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Digital Doppelgängers, Human Relationships, and Practical Identity.

Cristina Voinea1, Sebastian Porsdam Mann2,3, Julian Savulescu4

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Summary
This summary is machine-generated.

Exploring relationships with Large Language Model (LLM)-based digital doppelgängers (DDs) reveals their potential impact on users' practical identity. Understanding these AI interactions is crucial for future development and deployment.

Keywords:
LLMsdigital doppelgängersgriefpractical identityrelationship

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Area of Science:

  • Human-Computer Interaction
  • Artificial Intelligence Ethics
  • Psychology of Technology

Background:

  • Digital doppelgängers (DDs) are AI conversational agents trained on user data to mimic personality.
  • Relationships significantly shape an individual's practical identity.
  • Relational DDs are designed to emulate known individuals, acting as artificial companions.

Purpose of the Study:

  • To examine the effects of relationships with LLM-based DDs on users' values, concerns, and interests.
  • To understand how DDs influence practical identity formation.
  • To provide considerations for the development and deployment of DDs.

Main Methods:

  • Conceptual analysis of LLM-based digital doppelgängers.
  • Exploration of the role of relationships in defining practical identity.
  • Distinction between task-specific and relational DDs.

Main Results:

  • Relationships are central to shaping practical identity.
  • Relational DDs are specifically designed to serve as artificial relational partners.
  • Interactions with DDs have the potential to alter users' practical identities.

Conclusions:

  • The development and deployment of DDs require careful consideration of their impact on user identity.
  • Further research is needed to understand the long-term psychological effects of human-DD relationships.
  • Ethical guidelines are essential for responsible AI companion development.