Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle
Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan,...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Borsci, Simone [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2022 |
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| Übergeordnetes Werk: |
Enthalten in: AI & society - London : Springer, 1987, 38(2022), 4 vom: 22. Jan., Seite 1465-1484 |
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| Übergeordnetes Werk: |
volume:38 ; year:2022 ; number:4 ; day:22 ; month:01 ; pages:1465-1484 |
| Links: |
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| DOI / URN: |
10.1007/s00146-021-01383-x |
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SPR05223326X |
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| 520 | |a Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. | ||
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10.1007/s00146-021-01383-x doi (DE-627)SPR05223326X (SPR)s00146-021-01383-x-e DE-627 ger DE-627 rakwb eng Borsci, Simone verfasserin (orcid)0000-0002-3591-3577 aut Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. Artificial intelligence (dpeaa)DE-He213 Human artificial intelligence interaction (dpeaa)DE-He213 AI Policies (dpeaa)DE-He213 Symbiosis of AI and Humans (dpeaa)DE-He213 Societal impact (dpeaa)DE-He213 Trust (dpeaa)DE-He213 Lehtola, Ville V. (orcid)0000-0001-8856-5919 aut Nex, Francesco (orcid)0000-0002-5712-6902 aut Yang, Michael Ying (orcid)0000-0002-0649-9987 aut Augustijn, Ellen-Wien (orcid)0000-0002-3389-7585 aut Bagheriye, Leila (orcid)0000-0003-1605-5850 aut Brune, Christoph (orcid)0000-0003-0145-5069 aut Kounadi, Ourania (orcid)0000-0002-5998-7343 aut Li, Jamy (orcid)0000-0003-2440-9719 aut Moreira, Joao (orcid)0000-0002-4547-7000 aut Van Der Nagel, Joanne (orcid)0000-0002-7641-9890 aut Veldkamp, Bernard (orcid)0000-0003-3543-2164 aut Le, Duc V. (orcid)0000-0001-7851-0869 aut Wang, Mingshu (orcid)0000-0001-5260-3143 aut Wijnhoven, Fons (orcid)0000-0001-8231-7535 aut Wolterink, Jelmer M. (orcid)0000-0001-5505-475X aut Zurita-Milla, Raul (orcid)0000-0002-1769-6310 aut Enthalten in AI & society London : Springer, 1987 38(2022), 4 vom: 22. Jan., Seite 1465-1484 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2022 number:4 day:22 month:01 pages:1465-1484 https://dx.doi.org/10.1007/s00146-021-01383-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2022 4 22 01 1465-1484 |
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10.1007/s00146-021-01383-x doi (DE-627)SPR05223326X (SPR)s00146-021-01383-x-e DE-627 ger DE-627 rakwb eng Borsci, Simone verfasserin (orcid)0000-0002-3591-3577 aut Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. Artificial intelligence (dpeaa)DE-He213 Human artificial intelligence interaction (dpeaa)DE-He213 AI Policies (dpeaa)DE-He213 Symbiosis of AI and Humans (dpeaa)DE-He213 Societal impact (dpeaa)DE-He213 Trust (dpeaa)DE-He213 Lehtola, Ville V. (orcid)0000-0001-8856-5919 aut Nex, Francesco (orcid)0000-0002-5712-6902 aut Yang, Michael Ying (orcid)0000-0002-0649-9987 aut Augustijn, Ellen-Wien (orcid)0000-0002-3389-7585 aut Bagheriye, Leila (orcid)0000-0003-1605-5850 aut Brune, Christoph (orcid)0000-0003-0145-5069 aut Kounadi, Ourania (orcid)0000-0002-5998-7343 aut Li, Jamy (orcid)0000-0003-2440-9719 aut Moreira, Joao (orcid)0000-0002-4547-7000 aut Van Der Nagel, Joanne (orcid)0000-0002-7641-9890 aut Veldkamp, Bernard (orcid)0000-0003-3543-2164 aut Le, Duc V. (orcid)0000-0001-7851-0869 aut Wang, Mingshu (orcid)0000-0001-5260-3143 aut Wijnhoven, Fons (orcid)0000-0001-8231-7535 aut Wolterink, Jelmer M. (orcid)0000-0001-5505-475X aut Zurita-Milla, Raul (orcid)0000-0002-1769-6310 aut Enthalten in AI & society London : Springer, 1987 38(2022), 4 vom: 22. Jan., Seite 1465-1484 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2022 number:4 day:22 month:01 pages:1465-1484 https://dx.doi.org/10.1007/s00146-021-01383-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2022 4 22 01 1465-1484 |
