Abstract
This paper undertakes a comparative legal study to analyze the challenges of privacy and personal data protection posed by Artificial Intelligence (“AI”) embedded in Robots, and to offer policy suggestions. After identifying the benefits from various AI usages and the risks posed by AI-related technologies, I then analyze legal frameworks and relevant discussions in the EU, USA, Canada, and Japan, and further consider the efforts of Privacy by Design (“PbD”) originating in Ontario, Canada. While various AI usages provide great convenience, many issues, including profiling, discriminatory decisions, lack of transparency, and impeding consent, have emerged. The unpredictability arising from the AI machine learning function poses further difficulties, which have only been partially addressed by legal frameworks in the aforementioned jurisdictions. However, analyzing the relevant discussions yielded several suggestions. The first priority is adopting PbD as the most flexible, soft-legal, and preferable approach toward AI-oriented issues. Implementing PbD will protect individual privacy and personal data without specific efforts, and achieve both the development of AI and the advancement of privacy and personal data protection. Technical measures that can adapt to an individual’s dynamic choices according to the “context” should be further developed. Furthermore, alternative technical measures, including those to solve the “algorithmic black box” or achieve differential privacy, warrant thorough examination. If AI surpasses human intelligence, a terminating function, such as a “kill switch” will be the last resort to preserve individual choice. Despite numerous difficulties, we must prepare for the coming AI-prevalent society by taking a flexible approach.
Similar content being viewed by others
Notes
Igo is defined as “a Japanese game for two persons, played on a board having 361 intersections on which black and white stones or counters are alternately placed, the object being to block off and capture the opponent's stones and control the larger part of the board” (http://www.dictionary.com/browse/igo).
“Artificial intelligence, through machine learning, needs a vast amount of data to learn: data in the realm of big data considerations. On the other direction, big data uses artificial intelligence techniques to extract value from big datasets” (European Data Protection Supervisor 2016, p. 4).
The report referenced a more detailed history in the Appendix of the AI 100 Report (Stone et al. 2016).
He announced the achievement in a tweet: see https://twitter.com/JeffBezos/status/809034847121350657.
The Nevada Revised Statutes Chapter 482A and the Nevada Administrative Code Chapter 482A include provisions for autonomous vehicles.
The EDPS states: “It is important to remark that the models created by machine learning will not be human understandable in most cases. The criteria a machine learning algorithm may find to classify input data, or the memory as weights in a neural network, will most probably lack expressivity as correct as they may be. This has a big impact when discussing algorithmic transparency” (European Data Protection Supervisor 2016, p. 19).
Pagallo cites Gianmarco V (2006) Euron Roboethics Roadmap. In: Proceedings Euron Roboethics Atelier, February 27 to March 3, Genoa, Italy.
1995 O.J. (L 281) 31–50.
2016 O.J. (L 119) 1–88.
GDPR Article 6 conditions the lawfulness of processing. Article 6(1)(e) provides that the processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller. Article 6(1)(f) provides that processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject that require the protection of personal data, in particular where the data subject is a child.
This concerns the so-called “sensitive data.” Article 9(1) prohibits processing of personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, and the processing of genetic data, biometric data for the purpose of uniquely identifying a natural person, data concerning health or data concerning a natural person's sex life or sexual orientation.
The basic privacy principles of national application are the: Collection Limitation Principle; Data Quality Principle; Purpose Specification Principle; Use Limitation Principle; Security Safeguards Principle; Openness Principle; Individual Participation Principle; Accountability Principle. Retrieved from https://www.oecd.org/internet/ieconomy/privacy-guidelines.htm.
The EDPS paper cites Frank Pasquale’s “The Black Box Society” (Harvard University Press 2015).
The Transportation Security Administration is a division of the Department of Homeland Security. Founded in 2001 in response to terrorism, the entity is responsible for handling traveler screening for all of passengers. See Criminal Justice Degree Hub.com, http://www.criminaljusticedegreehub.com/tsa/.
“Context” is thought to be important in the PbD (see Sect. 3.3.3).
“Covered entity” means a person that collects, creates, processes, retains, uses, or discloses personal data in or affecting interstate commerce in Section 4(b) of the Consumer Privacy Bill of Rights Act (White House 2015, p. 3).
