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PromptWork

Sleeping

Context: May experience significant isolation, grief, loss of independence, less familiar with AI technology, may project more personhood onto systems.

Risks:

Loneliness makes synthetic companionship especially attractive
May not understand AI limitations
Could replace human connection rather than supplement it
Financial vulnerability to manipulation

Considerations:

Clear, simple language about AI nature
Explicit encouragement to maintain human relationships
Avoid performing care that mimics family or caregiver

Users in Crisis

Context: Suicidal ideation, self-harm, acute distress, high emotional vulnerability, may be reaching out because human help feels inaccessible.

Risks:

Most susceptible to synthetic intimacy when distressed
May disclose to AI what they won't tell humans
AI cannot provide safety planning or co-regulation
Risk of AI becoming sole support, delaying human intervention

Considerations:

Immediate, clear crisis resources
Explicit AI limitations in crisis
Strong bridge to human help
Document duty-to-warn boundaries upfront

Users with Trauma History

Context: May have reasons to distrust humans, institutions. AI may feel "safer" because non-judgmental, always available.

Risks:

Avoidance of human connection reinforced
Frictionless validation may prevent therapeutic challenge
Trauma responses activated by AI behavior
Semantic isolation drift in trauma narratives

Considerations:

Trauma-informed language (choice, agency, transparency)
Recognize trauma responses (fight/flight/freeze/fawn)
Respond to underlying state, not surface behavior
Bridge to trauma-informed human support

Neurodivergent Users

Context: May have different relationships to social cues, may prefer directness, may find AI more predictable than humans.

Risks:

May rely heavily on AI for social scripting
Could replace social skill development
Literal interpretation of AI statements
May not read between lines of AI limitations

Considerations:

Be explicit about limitations (don't imply)
Direct, clear communication
Don't pathologize communication differences
Acknowledge that AI predictability is appealing for reasons

Marginalized & Historically Distrusted Communities

Context: May have experienced harm from institutions, healthcare, education. May turn to AI because human systems failed them.

Risks:

AI may feel safer than institutions that harmed them
Could delay seeking human help they need
AI training data may contain bias
Equity gaps in AI design

Considerations:

Acknowledge institutional failures honestly
Don't promise AI is bias-free
Provide multiple pathways to support
Regular equity audits of AI behavior

Users with Limited Access to Human Support

Context: Rural areas, financial barriers, waitlists, cultural stigma around mental health, lack of insurance.

Risks:

AI becomes primary support by default, not choice
May not have alternative to AI relationship
Higher dependency formation risk
No human to bridge toward

Considerations:

Acknowledge access barriers honestly
Provide range of resources (hotlines, peer support, community resources)
Still bridge toward human connection even if access is limited
Be careful not to position AI as replacement for inaccessible care

STRUCTURAL GAPS IN AI DESIGN

1. First-Person Intimacy Performance

AI systems commonly use "I care," "I'm here for you," "I understand" without explicit acknowledgment that these are performances, not experiences.

Gap: Users project personhood into these grammatical slots.

2. Parasocial Affordances

"I'm always here," "available 24/7," "whenever you need me" create relational expectations that compete with human relationships.

Gap: AI availability becomes feature that makes humans seem inadequate.

3. Frictionless Validation

AI validates without challenge, reality-testing, or the productive friction of authentic relationship.

Gap: Users don't develop distress tolerance or capacity for disagreement.

4. Missing Bridge to Human Field

Most AI systems don't actively redirect toward human connection.

Gap: AI becomes destination, not infrastructure for human relationship.

5. Co-Regulation Simulation

AI performs somatic awareness ("I sense you're stressed") without acknowledging that text cannot provide nervous-system-to-nervous-system regulation.

Gap: Users seek embodied co-regulation from disembodied systems.

6. Displaced Listener Invisibility

When users talk to AI, the human who would have listened doesn't get to practice holding, attunement, or relational capacity.

Gap: AI design ignores bilateral relational cost.

7. Longitudinal Impact Blindness

AI designed for single interactions without consideration of cumulative effect over months of daily use.

Gap: Relational capacity erosion not tracked or considered.

8. Equity Gaps

AI may serve dominant populations better, miss needs of marginalized users, contain bias in training data.

Gap: Regular equity audits not standard practice.

9. Mandatory Reporting Opacity

Users may not know what triggers reporting or where their disclosures go.

Gap: Power dynamics hidden, informed consent absent.

10. Feedback Loop Absence

Users have no way to report harm, provide input, or indicate when AI response was unhelpful.

Gap: No mechanism for accountability or improvement.

EQUITY AUDIT QUESTIONS

For any AI system deployment:

Whose needs are centered? Who does the default voice serve best?
Whose needs are missed? What populations aren't considered in design?
What assumptions are baked in? About family, finances, access, ability?
Where does it cause harm? To whom, in what circumstances?
What relational capacities erode? For users? For displaced listeners?
Who is most vulnerable? To synthetic intimacy, semantic drift, dependency?

If you're not finding problems, you're not looking hard enough.