The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care

Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-base...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Rubeis, Giovanni [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Artificial intelligence Big data Elderly care Ethics Gerontechnology 4p-medicine

Übergeordnetes Werk:	Enthalten in: Archives of gerontology and geriatrics - Amsterdam [u.a.] : Elsevier Science, 1982, 91
Übergeordnetes Werk:	volume:91

DOI / URN:	10.1016/j.archger.2020.104186

Katalog-ID:	ELV004789423

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allfields	10.1016/j.archger.2020.104186 doi (DE-627)ELV004789423 (ELSEVIER)S0167-4943(20)30180-1 DE-627 ger DE-627 rda eng 610 DE-600 44.68 bkl Rubeis, Giovanni verfasserin aut The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made. Artificial intelligence Big data Elderly care Ethics Gerontechnology 4p-medicine Enthalten in Archives of gerontology and geriatrics Amsterdam [u.a.] : Elsevier Science, 1982 91 Online-Ressource (DE-627)320639312 (DE-600)2024857-X (DE-576)256155429 1872-6976 nnns volume:91 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.68 Gerontologie Geriatrie AR 91
spelling	10.1016/j.archger.2020.104186 doi (DE-627)ELV004789423 (ELSEVIER)S0167-4943(20)30180-1 DE-627 ger DE-627 rda eng 610 DE-600 44.68 bkl Rubeis, Giovanni verfasserin aut The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made. Artificial intelligence Big data Elderly care Ethics Gerontechnology 4p-medicine Enthalten in Archives of gerontology and geriatrics Amsterdam [u.a.] : Elsevier Science, 1982 91 Online-Ressource (DE-627)320639312 (DE-600)2024857-X (DE-576)256155429 1872-6976 nnns volume:91 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.68 Gerontologie Geriatrie AR 91
allfields_unstemmed	10.1016/j.archger.2020.104186 doi (DE-627)ELV004789423 (ELSEVIER)S0167-4943(20)30180-1 DE-627 ger DE-627 rda eng 610 DE-600 44.68 bkl Rubeis, Giovanni verfasserin aut The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made. Artificial intelligence Big data Elderly care Ethics Gerontechnology 4p-medicine Enthalten in Archives of gerontology and geriatrics Amsterdam [u.a.] : Elsevier Science, 1982 91 Online-Ressource (DE-627)320639312 (DE-600)2024857-X (DE-576)256155429 1872-6976 nnns volume:91 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.68 Gerontologie Geriatrie AR 91
allfieldsGer	10.1016/j.archger.2020.104186 doi (DE-627)ELV004789423 (ELSEVIER)S0167-4943(20)30180-1 DE-627 ger DE-627 rda eng 610 DE-600 44.68 bkl Rubeis, Giovanni verfasserin aut The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made. Artificial intelligence Big data Elderly care Ethics Gerontechnology 4p-medicine Enthalten in Archives of gerontology and geriatrics Amsterdam [u.a.] : Elsevier Science, 1982 91 Online-Ressource (DE-627)320639312 (DE-600)2024857-X (DE-576)256155429 1872-6976 nnns volume:91 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.68 Gerontologie Geriatrie AR 91
allfieldsSound	10.1016/j.archger.2020.104186 doi (DE-627)ELV004789423 (ELSEVIER)S0167-4943(20)30180-1 DE-627 ger DE-627 rda eng 610 DE-600 44.68 bkl Rubeis, Giovanni verfasserin aut The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made. Artificial intelligence Big data Elderly care Ethics Gerontechnology 4p-medicine Enthalten in Archives of gerontology and geriatrics Amsterdam [u.a.] : Elsevier Science, 1982 91 Online-Ressource (DE-627)320639312 (DE-600)2024857-X (DE-576)256155429 1872-6976 nnns volume:91 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.68 Gerontologie Geriatrie AR 91
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author	Rubeis, Giovanni
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title	The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care
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title_sort	the disruptive power of artificial intelligence. ethical aspects of gerontechnology in elderly care
title_auth	The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care
abstract	Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made.
abstractGer	Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made.
abstract_unstemmed	Gerontechnology based on Artificial Intelligence (AI) is expected to fulfill the promise of the so-called 4p-medicine and enable a predictive, personalized, preventive, and participatory elderly care. Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. Whether AI-based gerontechnology will actualize the 4p-perspective or bring about the 4d-scenario depends on whether joint efforts of users, caregivers, care providers, engineers, and policy makers will be made.
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title_short	The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care
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Although empirical evidence shows positive health outcomes, commentators are concerned that AI-based gerontechnology could bring along the disruption of elderly care. A systematic conceptualization of these concerns is lacking. In this paper, such a conceptualization is suggested by analyzing the risks of AI in elderly care as “4d-risks”: the depersonalization of care through algorithm-based standardization, the discrimination of minority groups through generalization, the dehumanization of the care relationship through automatization, and the disciplination of users through monitoring and surveillance. Based on the 4d-model, strategies for a patient-centered AI in elderly care are outlined. 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The disruptive power of Artificial Intelligence. Ethical aspects of gerontechnology in elderly care

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