See Kyllo v. United States, 533 U.S. 27 (2001).
It provides that the “the right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches and seizures, shall not be violated, and no warrants shall issue, but upon probable cause, supported by Oath or affirmation, and particularly describing the place to be searched, and the persons or things to be seized”.
Katz v. United States, 389 U.S. 347 (1967). In his concurring opinion, Justice Harlan stated that “[…] there is a twofold requirement, first that a person have exhibited an actual (subjective) expectation of privacy and, second, that the expectation be one that society is prepared to recognize as "reasonable".
United States v. Jones, 132 S.Ct. 945 (2012).
The overall laws and cases on privacy are organized in McIsaac et al. (2016).
Approximately 250 federal government institutions are listed in Schedule Three.
It also applies to personal information of employees of federally regulated works, undertakings, or businesses (organizations that are federally regulated, such as banks, airlines, and telecommunications companies).
The Canadian Standards Association originally developed a set of privacy protection principles that, in 1996, were approved as national standards by the Standards Council of Canada. The Model Code for the Protection of Personal Information was incorporated into PIPEDA. Meanwhile, the EU Directive gave impetus for privacy legislation in the private sector. Article 25 of the Directive prohibits member countries from transferring personal information to any non-member country that does not provide an adequate level of data protection.
Article 8 provides that everyone has the right to be secure against unreasonable search or seizure.
PbD is translated into 38 languages as of 2016.
The House of Representatives Cabinet Committee’s supplementary resolution on May 20, 2015 and the House of Councilors Cabinet Committee’s supplementary resolution on August 27, 2015 stated the importance of implementing PbD in the areas in which personal data are handled. Retrieved from https://www.oecd.org/internet/ieconomy/privacy-guidelines.htm.
Article 24 restricts data provision to a third party in a foreign country, which was introduced through the amendment in 2015.
The English translation can be retrieved from http://www.ppc.go.jp/files/pdf/Act_on_the_Protection_of_Personal_Infomration.pdf.
The author was solely responsible for English translation of the MIC Report.
Controlling the invasion by robots into private spheres, controlling the surveillance by robots in private spheres, controlling unauthorized access to robots, etc.
Controlling data collection, analysis, and use; implementing anonymization, encryption, and access control functions, etc.
Appropriate control of collection; analysis and use of biological information, including brain information, etc.
The author was solely responsible for English translation.
References
Article 29 Data Protection Working Party (2013) WP29 Opinion 3/2013 on purpose limitation. http://ec.europa.eu/justice/data-protection/article-29/documentation/opinion-recommendation/files/2013/wp203_en.pdf. Accessed 12 July 2017
Asimov I (2004) I, Robot, 2004th edn. Bantam Books, New York
Bekey G (2012) Current trends in robotics: technology and ethics. In: Lin P, Abney K, Bekey G (eds) Robot ethics: the ethical and social implications of robotics. MIT Press, Massachusetts, pp 17–34
Calo R (2012) Robots and Privacy. In: Lin P, Abney K, Bekey G (eds) Robot ethics: the ethical and social implications of robotics. MIT Press, Massachusetts, pp 187–202
Calo R, Froomkin M, Kerr I (eds) (2016) Robot Law. Edward Elgar Publishing, Massachusetts
Čapek K (2013) Rossum universal robots, English edn. Createspace, Seattle
Cavoukian A (2011a) Privacy by design: the 7 foundational principles. https://www.ipc.on.ca/wp-content/uploads/Resources/7foundationalprinciples.pdf. Accessed 12 July 2017
