Machine hermeneutics, postphenomenology, and facial recognition technology
Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hongladarom, Soraj [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Ltd., part of Springer Nature 2020 |
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| Übergeordnetes Werk: |
Enthalten in: AI & society - London : Springer, 1987, 38(2020), 6 vom: 20. Feb., Seite 2151-2158 |
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| Übergeordnetes Werk: |
volume:38 ; year:2020 ; number:6 ; day:20 ; month:02 ; pages:2151-2158 |
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| DOI / URN: |
10.1007/s00146-020-00951-x |
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SPR05416124X |
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| 520 | |a Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. | ||
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10.1007/s00146-020-00951-x doi (DE-627)SPR05416124X (SPR)s00146-020-00951-x-e DE-627 ger DE-627 rakwb eng Hongladarom, Soraj verfasserin aut Machine hermeneutics, postphenomenology, and facial recognition technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. Machine hermeneutics (dpeaa)DE-He213 Material hermeneutics (dpeaa)DE-He213 Perception (dpeaa)DE-He213 Don Ihde (dpeaa)DE-He213 Artificial intelligence (dpeaa)DE-He213 Enthalten in AI & society London : Springer, 1987 38(2020), 6 vom: 20. Feb., Seite 2151-2158 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2020 number:6 day:20 month:02 pages:2151-2158 https://dx.doi.org/10.1007/s00146-020-00951-x lizenzpflichtig 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 2020 6 20 02 2151-2158 |
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10.1007/s00146-020-00951-x doi (DE-627)SPR05416124X (SPR)s00146-020-00951-x-e DE-627 ger DE-627 rakwb eng Hongladarom, Soraj verfasserin aut Machine hermeneutics, postphenomenology, and facial recognition technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. Machine hermeneutics (dpeaa)DE-He213 Material hermeneutics (dpeaa)DE-He213 Perception (dpeaa)DE-He213 Don Ihde (dpeaa)DE-He213 Artificial intelligence (dpeaa)DE-He213 Enthalten in AI & society London : Springer, 1987 38(2020), 6 vom: 20. Feb., Seite 2151-2158 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2020 number:6 day:20 month:02 pages:2151-2158 https://dx.doi.org/10.1007/s00146-020-00951-x lizenzpflichtig 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 2020 6 20 02 2151-2158 |
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10.1007/s00146-020-00951-x doi (DE-627)SPR05416124X (SPR)s00146-020-00951-x-e DE-627 ger DE-627 rakwb eng Hongladarom, Soraj verfasserin aut Machine hermeneutics, postphenomenology, and facial recognition technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. Machine hermeneutics (dpeaa)DE-He213 Material hermeneutics (dpeaa)DE-He213 Perception (dpeaa)DE-He213 Don Ihde (dpeaa)DE-He213 Artificial intelligence (dpeaa)DE-He213 Enthalten in AI & society London : Springer, 1987 38(2020), 6 vom: 20. Feb., Seite 2151-2158 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2020 number:6 day:20 month:02 pages:2151-2158 https://dx.doi.org/10.1007/s00146-020-00951-x lizenzpflichtig 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 2020 6 20 02 2151-2158 |
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10.1007/s00146-020-00951-x doi (DE-627)SPR05416124X (SPR)s00146-020-00951-x-e DE-627 ger DE-627 rakwb eng Hongladarom, Soraj verfasserin aut Machine hermeneutics, postphenomenology, and facial recognition technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. Machine hermeneutics (dpeaa)DE-He213 Material hermeneutics (dpeaa)DE-He213 Perception (dpeaa)DE-He213 Don Ihde (dpeaa)DE-He213 Artificial intelligence (dpeaa)DE-He213 Enthalten in AI & society London : Springer, 1987 38(2020), 6 vom: 20. Feb., Seite 2151-2158 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2020 number:6 day:20 month:02 pages:2151-2158 https://dx.doi.org/10.1007/s00146-020-00951-x lizenzpflichtig 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 2020 6 20 02 2151-2158 |
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10.1007/s00146-020-00951-x doi (DE-627)SPR05416124X (SPR)s00146-020-00951-x-e DE-627 ger DE-627 rakwb eng Hongladarom, Soraj verfasserin aut Machine hermeneutics, postphenomenology, and facial recognition technology 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2020 Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. Machine hermeneutics (dpeaa)DE-He213 Material hermeneutics (dpeaa)DE-He213 Perception (dpeaa)DE-He213 Don Ihde (dpeaa)DE-He213 Artificial intelligence (dpeaa)DE-He213 Enthalten in AI & society London : Springer, 1987 38(2020), 6 vom: 20. Feb., Seite 2151-2158 (DE-627)253389690 (DE-600)1458413-X 1435-5655 nnns volume:38 year:2020 number:6 day:20 month:02 pages:2151-2158 https://dx.doi.org/10.1007/s00146-020-00951-x lizenzpflichtig 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 2020 6 20 02 2151-2158 |
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machine hermeneutics, postphenomenology, and facial recognition technology |
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Machine hermeneutics, postphenomenology, and facial recognition technology |
| abstract |
Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. © Springer-Verlag London Ltd., part of Springer Nature 2020 |
| abstractGer |
Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. © Springer-Verlag London Ltd., part of Springer Nature 2020 |
| abstract_unstemmed |
Abstract I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. © Springer-Verlag London Ltd., part of Springer Nature 2020 |
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Machine hermeneutics, postphenomenology, and facial recognition technology |
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https://dx.doi.org/10.1007/s00146-020-00951-x |
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10.1007/s00146-020-00951-x |
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|
| score |
7.400099 |