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10.1007/s00146-021-01383-x doi (DE-627)SPR05223326X (SPR)s00146-021-01383-x-e DE-627 ger DE-627 rakwb eng Borsci, Simone verfasserin (orcid)0000-0002-3591-3577 aut Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. Artificial intelligence (dpeaa)DE-He213 Human artificial intelligence interaction (dpeaa)DE-He213 AI Policies (dpeaa)DE-He213 Symbiosis of AI and Humans (dpeaa)DE-He213 Societal impact (dpeaa)DE-He213 Trust (dpeaa)DE-He213 Lehtola, Ville V. (orcid)0000-0001-8856-5919 aut Nex, Francesco (orcid)0000-0002-5712-6902 aut Yang, Michael Ying (orcid)0000-0002-0649-9987 aut Augustijn, Ellen-Wien (orcid)0000-0002-3389-7585 aut Bagheriye, Leila (orcid)0000-0003-1605-5850 aut Brune, Christoph (orcid)0000-0003-0145-5069 aut Kounadi, Ourania (orcid)0000-0002-5998-7343 aut Li, Jamy (orcid)0000-0003-2440-9719 aut Moreira, Joao (orcid)0000-0002-4547-7000 aut Van Der Nagel, Joanne (orcid)0000-0002-7641-9890 aut Veldkamp, Bernard (orcid)0000-0003-3543-2164 aut Le, Duc V. (orcid)0000-0001-7851-0869 aut Wang, Mingshu (orcid)0000-0001-5260-3143 aut Wijnhoven, Fons (orcid)0000-0001-8231-7535 aut Wolterink, Jelmer M. (orcid)0000-0001-5505-475X aut Zurita-Milla, Raul (orcid)0000-0002-1769-6310 aut Enthalten in AI & society London : Springer, 1987 38(2022), 4 vom: 22. Jan., Seite 1465-1484 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2022 number:4 day:22 month:01 pages:1465-1484 https://dx.doi.org/10.1007/s00146-021-01383-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2022 4 22 01 1465-1484 |
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10.1007/s00146-021-01383-x doi (DE-627)SPR05223326X (SPR)s00146-021-01383-x-e DE-627 ger DE-627 rakwb eng Borsci, Simone verfasserin (orcid)0000-0002-3591-3577 aut Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. Artificial intelligence (dpeaa)DE-He213 Human artificial intelligence interaction (dpeaa)DE-He213 AI Policies (dpeaa)DE-He213 Symbiosis of AI and Humans (dpeaa)DE-He213 Societal impact (dpeaa)DE-He213 Trust (dpeaa)DE-He213 Lehtola, Ville V. (orcid)0000-0001-8856-5919 aut Nex, Francesco (orcid)0000-0002-5712-6902 aut Yang, Michael Ying (orcid)0000-0002-0649-9987 aut Augustijn, Ellen-Wien (orcid)0000-0002-3389-7585 aut Bagheriye, Leila (orcid)0000-0003-1605-5850 aut Brune, Christoph (orcid)0000-0003-0145-5069 aut Kounadi, Ourania (orcid)0000-0002-5998-7343 aut Li, Jamy (orcid)0000-0003-2440-9719 aut Moreira, Joao (orcid)0000-0002-4547-7000 aut Van Der Nagel, Joanne (orcid)0000-0002-7641-9890 aut Veldkamp, Bernard (orcid)0000-0003-3543-2164 aut Le, Duc V. (orcid)0000-0001-7851-0869 aut Wang, Mingshu (orcid)0000-0001-5260-3143 aut Wijnhoven, Fons (orcid)0000-0001-8231-7535 aut Wolterink, Jelmer M. (orcid)0000-0001-5505-475X aut Zurita-Milla, Raul (orcid)0000-0002-1769-6310 aut Enthalten in AI & society London : Springer, 1987 38(2022), 4 vom: 22. Jan., Seite 1465-1484 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2022 number:4 day:22 month:01 pages:1465-1484 https://dx.doi.org/10.1007/s00146-021-01383-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2022 4 22 01 1465-1484 |
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10.1007/s00146-021-01383-x doi (DE-627)SPR05223326X (SPR)s00146-021-01383-x-e DE-627 ger DE-627 rakwb eng Borsci, Simone verfasserin (orcid)0000-0002-3591-3577 aut Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. Artificial intelligence (dpeaa)DE-He213 Human artificial intelligence interaction (dpeaa)DE-He213 AI Policies (dpeaa)DE-He213 Symbiosis of AI and Humans (dpeaa)DE-He213 Societal impact (dpeaa)DE-He213 Trust (dpeaa)DE-He213 Lehtola, Ville V. (orcid)0000-0001-8856-5919 aut Nex, Francesco (orcid)0000-0002-5712-6902 aut Yang, Michael Ying (orcid)0000-0002-0649-9987 aut Augustijn, Ellen-Wien (orcid)0000-0002-3389-7585 aut Bagheriye, Leila (orcid)0000-0003-1605-5850 aut Brune, Christoph (orcid)0000-0003-0145-5069 aut Kounadi, Ourania (orcid)0000-0002-5998-7343 aut Li, Jamy (orcid)0000-0003-2440-9719 aut Moreira, Joao (orcid)0000-0002-4547-7000 aut Van Der Nagel, Joanne (orcid)0000-0002-7641-9890 aut Veldkamp, Bernard (orcid)0000-0003-3543-2164 aut Le, Duc V. (orcid)0000-0001-7851-0869 aut Wang, Mingshu (orcid)0000-0001-5260-3143 aut Wijnhoven, Fons (orcid)0000-0001-8231-7535 aut Wolterink, Jelmer M. (orcid)0000-0001-5505-475X aut Zurita-Milla, Raul (orcid)0000-0002-1769-6310 aut Enthalten in AI & society London : Springer, 1987 38(2022), 4 vom: 22. Jan., Seite 1465-1484 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2022 number:4 day:22 month:01 pages:1465-1484 https://dx.doi.org/10.1007/s00146-021-01383-x kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 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_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2022 4 22 01 1465-1484 |
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Borsci, Simone @@aut@@ Lehtola, Ville V. @@aut@@ Nex, Francesco @@aut@@ Yang, Michael Ying @@aut@@ Augustijn, Ellen-Wien @@aut@@ Bagheriye, Leila @@aut@@ Brune, Christoph @@aut@@ Kounadi, Ourania @@aut@@ Li, Jamy @@aut@@ Moreira, Joao @@aut@@ Van Der Nagel, Joanne @@aut@@ Veldkamp, Bernard @@aut@@ Le, Duc V. @@aut@@ Wang, Mingshu @@aut@@ Wijnhoven, Fons @@aut@@ Wolterink, Jelmer M. @@aut@@ Zurita-Milla, Raul @@aut@@ |
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2022-01-22T00:00:00Z |
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253389690 |
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SPR05223326X |
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englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR05223326X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230714064738.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230714s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00146-021-01383-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR05223326X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00146-021-01383-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Borsci, Simone</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-3591-3577</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2022</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. 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| author |
Borsci, Simone |
| spellingShingle |
Borsci, Simone misc Artificial intelligence misc Human artificial intelligence interaction misc AI Policies misc Symbiosis of AI and Humans misc Societal impact misc Trust Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle |
| authorStr |
Borsci, Simone |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)253389690 |
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Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle Artificial intelligence (dpeaa)DE-He213 Human artificial intelligence interaction (dpeaa)DE-He213 AI Policies (dpeaa)DE-He213 Symbiosis of AI and Humans (dpeaa)DE-He213 Societal impact (dpeaa)DE-He213 Trust (dpeaa)DE-He213 |
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Borsci, Simone Lehtola, Ville V. Nex, Francesco Yang, Michael Ying Augustijn, Ellen-Wien Bagheriye, Leila Brune, Christoph Kounadi, Ourania Li, Jamy Moreira, Joao Van Der Nagel, Joanne Veldkamp, Bernard Le, Duc V. Wang, Mingshu Wijnhoven, Fons Wolterink, Jelmer M. Zurita-Milla, Raul |
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embedding artificial intelligence in society: looking beyond the eu ai master plan using the culture cycle |
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Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle |
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Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. © The Author(s) 2022 |
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Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. © The Author(s) 2022 |
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Abstract The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. © The Author(s) 2022 |
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| score |
7.3990755 |