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Self-Disclosure to AI: The Paradox of Trust and Vulnerability in Human-Machine Interactions

Zoe Zhiqiu Jiang

TL;DR

The paper investigates the paradox of trust and vulnerability in self-disclosure to AI, motivated by examples like Reben's BlabDroid. It combines psychological theories of self-disclosure (Social Penetration Theory and Communication Privacy Management) with philosophical lenses (posthumanism and phenomenology) to analyze how people disclose intimate information to machines and how privacy is managed. The work highlights risks such as false impressions of intimacy, data privacy concerns, and ethical implications of AI as confidants, including potential manipulation and emotional impacts. It argues for new ethical guardrails, accountability mechanisms, and continued interdisciplinary dialogue to responsibly integrate intimate AI interactions into society.

Abstract

In this paper, we explore the paradox of trust and vulnerability in human-machine interactions, inspired by Alexander Reben's BlabDroid project. This project used small, unassuming robots that actively engaged with people, successfully eliciting personal thoughts or secrets from individuals, often more effectively than human counterparts. This phenomenon raises intriguing questions about how trust and self-disclosure operate in interactions with machines, even in their simplest forms. We study the change of trust in technology through analyzing the psychological processes behind such encounters. The analysis applies theories like Social Penetration Theory and Communication Privacy Management Theory to understand the balance between perceived security and the risk of exposure when personal information and secrets are shared with machines or AI. Additionally, we draw on philosophical perspectives, such as posthumanism and phenomenology, to engage with broader questions about trust, privacy, and vulnerability in the digital age. Rapid incorporation of AI into our most private areas challenges us to rethink and redefine our ethical responsibilities.

Self-Disclosure to AI: The Paradox of Trust and Vulnerability in Human-Machine Interactions

TL;DR

The paper investigates the paradox of trust and vulnerability in self-disclosure to AI, motivated by examples like Reben's BlabDroid. It combines psychological theories of self-disclosure (Social Penetration Theory and Communication Privacy Management) with philosophical lenses (posthumanism and phenomenology) to analyze how people disclose intimate information to machines and how privacy is managed. The work highlights risks such as false impressions of intimacy, data privacy concerns, and ethical implications of AI as confidants, including potential manipulation and emotional impacts. It argues for new ethical guardrails, accountability mechanisms, and continued interdisciplinary dialogue to responsibly integrate intimate AI interactions into society.

Abstract

In this paper, we explore the paradox of trust and vulnerability in human-machine interactions, inspired by Alexander Reben's BlabDroid project. This project used small, unassuming robots that actively engaged with people, successfully eliciting personal thoughts or secrets from individuals, often more effectively than human counterparts. This phenomenon raises intriguing questions about how trust and self-disclosure operate in interactions with machines, even in their simplest forms. We study the change of trust in technology through analyzing the psychological processes behind such encounters. The analysis applies theories like Social Penetration Theory and Communication Privacy Management Theory to understand the balance between perceived security and the risk of exposure when personal information and secrets are shared with machines or AI. Additionally, we draw on philosophical perspectives, such as posthumanism and phenomenology, to engage with broader questions about trust, privacy, and vulnerability in the digital age. Rapid incorporation of AI into our most private areas challenges us to rethink and redefine our ethical responsibilities.
Paper Structure (9 sections, 2 figures)

This paper contains 9 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Trust in Human-Machine Interaction
  3. The Psychology of Confiding and Self-Disclosure
  4. Theoretical Perspectives on Self-Disclosure
  5. Vulnerability and Risk in Self-Disclosure
  6. Technological Philosophy and Ethics
  7. Philosophical Perspectives on AI and Trust
  8. Ethical Implications of AI as a Confidant
  9. Conclusion

Figures (2)

  • Figure 1: Alexander Reben's BlabDroid: Robots in Residence. Source: Reben, 2018 reben2018.
  • Figure 2: Relationships layers according to Social Penetration Theory. Source: Pecune, 2013 pecune2013toward.