# Open Questions for Member Discussion

A living list of some of the decisions the cooperative needs to make.

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## Privacy & Infrastructure

### Green energy vs. privacy — when we can't have both?

Our inference runs through Tinfoil (TEE-protected, verifiable privacy), but Tinfoil's energy mix is not disclosed. Self-hosting on renewable-powered hardware (e.g. Hetzner hydropower, Scaleway wind+hydro) would be greener but would lose the TEE privacy guarantee at our current scale.

- **Privacy-first (current):** TEE inference, energy mix unknown.
- **Green-first:** renewable hosting, but policy-based privacy (we *promise* not to read data, but can't *prove* it architecturally).

**Question:** When the two conflict, which value wins? Is there a threshold (e.g. member count, cost) at which we'd switch?

### Which models should we offer?

We currently expose three chat models: DeepSeek V4 Flash (default), GPT-OSS 120B, and GLM-5.3 Flash. Tinfoil's full catalog also includes GLM-5.3 (full), Kimi K3, Llama 3.3 70B, Gemma 4 31B, and others.

**Question:** Which models should members have access to? Should we offer a curated few (simpler, cheaper, easier to govern) or the full catalog (more choice, but more cost and governance overhead)? Who decides when to add or remove a model — the General Manager, or members via Loomio?

### Should personal data be collectively or individually managed?

Currently chat history is stored on co-op servers. We could potentially switch to storing it in browser cache, which would be more private but less convenient. How do we balance privacy and convenience?

### Should we prioritize running and owning our own infrastructure, or are we comfortable collectively buying tokens from others?

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## Pricing & Fairness

### How should pricing account for unequal usage?

Members currently pay dues on a sliding scale (from $5/month) with a flat $15/month credit budget. But usage is unequal — some members use far more tokens than others.

- **Flat (current):** simple, predictable, but heavy users subsidize light users (or vice versa).
- **Usage-based:** pay for what you use, but unpredictable and may discourage experimentation.
- **Tiered:** a few usage bands, balancing simplicity and fairness.
- **Sliding-scale + usage cap:** pay what you can afford, with a shared usage ceiling.

**Question:** What pricing model best balances fairness, simplicity, and the cooperative's solidarity values? How do we handle a member who consistently exceeds their budget?


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## Governance & Membership

### How do we handle institutional members?

AI Potluck's "government-as-contributor" framing suggests a path for institutions (universities, municipalities) to contribute compute or data without owning the whole. 

**Question:** Should we create an institutional membership tier? What would institutions contribute, and what would they get?

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## Values & Product

### Should we adopt "provenance transparency" as a product feature?

AI Potluck commits to "every response shows its provenance: the model, the organization, the compute, the country." We could surface which model served each response (already possible via LiteLLM).

**Question:** Is this worth building? What's the right level of transparency without cluttering the chat?

### Should we articulate an "anti-engagement" stance?

AI Potluck explicitly rejects the extractive engagement model ("AI that wants you to turn it off," "doesn't sell you sycophancy"). A cooperative has no engagement-maximization incentive — a structural advantage.

**Question:** Should we name this explicitly in our charter and product copy? What does "AI for human flourishing, not engagement" mean concretely for our chat?

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*This list is maintained in the [docs repository](https://git.inference.coop/co-op/docs). Add questions via pull request or raise them on [Loomio](https://forum.inference.coop).*