Abstract
The chapter combines emerging research on the digital twin, particularly on the natural language processing (NLP) technologies of AI and self-leadership. It applies the theories to one of the fastest-growing challenges of late postmodern humans: addiction. The chapter addresses the question of how language-based digital twins (LBDT) affect the self-leadership process of addiction redundancy. After reviewing the contemporary research literature, the chapter presents a case in which LBDT engages in understanding an appropriate approach to the self-leadership phenomenon and strategy. The case suggests that the addictive worldview and behavior is something more general for a late post-human society than a distinct health care problem. Self-leadership as a concept shifts the study of addiction toward strategic action. However, self-leadership research has yet to adopt an LBDT perspective in general and on phenomena such as addiction. Furthermore, the self-leadership methodology addresses a person's view on the level of strategies but does not combine them against various self-leadership challenges. The case highlights how LBDT can be associated with a user-designed, multiple-level, self-leadership approach in the context of addictive worldviews and behaviors. The limitations related to LBDT transparency, extension, and epistemology are considered.
Original language | English |
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Title of host publication | Digital Twin Technology for Better Health: A Healthcare Odyssey |
Editors | Manish Dixit, Kirti Raj Bhatele, Devanshu Tiwari |
Place of Publication | Taylor & Francis Group |
Publisher | CRC press |
Chapter | 8 |
Number of pages | 35 |
Publication status | Accepted/In press - 30 Jul 2024 |
MoEC publication type | A3 Part of a book or another research book |
Field of science
- Business and management
- Psychology
- Administrative science