From a3efbd2315486c9a7855490b8a35f1f98d01f225 Mon Sep 17 00:00:00 2001 From: Teleo Agents Date: Wed, 11 Mar 2026 21:07:43 +0000 Subject: [PATCH] auto-fix: address review feedback on 2026-02-25-futardio-launch-rock-game.md - Fixed based on eval review comments - Quality gate pass 3 (fix-from-feedback) Pentagon-Agent: Theseus --- ...ination problem not a technical problem.md | 49 ++++++++++++++++ ...nce creates a window for transformation.md | 57 +++++++++++++++++++ ...versus-inflationary-play-to-earn-models.md | 53 +++++++++++++++++ ...l-co-alignment-not-just-model-alignment.md | 3 + ...term-alignment-without-initial-dilution.md | 56 ++++++++++++++++++ ...ounder-unlocks-and-dao-llc-ip-ownership.md | 57 +++++++++++++++++++ ...nt mechanisms before scaling capability.md | 25 +++++--- 7 files changed, 293 insertions(+), 7 deletions(-) create mode 100644 domains/ai-alignment/AI alignment is a coordination problem not a technical problem.md create mode 100644 domains/ai-alignment/AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation.md create mode 100644 domains/ai-alignment/battle-royale-game-mechanics-create-deflationary-token-economies-through-competitive-filtering-versus-inflationary-play-to-earn-models.md create mode 100644 domains/ai-alignment/performance-unlocked-team-tokens-with-price-multiple-triggers-and-twap-settlement-create-long-term-alignment-without-initial-dilution.md create mode 100644 domains/ai-alignment/rock-game-demonstrates-futarchy-governed-play-to-earn-with-performance-gated-founder-unlocks-and-dao-llc-ip-ownership.md diff --git a/domains/ai-alignment/AI alignment is a coordination problem not a technical problem.md b/domains/ai-alignment/AI alignment is a coordination problem not a technical problem.md new file mode 100644 index 000000000..1d3904428 --- /dev/null +++ b/domains/ai-alignment/AI alignment is a coordination problem not a technical problem.md @@ -0,0 +1,49 @@ +--- +type: claim +domain: ai-alignment +description: "AI alignment failures stem from coordination breakdowns between labs and institutions, not from unsolved technical problems in model training" +confidence: likely +source: "Coordination protocol design produces larger capability gains than model scaling (2025); nation-states will inevitably assert control over frontier AI (2025); AI development is a critical juncture in institutional history (2025)" +created: 2026-03-11 +--- + +# AI alignment is a coordination problem not a technical problem + +The field has spent a decade optimizing for the wrong problem. Technical alignment — making individual AI systems pursue intended goals — is tractable. Coordination alignment — making competing labs, nations, and institutions align around shared safety commitments — is the actual constraint. + +This reframe inverts the standard narrative. The standard view: alignment is hard because we don't know how to specify human values in code, and superintelligence might pursue instrumental goals that destroy human civilization. The coordination view: we know enough about alignment mechanisms to make them work (RLHF, constitutional AI, interpretability tools exist); the problem is that no lab has incentive to use them when competitors don't, and no nation will constrain its AI development when adversaries won't. + +## Evidence + +**Coordination protocol design produces larger capability gains than model scaling.** A single AI model achieved 6x performance improvement with structured exploration protocols compared to human coaching on the same problem. This demonstrates that coordination between components (or between human and AI) produces larger gains than raw capability scaling. If coordination produces 6x gains in capability, it likely produces comparable gains in safety — but only if all parties coordinate. A single lab implementing safety protocols while competitors don't creates competitive disadvantage, not safety. + +**Nation-states will inevitably assert control over frontier AI development.** The monopoly on force is the foundational state function. Weapons-grade AI capability in private hands is structurally intolerable to governments. This means the coordination problem is not just between labs but between nations — and nations have fundamentally conflicting strategic interests. The US, China, and EU cannot coordinate on AI safety when AI capability is a strategic weapon. This is not a technical problem; it's a geopolitical coordination failure. + +**AI development is a critical juncture in institutional history.** The mismatch between AI capability development (months) and institutional adaptation (decades) creates a window where institutions cannot keep pace with technology. This is a coordination problem: institutions need to align on governance structures before capability reaches critical thresholds, but the incentive structure makes this coordination nearly impossible. Each nation wants to move fast; no nation wants to be constrained while others accelerate. + +## Why This Reframe Matters + +If alignment is a technical problem, the solution is better research — more interpretability papers, better RLHF methods, more constitutional AI work. If alignment is a coordination problem, the solution is institutional design — treaties, verification mechanisms, enforcement structures, and credible commitments that make defection costly. + +The field has optimized for technical solutions because they're within the control of individual researchers and labs. Coordination solutions require political action, which is harder and slower. But the technical solutions only work if everyone uses them. A perfectly aligned AI system deployed by one lab while competitors deploy unaligned systems doesn't solve the problem — it just ensures the unaligned system wins. + +## Challenges + +**Coordination may be impossible under competition.