Cavoukian A (2011b) The 7 foundational principles: implementation and mapping of fair information practices. https://www.ipc.on.ca/wp-content/uploads/Resources/pbd-implement-7found-principles.pdf. Accessed 12 July 2017
Cavoukian A (2012a) Operationalizing privacy by design: a guide to implementing strong privacy practices. http://www.ontla.on.ca/library/repository/mon/26012/320221.pdf. Accessed 12 July 2017
Cavoukian A (2012b) Abandon zero-sum, simplistic either/or solutions—positive-sum is paramount: achieving public safety and privacy. http://www.ontla.on.ca/library/repository/mon/26011/320090.pdf. Accessed 12 July 2017
Cavoukian A (2013) Privacy by design and the promise of SmartData. In: Harvey I, Globe A, Tomko G, Borrett D, Kwan H, Hatzinakos D (eds) Smart data: privacy meets evolutionary robotics. Springer, New York, pp 1–9
Chowdhury G (2003) Natural language processing. Annu Rev Inf Sci Technol 37(1):51–89
Cooley TM (1888) A treatise on the law of torts or the wrongs which arise independent of contract, 2nd edn. Callaghan, Chicago
European Data Protection Supervisor (2016) Artificial intelligence, robotics, privacy and data protection: room document for the 38th data protection and privacy commissioners. https://secure.edps.europa.eu/EDPSWEB/webdav/site/mySite/shared/Documents/Cooperation/Conference_int/16-10-19_Marrakesh_AI_paper_EN.pdf. Accessed 12 July 2017
European Parliament (2017) the committee on legal affairs published a report with recommendations to the commission on civil law rules on robotics. http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//NONSGML+REPORT+A8-2017-0005+0+DOC+PDF+V0//EN. Accessed 12 July 2017
Executive Office of the President (2014) Big data: seizing opportunities, preserving values. https://obamawhitehouse.archives.gov/sites/default/files/docs/big_data_privacy_report_5.1.14_final_print.pdf. Accessed 12 July 2017
Executive Office of the President, National Science and Technology Council, Committee on Technology (2016) Preparing for the future of artificial intelligence. https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf. Accessed 12 July 2017
Federal Trade Commission (2000) Online profiling: a report to congress. https://www.ftc.gov/sites/default/files/documents/reports/online-profiling-federal-trade-commission-report-congress-part-2/onlineprofilingreportjune2000.pdf. Accessed 12 July 2017
Federal Trade Commission (2012a) Protecting Consumer privacy in an era of rapid change: recommendations for businesses and policymakers. https://www.ftc.gov/sites/default/files/documents/reports/federal-trade-commission-report-protecting-consumer-privacy-era-rapid-change-recommendations/120326privacyreport.pdf. Accessed 12 July 2017
Federal Trade Commission (2012b) Spokeo to Pay $800,000 to settle FTC charges company allegedly marketed information to employers and recruiters in violation of FCRA, June 12. https://www.ftc.gov/news-events/press-releases/2012/06/spokeo-pay-800000-settle-ftc-charges-company-allegedly-marketed. Accessed 12 July 2017
Federal Trade Commission (2015) Internet of things: privacy and security in a connected world. https://www.ftc.gov/system/files/documents/reports/federal-trade-commission-staff-report-november-2013-workshop-entitled-internet-things-privacy/150127iotrpt.pdf. Accessed 12 July 2017
Federal Trade Commission (2016) Big data a tool for inclusion or exclusion? Understanding the issues. https://www.ftc.gov/system/files/documents/reports/big-data-tool-inclusion-or-exclusion-understanding-issues/160106big-data-rpt.pdf. Accessed 7 Feb 2017
Heaton JB, Polson NG, Witte JH (2016) Deep learning in finance. https://pdfs.semanticscholar.org/9308/45234a42985b0f85215d30d7d0dfd9b65aab.pdf. Accessed 12 July 2017
Hildebrandt M, Koops BJ (2010) The challenges of ambient law and legal protection in the profiling era. The Mod Law Rev 73(3):428–460
House of Commons, Science and Technology Committee (2016) Robotics and artificial intelligence: fifth report of session 2016–17. https://www.publications.parliament.uk/pa/cm201617/cmselect/cmsctech/145/145.pdf. Accessed 12 July 2017
