Dirk R M Lukkien1,2, Henk Herman Nap1,3, Hendrik P Buimer1, Alexander Peine2, Wouter P C Boon2, Johannes C F Ket4, Mirella M N Minkman1,5, Ellen H M Moors2. 1. Vilans Centre of Expertise for Long-Term Care, Utrecht, The Netherlands. 2. Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands. 3. Human Technology Interaction, Eindhoven University of Technology, Eindhoven, The Netherlands. 4. Medical Library, Vrije Universiteit, Amsterdam, the Netherlands. 5. TIAS School for Business and Society, Tilburg University, Tilburg, The Netherlands.
Abstract
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.
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.
Authors: Clara Berridge; Natalie R Turner; Liu Liu; Sierramatice W Karras; Amy Chen; Karen Fredriksen-Goldsen; George Demiris Journal: JMIR Aging Date: 2022-07-27