Abstract for World Physiotherapy Congress 2021Title Ethical Considerations of Using Machine Learning for Decision Support in Occupational Physical Therapy: a narrative literature study and ethical deliberation. Authors Marianne W. M. C. Six Dijkstra1,4,7 · Egbert Siebrand2 · Steven Dorrestijn2 · Etto L. Salomons3 ·Michiel F. Reneman4 · Frits G. J. Oosterveld1 · Remko Soer1,5 · Douglas P. Gross6 · Hendrik J. Bieleman1 Presenter and contactName: Marianne W. M. C. Six DijkstraEmail: w.m.c.sixdijkstra@saxion.nlAdres: School of Health, Saxion University of Applied Sciences/AGZ, M.H. Tromplaan 28, 7500 KB, Enschede, The NetherlandsTel: +31(0)612379329 1 School of Health, Saxion University of AppliedSciences, Enschede, The Netherlands2 Research Group Ethics & Technology, Saxion Universityof Applied Sciences, Enschede, The Netherlands3 School of Ambient Intelligence, Saxion Universityof Applied Sciences, Enschede, The Netherlands4 Department of Rehabilitation Medicine, University MedicalCenter Groningen, University of Groningen, Groningen,The Netherlands5 University Medical Center Groningen, Pain Centre,University of Groningen, Groningen, The Netherlands6 Department of Physical Therapy, University of Alberta,Edmonton, Canada7 University of Groningen, Groningen, The Netherlands Funding This study was funded by Netherlands Organisation for Scientific Research (NWO) (023.011.076) and Saxion University of Applied Sciences in The Netherlands. The funding source had no involvementin study design, data collection, analysis or interpretation, in the writing of the report, or the decision to submit the article for publication.Ethical approvalThis study is part of a PhD project entitled “Development of a Decision Support System – Artificial Intelligence advices for Sustainable Employability”. The Ethics Board at the University Medical Center Groningen in The Netherlands decided that formal approval of the study was not necessary because all workers were subjected to care as usual only.AbstractBackground Computer algorithms and Machine Learning (ML) will be integrated into clinical decision support within physical therapy. This will change the interaction between therapists and their clients, with unknown consequences.Purpose The aim of this study was to explore ethical considerations and potential consequences of using ML based decision support tools (DSTs). We used an example in the context of occupational physical therapy.Methods We conducted an ethical deliberation. This was supported by a narrative literature review of publications about ML and DSTs in occupational health and by an assessment of the potential impact of ML-DSTs according to frameworks from medical ethics and philosophy of technology. We introduce a hypothetical clinical scenario in occupational physical therapy to reflect on biomedical ethical principles: respect for autonomy, beneficence, non-maleficence and justice. The reflection was guided by the Product Impact Tool.
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Abstract Background: Healthcare professionals encounter ethical dilemmas and concerns in their practice. More research is needed to understand these ethical problems and to know how to educate professionals to respond to them. Research objective: To describe ethical dilemmas and concerns at work from the perspectives of Finnish and Dutch healthcare professionals studying at the master’s level. Research design: Exploratory, qualitative study that used the text of student online discussions of ethical dilemmas at work as data. Method: Participants’ online discussions were analyzed using inductive content analysis. Participants: The sample consisted of 49 students at master’s level enrolled in professional ethics courses at universities in Finland and the Netherlands. Ethical considerations: Permission for conducting the study was granted from both universities of applied sciences. All students provided their informed consent for the use of their assignments as research data. Findings: Participants described 51 problematic work situations. Among these, 16 were found to be ethical dilemmas, and the remaining were work issues with an ethical concern and did not meet criteria of a dilemma. The most common problems resulted from concerns about quality care, safety of healthcare professionals, patients’ rights, and working with too few staff and inadequate resources. Discussion: The results indicated that participants were concerned about providing quality of care and raised numerous questions about how to provide it in challenging situations. The results show that it was difficult for students to differentiate ethical dilemmas from other ethical work concerns. Conclusion: Online discussions among healthcare providers give them an opportunity to relate ethical principles to real ethical dilemmas and problems in their work as well as to critically analyze ethical issues. We found that discussions with descriptions of ethical dilemmas and concerns by health professionals provide important information and recommendations not only for education and practice but also for health policy.
The guidance offered here is intended to assist social workers in thinking through the specific ethical challenges that arise whilst practising during a pandemic or other type of crisis. In crisis conditions, people who need social work services, and social workers themselves, face increased and unusual risks. These challenging conditions are further compounded by scarce or reallocated governmental and social resources. While the ethical principles underpinning social work remain unchanged by crises, unique and evolving circumstances may demand that they be prioritised differently. A decision or action that might be regarded as ethically wrong in ‘normal’ times, may be judged to be right in a time of crisis. Examples include: prioritising individual and public health considerations by restricting people’s freedom of movement; not consulting people about treatment and services; or avoiding face-to-face meetings.
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Smart city technologies, including artificial intelligence and computer vision, promise to bring a higher quality of life and more efficiently managed cities. However, developers, designers, and professionals working in urban management have started to realize that implementing these technologies poses numerous ethical challenges. Policy papers now call for human and public values in tech development, ethics guidelines for trustworthy A.I., and cities for digital rights. In a democratic society, these technologies should be understandable for citizens (transparency) and open for scrutiny and critique (accountability). When implementing such public values in smart city technologies, professionals face numerous knowledge gaps. Public administrators find it difficult to translate abstract values like transparency into concrete specifications to design new services. In the private sector, developers and designers still lack a ‘design vocabulary’ and exemplary projects that can inspire them to respond to transparency and accountability demands. Finally, both the public and private sectors see a need to include the public in the development of smart city technologies but haven’t found the right methods. This proposal aims to help these professionals to develop an integrated, value-based and multi-stakeholder design approach for the ethical implementation of smart city technologies. It does so by setting up a research-through-design trajectory to develop a prototype for an ethical ‘scan car’, as a concrete and urgent example for the deployment of computer vision and algorithmic governance in public space. Three (practical) knowledge gaps will be addressed. With civil servants at municipalities, we will create methods enabling them to translate public values such as transparency into concrete specifications and evaluation criteria. With designers, we will explore methods and patterns to answer these value-based requirements. Finally, we will further develop methods to engage civil society in this processes.