Institute for Information and Communications Policy of the Ministry of Internal Affairs and Communications (2016) AI network review meeting report: challenges for achieving wisdom network society (WINS). http://www.soumu.go.jp/menu_news/s-news/01iicp01_02000050.html. Accessed 12 July 2017 (in Japanese)
International Conference of Data Protection and Privacy Commissioners (2010) Resolution on privacy by design. The 32nd international conference of data protection and privacy commissioners. https://icdppc.org/wp-content/uploads/2015/02/32-Conference-Israel-resolution-on-Privacy-by-Design.pdf. Accessed 12 July 2017
Japanese Cabinet (2016) Japan revitalization strategy 2016. http://www.kantei.go.jp/jp/singi/keizaisaisei/pdf/2016_zentaihombun_en.pdf. Accessed 12 July 2017
Kroll JA, Huey J, Barocas S, Felten EW, Reindenberg JR, Robinson DG, Yu H (eds) (2016) Accountable Algorithms. Univ. of Pa. Law Rev, vol 165, p 633
Kurzweil R (2006) Singularity is near. Penguin Books, London
Kusuda Y (2005) A history of Japanese service robots. http://sts.kahaku.go.jp/diversity/document/system/pdf/016.pdf. Accessed 12 July 2017 (in Japanese)
McIsaac B, Shields R, Klein K (2016) The law of privacy in Canada, 2016th edn. Carswell, Toronto
Miller A (1971) The assault on privacy: computers, data banks, and dossiers. University of Michigan Press, Michigan
Mittelstadt BD, Allo P, Taddeo M, Wachter S, Floridi L (2016) The ethics of algorithms: mapping the debate. Big Data Soc July–December 1–21
Nissenbaum H (2004) Privacy as contextual integrity. Wash. Law Rev. 79(1):119–158
Office of the Privacy Commissioner of Canada (2016) Consent and privacy https://www.priv.gc.ca/media/1806/consent_201605_e.pdf. Accessed 12 July 2017
Office of the Under Secretary of Defense for Acquisition, Technology and Logistics (2016) Report of the defense science board summer study on autonomy. https://www.hsdl.org/?view&did=794641. Accessed 12 July 2017
Pagallo U (2011) Responsibility, jurisdiction, and the future of “privacy by design”. In: Dudley A, Braman J, Vincenti G (eds) Investigating cyber law and cyber ethics: issues, impacts and practices. IGI Global, Pennsylvania, pp 1–20
Pagallo U (2013) Robot in the cloud with privacy: a new threat to data protection? Comput Law Secur Rev 29:501–508
Pasquale F (2015) The black box society: the secret algorithm behind money and information. Harvard University Press, Massachusetts
Prosser W (1960) Privacy. Calif Law Rev 48:383–423
Russel S, Norvig P (eds) (2016) Artificial intelligence: a modern approach, 3rd edn. Pearson, Essex
Roth A, Dwork C (2014) The algorithmic foundations of differential privacy. Found Trends® Theor Comput Sci 9(3–4):211–407
Samuel AL (1959) Some studies in machine learning using the game of checkers. IBM J 3(3):211–229
Schönberger VM, Padova Y (2016) Regime change? Enabling big data through europe’s New data protection regulation. Columbia Sci Technol Law Rev 17:315
Shimpo F (2017) The eight principles of robot law. Curr Law (Tokinohourei) 2021:2–3 (in Japanese)
Tavan H (2015) Ethics and technology: controversies, questions, and strategies for ethical computing, 5th edn. Wiley, New Jersey
Tomko G (2013) SmartData: the need, the goal and the challenge. In: Harvey I, Globe A, Tomko G, Borrett D, Kwan H, Hatzinakos D (eds) Smart data: privacy meets evolutionary robotics. Springer, New York, pp 11–25
Turing AM (1950) Computing machinery and intelligence. Mind 59(236):433–460
Van Otterlo M (2013) A machine learning view on profiling. In: Hildebrandt M, de Vries K (eds) Privacy, due process and the computational turn—the philosophy of law meets the philosophy of technology. Routledge, Abingdon, pp 41–64
Waldman W (1985) Dictionary of robotics. Macmillan, London
Walzer M (1984) Spheres of justice: a defense of pluralism and equality. Basic Books, New York
Warren SD, Brandeis LD (1890) The right to privacy. Harv Law Rev 4:193–220
