Taxonomy of Generative AI Applications for Risk Assessment

The superior functionality and versatility of generative AI have raised expectations for the improvement of human society and concerns about the ethical and social risks associated with the use of generative AI. Many previous studies have presented risk issues as concerns associated with the use of...

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Veröffentlicht in:2024 IEEE/ACM 3rd International Conference on AI Engineering – Software Engineering for AI (CAIN) S. 288 - 289
Hauptverfasser: Tanaka, Hiroshi, Ide, Masaru, Yajima, Jun, Onodera, Sachiko, Munakata, Kazuki, Yoshioka, Nobukazu
Format: Tagungsbericht
Sprache:Englisch
Japanisch
Veröffentlicht: ACM 14.04.2024
Schlagworte:
Atmospheric modeling
Computational modeling
Ethics
Generative AI
language models
responsible AI
responsible innovation
risk assessment
Risk management
Surveys
Taxonomy
technology risks
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Abstract The superior functionality and versatility of generative AI have raised expectations for the improvement of human society and concerns about the ethical and social risks associated with the use of generative AI. Many previous studies have presented risk issues as concerns associated with the use of generative AI, but since most of these concerns are from the user's perspective, they are difficult to lead to specific countermeasures. In this study, the risk issues presented by the previous studies were broken down into more detailed elements, and risk factors and impacts were identified. In this way, we presented information that leads to countermeasure proposals for generative AI risks.CCS CONCEPTS* General and reference→Evaluation; Surveys and overviews, * Human-centered computing→HCI theory, concepts and models; * Social and professional topics→Computing / technology policy.
AbstractList The superior functionality and versatility of generative AI have raised expectations for the improvement of human society and concerns about the ethical and social risks associated with the use of generative AI. Many previous studies have presented risk issues as concerns associated with the use of generative AI, but since most of these concerns are from the user's perspective, they are difficult to lead to specific countermeasures. In this study, the risk issues presented by the previous studies were broken down into more detailed elements, and risk factors and impacts were identified. In this way, we presented information that leads to countermeasure proposals for generative AI risks.CCS CONCEPTS* General and reference→Evaluation; Surveys and overviews, * Human-centered computing→HCI theory, concepts and models; * Social and professional topics→Computing / technology policy.
Author Ide, Masaru
Yoshioka, Nobukazu
Onodera, Sachiko
Yajima, Jun
Tanaka, Hiroshi
Munakata, Kazuki
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  surname: Tanaka
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  givenname: Masaru
  surname: Ide
  fullname: Ide, Masaru
  email: masaru.ide@fujitsu.com
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  givenname: Jun
  surname: Yajima
  fullname: Yajima, Jun
  email: jyajima@fujitsu.com
  organization: Fujitsu Limited,Kawasaki,Japan
– sequence: 4
  givenname: Sachiko
  surname: Onodera
  fullname: Onodera, Sachiko
  email: sachiko@fujitsu.com
  organization: Fujitsu Limited,Kawasaki,Japan
– sequence: 5
  givenname: Kazuki
  surname: Munakata
  fullname: Munakata, Kazuki
  email: munakata.kazuki@fujitsu.com
  organization: Fujitsu Limited,Kawasaki,Japan
– sequence: 6
  givenname: Nobukazu
  surname: Yoshioka
  fullname: Yoshioka, Nobukazu
  email: nobukazuy@acm.org
  organization: Waseda University,Tokyo,Japan
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SubjectTerms Atmospheric modeling
Computational modeling
Ethics
Generative AI
language models
responsible AI
responsible innovation
risk assessment
Risk management
Surveys
Taxonomy
technology risks
Title Taxonomy of Generative AI Applications for Risk Assessment
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