g. Navigating AI Integration in Socio-Technical Systems by Advancing Accountability in ICT PlatformsA New Paradigm for Interplay of Accountability and Interpretation

Effective change management in complex, relational service or enter- prise environments, those involving multiple agencies and diverse cultural con- texts, requires a higher-level framework based on cybernetics second-order con- cepts such as principles, objectives, roles, responsibilities, intentions, and aware- ness. These concepts are crucial for ensuring accountability in human actions, far beyond the basic functional data typically handled by institutional ICT platforms. Current ICT platforms, without an updated information paradigm, are inadequate for addressing accountability questions in complex socio-technical settings— whether analysed by humans or Trained Generative AI modules; eventually equipped with the necessary hermeneutic interpretation abilities, unavailable as yet however. In 2020, Martin and Wilson introduced a new, suitable Information Communications (IC) paradigm designed for ICT platforms. This paper revisits IC concepts and utilizes a conversation model to explore the connection between AI and accountability, presenting the resulting framework for second-order gov- ernance. Although the need for a shift in the formal ICT paradigm is clear, the momentum for such change has yet to fully develop. However, we foresee that the growing application of Trained Generative AI to institutional ICT data will drive a significant shift toward this new paradigm. With access to second-order data and future, enhanced hermeneutic abilities, or with appropriate human ap- proaches at using Trained Generative AI system that influence and bias AI result with human interpretation, AI-generated narratives could become not only plau- sible but also credible and reliable. In collaboration with colleagues, we are cur- rently developing a prototype conversational platform that enables second-order communications within information systems in ICT.

Publication Details

Journal
Journal of the Association for Information Systems
Published
2024-10-11
Primary Topic
Magnetic Field Sensors Techniques
Type
article
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article

g. Navigating AI Integration in Socio-Technical Systems by Advancing Accountability in ICT PlatformsA New Paradigm for Interplay of Accountability and Interpretation

Journal of the Association for Information Systems
Magnetic Field Sensors Techniques
article

g. Navigating AI Integration in Socio-Technical Systems by Advancing Accountability in ICT PlatformsA New Paradigm for Interplay of Accountability and Interpretation

article en

Abstract

Effective change management in complex, relational service or enter- prise environments, those involving multiple agencies and diverse cultural con- texts, requires a higher-level framework based on cybernetics second-order con- cepts such as principles, objectives, roles, responsibilities, intentions, and aware- ness. These concepts are crucial for ensuring accountability in human actions, far beyond the basic functional data typically handled by institutional ICT platforms. Current ICT platforms, without an updated information paradigm, are inadequate for addressing accountability questions in complex socio-technical settings— whether analysed by humans or Trained Generative AI modules; eventually equipped with the necessary hermeneutic interpretation abilities, unavailable as yet however. In 2020, Martin and Wilson introduced a new, suitable Information Communications (IC) paradigm designed for ICT platforms. This paper revisits IC concepts and utilizes a conversation model to explore the connection between AI and accountability, presenting the resulting framework for second-order gov- ernance. Although the need for a shift in the formal ICT paradigm is clear, the momentum for such change has yet to fully develop. However, we foresee that the growing application of Trained Generative AI to institutional ICT data will drive a significant shift toward this new paradigm. With access to second-order data and future, enhanced hermeneutic abilities, or with appropriate human ap- proaches at using Trained Generative AI system that influence and bias AI result with human interpretation, AI-generated narratives could become not only plau- sible but also credible and reliable. In collaboration with colleagues, we are cur- rently developing a prototype conversational platform that enables second-order communications within information systems in ICT.

Journal of the Association for Information Systems
Openalex Percentile: Top 58%
Magnetic Field Sensors Techniques
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