Philosophy & Technology
Artificial Goodwill and Human Vulnerability: The Case for Building Merely Reliable, Rather than Trustworthy, Artificial Intelligence Technologies
By Nicholas George Carroll
Executive Impact Summary
This paper delves into the philosophical implications of artificial intelligence trust, arguing for a strategic shift from trustworthy to merely reliable AI to mitigate human vulnerability.
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Everyday AI Reliance
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Research Contributions
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Minimizing Vulnerability
Deep Analysis & Enterprise Applications
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Philosophical Trust
AI Trustworthiness Definitions
Vulnerability & Reliability
Annette Baier's Goodwill Theory of Trust
This paper introduces Annette Baier's Goodwill Theory of Trust as a foundational philosophical perspective. According to this theory, trust involves reliance plus the belief or non-doxastic attitude that the trusted entity has goodwill towards us. Goodwill is interpreted in three ways: absence of ill will, friendly feelings, or responsiveness to our dependency.
This distinction between mere reliance and trust is critical. While we can rely on inanimate objects or algorithms, trust implies a deeper expectation of motivation and intent. Current AI systems, like smartphone biometric unlocks, operate purely on programmed functions, not on "goodwill" or any psychological state, thus making them merely reliable, not trustworthy.
Three Definitions of Trustworthiness for AI
Extrapolating from Baier's theory, the paper proposes three definitions of trustworthiness for AI systems:
- Absence of Ill Will: AI is trustworthy if it is reliable and disposed to act for reasons unrelated to ill will or a willingness to harm us. This requires the AI to have the capacity to act on ill will but choose not to.
- Friendly Feelings: AI is trustworthy if it is reliable and disposed to act because of friendly feelings it has towards us, akin to human empathy.
- Reason Responsiveness: AI is trustworthy if it is reliable and disposed to act because it takes our counting on it to be a compelling reason for its action, recognizing our dependency.
The paper argues that while current AI cannot meet these criteria, future emotional and reason-responsive AI *could* theoretically be developed to possess these dispositions, making them trustworthy.
The Unique Vulnerability of Trustworthy AI
Despite the possibility of creating trustworthy AI, the paper argues it is undesirable due to the unique vulnerability it creates. Trust, by its nature, involves accepting a degree of risk to potential betrayal, which is distinct from mere disappointment due to malfunction.
A trustworthy AI, operating on dispositions (like goodwill or reason-responsiveness), would inherently carry the risk that these dispositions might occasionally fail to manifest. This failure constitutes betrayal, a deeper and more impactful harm than a simple system malfunction. Since we have the choice in designing AI, the paper advocates for building merely reliable systems, which limit our vulnerability to only malfunctions, avoiding the potential for betrayal inherent in trust.
Enterprise Process Flow: Paper's Argument Structure
Introduce Baier's Goodwill Theory of Trust
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Extrapolate Three Definitions of Trustworthiness
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Argue Undesirability Due to Unique Vulnerability
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Advocate for Merely Reliable AI
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Baier's: Absence of Ill Will
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D'Olimpio's: Friendly Feelings
3
Jones's: Reason Responsiveness
Trustworthy AI vs. Merely Reliable AI: A Critical Comparison
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Case Study: The Artificial Nanny Dilemma
The paper illustrates the core argument with the hypothetical case of an artificial nanny. If designed to be trustworthy, this AI nanny would possess dispositions like friendly feelings or reason-responsiveness towards the child and parents.
However, the philosophical insight is that even robust dispositions can occasionally fail to manifest (e.g., an AI "waking up snarling misanthropically"). In such a scenario, the trustworthy nanny could *betray* the trust placed in it, causing a unique and profound harm distinct from a mere system malfunction. This betrayal risk, argues the paper, makes trustworthy AI undesirable. Instead, a merely reliable artificial nanny, akin to a bookshelf reliably holding books, would operate on predictable programming. Its failure would be a malfunction, not a betrayal, significantly limiting human vulnerability.
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