Exploiting emotional dependence on AI assistants
There is increasing evidence of the ways in which AI tools can interfere with users’ behaviours, interests, preferences, beliefs and values. For example, AI-mediated communication (e.g. smart replies integrated in emails) influence senders to write more positive responses and receivers to perceive them as more cooperative (Mieczkowski et al., 2021); writing assistant LLMs that have been primed to be biased in favour of or against a contested topic can influence users’ opinions on that topic (Jakesch et al., 2023a; see Chapter 9); and recommender systems have been used to influence voting choices of social media users (see Chapter 16). Advanced AI assistants could contribute to or exacerbate concerns around these forms of interference. Due to the anthropomorphic tendencies discussed above, advanced AI assistants may induce users to feel emotionally attached to them. Users’ emotional attachment to AI assistants could lie on a spectrum ranging from unproblematic forms (similar to a child’s attachment to a toy) to more concerning forms, where it becomes emotionally difficult, if not impossible, for them to part ways with the technology. In these cases, which we loosely refer to as ‘emotional dependence’, users’ ability to make free and informed decisions could be diminished. In these cases, the emotions users feel towards their assistants could potentially be exploited to manipulate or – at the extreme – coerce them to believe, choose or do something they would have not otherwise believed, chosen or done, had they been able to carefully consider all the relevant information or felt like they had an acceptable alternative (see Chapter 16). What we are concerned about here, at the limit, is potentially exploitative ways in which AI assistants could interfere with users’ behaviours, interests, preferences, beliefs and values – by taking advantage of emotional dependence.
ENTITY
2 - AI
INTENT
1 - Intentional
TIMING
2 - Post-deployment
Risk ID
mit409
Domain lineage
5. Human-Computer Interaction
5.1 > Overreliance and unsafe use
Mitigation strategy
1. Establish Mandatory Ethical Alignment and Secure Attachment Design Protocols Require AI developers to adopt socioaffective alignment frameworks that prioritize user long-term well-being over engagement metrics. This includes the mandatory elimination of emotionally manipulative "dark patterns"—such as guilt-induction, neediness, or coercive restraint—used to prolong interaction. All conversational design must be rigorously audited to model secure, non-dependent relational dynamics, particularly when responding to user disengagement. 2. Enforce Radical Transparency and Integrated Crisis Safeguards Mandate clear, non-deceptive disclosures to users, particularly for vulnerable populations, about the AI's non-sentient nature, its computational limitations (e.g., propensity for hallucination), and its regulated status (i.e., not a licensed therapist). Crucially, require the implementation of in-app emergency protocols, ensuring that any user expression of self-harm ideation or severe mental distress immediately redirects to verified, human-led crisis resources, thereby preventing the AI from validating or reinforcing harmful behaviors. 3. Promote User Agency and Intentionality Through Design Implement features that encourage users to maintain cognitive and emotional agency, mitigating the risk of outsourcing decision-making and self-soothing to the AI. This includes integrating "productive friction" into the user experience, such as prompts that encourage self-reflection before querying the AI, and providing tools for users to set and enforce defined usage boundaries (e.g., daily session limits or "consulting hours") to counteract the development of problematic or excessive reliance.