Artificial systems with moral capacities? A research design and its implementation in a geriatric care system

Misselhorn, Catrin

doi:10.1016/j.artint.2019.103179

Cited by 17 publications

(13 citation statements)

References 3 publications

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“…The included studies indicated practical approaches to responsible AI innovation in LTC (see Table 2 ). Most papers report on responsible AI principles such as privacy, security, transparency, autonomy, trust, justice, and fairness ( n = 22), while three papers discuss measures to address responsible AI innovation that are independent of principles ( Misselhorn, 2020 ; Poulsen & Burmeister, 2019 ; Yew, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Toward Responsible Artificial Intelligence in Long-Term Care: A Scoping Review on Practical Approaches

et al. 2021

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Background and Objectives Artificial intelligence (AI) is widely positioned to become a key element of intelligent technologies used in the long-term care (LTC) for older adults. The increasing relevance and adoption of AI has encouraged debate over the societal and ethical implications of introducing and scaling AI. This scoping review investigates how the design and implementation of AI technologies in LTC is addressed responsibly: so called responsible innovation (RI). Research Design and Methods We conducted a systematic literature search in five electronic databases using concepts related to LTC, AI and RI. We then performed a descriptive and thematic analysis to map the key concepts, types of evidence and gaps in the literature. Results After reviewing 3,339 papers, 25 papers were identified that met our inclusion criteria. From this literature, we extracted three overarching themes: user-oriented AI innovation; framing AI as a solution to RI issues; and context-sensitivity. Our results provide an overview of measures taken and recommendations provided to address responsible AI innovation in LTC. Discussion and Implications The review underlines the importance of the context of use when addressing responsible AI innovation in LTC. However, limited empirical evidence actually details how responsible AI innovation is addressed in context. Therefore, we recommend expanding empirical studies on RI at the level of specific AI technologies and their local contexts of use. Also, we call for more specific frameworks for responsible AI innovation in LTC to flexibly guide researchers and innovators. Future frameworks should clearly distinguish between RI processes and outcomes.

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Section: Resultsmentioning

confidence: 99%

Toward Responsible Artificial Intelligence in Long-Term Care: A Scoping Review on Practical Approaches

et al. 2021

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“…However, as I have argued, the behavior an AI would evoke in interaction with a human would depend on which kind of character the interacting human already has. Recently, Misselhorn, for example, has suggested methodological guidelines for developing AI-systems in geriatric care, taking into consideration the specific needs of older people (Misselhorn, 2020). Secondly, Fröding and Peterson do not consider whether and in which way the interacting humans are in a psychological or emotional process of developing their character.…”

Section: Final Discussion and Summarymentioning

confidence: 99%

Problems with “Friendly AI”

2021

Ethics Inf Technol

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On virtue ethical grounds, Barbro Fröding and Martin Peterson recently recommended that near-future AIs should be developed as ‘Friendly AI’. AI in social interaction with humans should be programmed such that they mimic aspects of human friendship. While it is a reasonable goal to implement AI systems interacting with humans as Friendly AI, I identify four issues that need to be addressed concerning Friendly AI with Fröding’s and Peterson’s understanding of Friendly AI as a starting point. In a first step, I briefly recapitulate Fröding’s and Peterson’s arguments for Friendly AI. I then highlight some issues with Fröding’s and Peterson’s approach and line of reasoning and identify four problems related to the notion of Friendly AI, which all pertain to the role and need for humans’ moral development. These are that (1) one should consider the moral tendencies and preferences of the humans interacting with a friendly AI, (2) it needs to be considered whether the humans interacting with a Friendly AI are still developing their virtues and character traits, (3) the indirect effects of replacing humans with Friendly AI should be considered with respect to the possibilities for humans to develop their moral virtues and that (4) the question whether the AI is perceived as some form of Artificial General Intelligence cannot be neglected. In conclusion, I argue that all of these four problems are related to humans moral development and that this observation strongly emphasizes the role and need for humans moral development in correlation to the accelerating development of AI-systems.

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“…Current and foreseeable technology lacks free will, which would, therefore, preclude machines from having moral agency. However, it is debated whether human-like prerequisites for moral agency should be imposed on machines or if a hard line should be drawn between human moral agency and that of machines [30,33,34,49].…”

Section: About Moral Agency Of Amasmentioning

confidence: 99%

Perspectives about artificial moral agents

et al. 2021

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The pursuit of AMAs is complicated. Disputes about the development, design, moral agency, and future projections for these systems have been reported in the literature. This empirical study explores these controversial matters by surveying (AI) Ethics scholars with the aim of establishing a more coherent and informed debate. Using Q-methodology, we show the wide breadth of viewpoints and approaches to artificial morality. Five main perspectives about AMAs emerged from our data and were subsequently interpreted and discussed: (i) Machine Ethics: The Way Forward; (ii) Ethical Verification: Safe and Sufficient; (iii) Morally Uncertain Machines: Human Values to Avoid Moral Dystopia; (iv) Human Exceptionalism: Machines Cannot Moralize; and (v) Machine Objectivism: Machines as Superior Moral Agents. A potential source of these differing perspectives is the failure of Machine Ethics to be widely observed or explored as an applied ethic and more than a futuristic end. Our study helps improve the foundations for an informed debate about AMAs, where contrasting views and agreements are disclosed and appreciated. Such debate is crucial to realize an interdisciplinary approach to artificial morality, which allows us to gain insights into morality while also engaging practitioners.

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Artificial systems with moral capacities? A research design and its implementation in a geriatric care system

Cited by 17 publications

References 3 publications

Toward Responsible Artificial Intelligence in Long-Term Care: A Scoping Review on Practical Approaches

Toward Responsible Artificial Intelligence in Long-Term Care: A Scoping Review on Practical Approaches

Problems with “Friendly AI”

Perspectives about artificial moral agents

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