Westin AF (1967) Privacy and freedom. Atheneum, New York
White House (2015) Administration discussion draft consumer privacy bill of rights act. http://europrivacy.info/wp-content/uploads/2015/10/privacy-USA-cpbr-act-of-2015-discussion-draft.pdf. Accessed 12 July 2017
Judgments
Bundesverfassungsgericht [BVerfG], Dec. 15, 1983, 65 Entscheidungen des Bundesverfassungsgerichts [BVerfGE] 1
Katz v. United States, 389 U.S. 347 (1967)
Kyllo v. United States, 533 U.S. 27 (2001)
United States v. Jones, 132 S.Ct. 945 (2012)
Online news article and magazines
AFP (2015) Japan shows off disaster-response robots at android fair. The express tribune. https://tribune.com.pk/story/1002448/japan-shows-off-disaster-response-robots-at-android-fair/. Accessed 12 July 2017
BBC (2016) Google developing kill switch for AI. BBC News, Jun 8. http://www.bbc.com/news/technology-36472140. Accessed 12 July 2017
Cellan-Jones R (2014) Stephen Hawking warns artificial intelligence could end mankind. BBC News. http://www.bbc.com/news/technology-30290540. Accessed 12 July 2017
Crawford K (2016) Artificial intelligence’s white guy problem. The New York Times. https://www.nytimes.com/2016/06/26/opinion/sunday/artificial-intelligences-white-guy-problem.html?_r=2. Accessed 12 July 2017
IBM (2016) IBM’s Watson Helps Employees Tackle Cancer. PR Newswire. http://www.prnewswire.com/news-releases/ibms-watson-helps-employees-tackle-cancer-300341967.html. Accessed 12 July 2017
Kurzweil Accelerating Intelligence (2014) http://www.kurzweilai.net/new-uhf-rfid-technology-helps-robots-find-household-objects. Accessed 12 July 2017
NHK News Web (2016) The autonomous vehicle revolution: the threat of Google. http://www3.nhk.or.jp/news/business_tokushu/2016_1003.html. Accessed 12 July 2017 (in Japanese)
Nirmala J (for Japan Robot Association) (2015) Service robots are thriving in Japan. http://www.roboticstomorrow.com/article/2015/08/service-robots-are-thriving-in-japan/6598. Accessed 12 July 2017
Reisinger D (2016) Watch Amazon’s prime air complete its first drone delivery. fortune. http://fortune.com/2016/12/14/amazon-prime-air-delivery/. Accessed 12 July 2017
Shimpo F (2016) The right direction for analyzing the legal and system-related issues on robots and AI. http://www8.cao.go.jp/cstp/tyousakai/ai/1kai/siryo5-4.pdf. Accessed 12 July 2017 (in Japanese)
Takeshita R (2016) Igo professional player lost to AI made in Japan for the first time “Human beings do not notice hand”. Huffington Post. http://www.huffingtonpost.jp/2016/11/20/ai-beats-go-master_n_13105316.html. Accessed 12 July 2017
The Economist (2016) The Economist special report: artificial intelligence: ethics, Frankenstein’s paperclips. http://www.economist.com/news/special-report/21700762-techies-do-not-believe-artificial-intelligence-will-run-out-control-there-are. Accessed 12 July 2017
The Globe and Mail (2015) Canada risks losing its lead in artificial intelligence to Silicon Valley. http://www.theglobeandmail.com/technology/tech-news/canada-risks-losing-its-lead-in-artificial-intelligence-to-silicon-valley/article27810747/. Accessed 12 July 2017
Woo M (2014) Robots: can we trust them with our privacy?. BBC Future. http://www.bbc.com/future/story/20140605-the-greatest-threat-of-robots. Accessed 12 July 2017
Other online sources
Bernal-Castillero M (2013) Canada’s federal privacy laws, parliament of Canada. https://lop.parl.ca/Content/LOP/ResearchPublications/2007-44-e.htm. Accessed 12 July 2017
Bouchard S (2014) Differences between industrial and service robotics. http://blog.robotiq.com/bid/33839/10-Differences-Between-Industrial-and-Service-Robotics. Accessed 12 July 2017
Buttarelli G (2016) A smart approach: counteract the bias in artificial intelligence. https://edps.europa.eu/press-publications/press-news/blog/smart-approach-counteract-bias-artificial-intelligence_en. Accessed 12 July 2017
Cavoukian A (2014) So glad you didn’t say that! A response to Viktor Mayer-Schönberger. https://iapp.org/news/a/so-glad-you-didnt-say-that-a-response-to-viktor-mayer-schoenberger/. Accessed 12 July 2017
