environment’ (2017) 552(7685) Nature 325–27.Google Scholar
Kitano, H, ‘Artificial Intelligence to Win the Nobel Prize and Beyond: Creating the Engine for Scientific Discovery’ (2016) 37(1) AI Magazine, www.rsc.org/globalassets/22-new-perspectives/discovery/digital-futures/rsc-digital-futures-report---digital.pdf, accessed 17 May 2021.Google Scholar
Lenat, DB and Brown, JS, ‘Why AM and EURISKO Appear to Work’ (1984) 23(3) Artificial Intelligence 236–40.CrossRefGoogle Scholar
Lindsay, RK and others, ‘DENDRAL: A Case Study of the First Expert System for Scientific Hypothesis Formation’ (1993) 61(2) Artificial Intelligence 209–61.CrossRefGoogle Scholar
MacDonald, EA, ‘Aurorasaurus: A Citizen Science Platform for Viewing and Reporting the Aurora’ (2015) 13(9) Space Weather 1–12.Google Scholar
Meszaros, J and Ho, C-H, ‘Big Data and Scientific Research: The Secondary Use of Personal Data Under the Research Exemption in the GDPR’ (2018) 59(4) Acta Juridica Hungarica 403–19.Google Scholar
Meszaros, J, Ho, C-H and Corrales Compagnucci, M, ‘Nudging Consent & the New Opt-Out System to the Processing of Health Data in England’ in Corrales Compagnucci, M and others (eds), Legal Tech and the New Sharing Economy (Springer 2020).Google Scholar
Minssen, T and others, ‘The EU-US Privacy Shield Regime for Cross-Border Transfers of Personal Data Under the GDPR: What are the Legal Challenges and How Might these Affect Cloud-Based Technologies, Big Data, and AI in the Medical Sector?’ (2020) 4(1) European Pharmaceutical Law Review 34–50.Google Scholar
OECD, Frascati Manual: Guidelines for Collecting and Reporting Data on Research and Experimental Development (OECD 2015).Google Scholar
OECD, ‘Making Open Science a Reality’ Technology and Industry Policy Papers, No. 25, OECD Publishing, Paris (2015), https://doi.org/10.1787/5jrs2f963zs1-en, accessed 24 February 2021.Google Scholar
Pagallo, U and others, ‘The Rise of Robotics & AI: Technological Advances & Normative Dilemmas’ in Corrales, M and others (eds), Robotics, AI and the Future of Law (Springer 2018) 1–13.Google Scholar
Royal Society of Chemistry, ‘Digital futures, a new frontier for science exploration and invention’ 2020, www.rsc.org/globalassets/22-new-perspectives/discovery/digital-futures/rsc-digital-futures-report---digital.pdf, accessed 17 May 2021.Google Scholar
Schüritz, R and others, ‘Capturing Value from Data: Revenue Models for Data-Driven Services’ Proceedings of the 50th Hawaii International Conference on System Sciences (2017). doi:10.24251/HICSS.2017.648CrossRefGoogle Scholar
Sparkes, A and others, ‘Towards Robot Scientists for Autonomous Scientific Discovery’ (2010) 2 (1) Automated Experimentation 1–11.CrossRefGoogle ScholarPubMed
Suman, AB and Pierce, R, ‘Challenges for Citizen Science and the EU Open Science Agenda Under the GDPR’ (2018) 4(3) European Data Protection Law Review 1–12.Google Scholar
Szalay, A and Gray, J, ‘2020 Computing: Science in an Exponential World’ (2006) 440(7083) Nature 413–14.CrossRefGoogle Scholar
The Future of Life Institute, ‘Asilomar AI principles’ developed in conjunction with the 2017 Asilomar Conference (2017), https://futureoflife.org/2017/08/11/ai-principles/, accessed 17 May 2021.Google Scholar
United States Code, 2012 Edition, Supplement 4, Title 15 – COMMERCE AND TRADE 15 U.S.C. 3724 – Crowdsourcing and citizen science (2016), www.govinfo.gov/app/details/USCODE-2016-title15/USCODE-2016-title15-chap63-sec3724, accessed 24 February 2021.Google Scholar
- 1
- Cited by