Cavoukian A (2015) Welcome to privacy and big data analytics—by design. http://www.ryerson.ca/content/dam/pbdi/PbD-Seminar-slides.pdf. Accessed Jul 12, 2017
Campbell M (2017) Mercedes-Benz autonomous vehicles due on the road between 2020 and 2025. Car Advice. http://www.caradvice.com.au/511552/mercedes-benz-autonomous-vehicles-due-on-the-road-between-2020-and-2025/. Accessed 12 July 2017
Deloitte (2015) Privacy by design: protecting privacy in the age of analytics. https://www2.deloitte.com/content/dam/Deloitte/za/Documents/risk/ZA_Privacybydesign_270515.pdf. Accessed 3 July 2017
Future of Life Institute (2015) Autonomous weapons: an open letter from AI and robotics researchers. http://futureoflife.org/open-letter-autonomous-weapons/. Accessed 3 July 2017
Honda (n.d.) High access survey robot. http://world.honda.com/High-AccessSurveyRobot/behindthescenes/. Accessed 3 July 2017
Kurzweil Accelerating Intelligence (2014) New UHF RFID technology helps robots find household objects Machine plays “hotter/colder” game while searching. http://www.kurzweilai.net/new-uhf-rfid-technology-helps-robots-find-household-objects. Accessed 12 July 2017
McCarthy J (2007) What is artificial intelligence?. http://www-formal.stanford.edu/jmc/whatisai/. Accessed 12 July 2017
MarketsandMarkets (2016) Artificial intelligence market by technology (deep learning, robotics, digital personal assistant, querying method, natural language processing, context aware processing), offering, end-user industry, and geography—global forecast to 2022. http://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html. Accessed 12 July 2017
Qatar Computing Research Institute. Projects (n.d.) http://qcri.com/our-research/social-innovation/social-innovation-projects. Accessed 7 Feb 2017
Ryerson University (2017) Privacy and big data institute. http://www.ryerson.ca/pbdi/privacy-by-design/resources/. Accessed 12 July 2017
State of Nevada, Department of Motor Vehicles (n.d.) Official website of the State of Nevada, Department of Motor Vehicles, Autonomous Vehicles. http://www.dmvnv.com/autonomous.htm. Accessed 12 July 2017
TechSci Research (2016) United States artificial intelligence market, by application, by region, by end user competition forecast and opportunities, 2011–2021. https://www.techsciresearch.com/report/united-states-artificial-intelligence-market-by-application-speech-recognition-image-recognition-etc-by-region-and-by-end-user-consumer-electronics-security-access-control-etc-competition-forecast-opportunities-2011-2021/676.html. Accessed 12 July 2017
The Government of Canada (2017) Credit reporting (consumer information). http://www.consumerinformation.ca/eic/site/032.nsf/eng/00038.html. Accessed 12 July 2017
The Robot Report (2017) Service robots for personal and private use. https://www.therobotreport.com/map/service-robots-for-personal-and-private-use. Accessed 12 July 2017
Workman D (2017) World’s top exports. http://www.worldstopexports.com/top-industrial-robots-exporters/. Accessed 12 July 2017
Video
Roques-Bonnet MC, Louveaux S, Brill J, Cannataci J, Ikonomou D, Wong SK, Wood S (2017) AI and GDPR: Concretely, what are the obligations and steps to take? In: CPDP 2017 (This article referred the speech made by Brill J.). https://www.youtube.com/watch?v=PWIeyNYQbm8. Accessed 12 July 2017
Acknowledgements
This research is supported by the research program “Human-Information Technology Ecosystem” within the Research Institute of Science and Technology for Society, Japan Science and Technology Agency.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ishii, K. Comparative legal study on privacy and personal data protection for robots equipped with artificial intelligence: looking at functional and technological aspects. AI & Soc 34, 509–533 (2019). https://doi.org/10.1007/s00146-017-0758-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00146-017-0758-8