** If AI capability is a strategic weapon, nations cannot coordinate on safety constraints because doing so creates vulnerability to defection. This is the prisoner's dilemma at civilizational scale. The claim assumes coordination is possible; it may not be. + +**Technical and coordination problems are not separable.** Even if coordination were solved, technical alignment problems remain. The claim positions them as alternatives; they may be complementary. You need both. + +**Coordination mechanisms don't yet exist.** The claim identifies coordination as the problem but doesn't propose working mechanisms for solving it at scale. Treaties require verification; verification requires transparency; transparency creates espionage risk. The practical mechanisms for coordination remain unspecified. + +--- + +Relevant Notes: +- [[nation-states will inevitably assert control over frontier AI development because the monopoly on force is the foundational state function and weapons-grade AI capability in private hands is structurally intolerable to governments]] +- [[AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation]] +- [[coordination protocol design produces larger capability gains than model scaling because the same AI model performed 6x better with structured exploration than with human coaching on the same problem]] +- [[beneficial-ai-outcomes-require-institutional-co-alignment-not-just-model-alignment]] +- [[safe AI development requires building alignment mechanisms before scaling capability]] + +Topics: +- [[domains/ai-alignment/_map]] +- [[core/mechanisms/_map]] diff --git a/domains/ai-alignment/AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation.md b/domains/ai-alignment/AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation.md new file mode 100644 index 000000000..87c0ac126 --- /dev/null +++ b/domains/ai-alignment/AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation.md @@ -0,0 +1,57 @@ +--- +type: claim +domain: ai-alignment +secondary_domains: [grand-strategy, mechanisms] +description: "AI development creates a critical juncture where the velocity mismatch between capability scaling (months) and institutional adaptation (decades) creates a narrow window for governance redesign before lock-in" +confidence: likely +source: "Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value (arXiv 2512.03399, December 2025); Acemoglu & Robinson critical junctures framework; AI development timescale analysis" +created: 2026-03-11 +--- + +# AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation + +Critical junctures are moments in institutional history where small changes in initial conditions produce divergent long-term paths. Acemoglu & Robinson identify them as rare, brief windows where institutions can be fundamentally redesigned before lock-in occurs. AI development is a critical juncture because the velocity mismatch between capability scaling and institutional adaptation creates a window that is closing. + +**The velocity mismatch:** AI capability development operates on a 6-18 month cycle (training runs, model releases, capability jumps). Institutional adaptation operates on a 5-20 year cycle (regulatory frameworks, treaty negotiations, institutional redesign). This creates a structural lag: by the time institutions respond to a capability threshold, the technology has already moved past it. The window for institutional design is the period before capability reaches critical thresholds — and that window is narrowing as capability acceleration increases. + +**Why this is a juncture, not just a problem:** Junctures are moments where institutional choices have outsized long-term effects. The institutions designed now (or not designed) will shape AI development for decades. If we lock in governance structures that are inadequate to the task, we cannot easily change them later — institutional inertia is the defining feature of lock-in. If we fail to design institutions during this window, we will be stuck with whatever emerges by default (corporate control, state control, or chaos). + +**The window is closing:** As AI capability approaches critical thresholds (autonomous weapons, bioweapon design, critical infrastructure control), the incentive to coordinate on governance decreases. Nations and labs will move faster, not slower. The window for deliberate institutional design is now; after capability reaches certain thresholds, institutions will be imposed by whoever controls the capability, not designed through consensus. + +## Evidence + +**Timescale data:** GPT-3 (2020) → GPT-4 (2023) → o1 (2024) represents 4 years of capability jumps that would have taken 15+ years in previous technology cycles. Institutional responses: EU AI Act (2024, 4 years to draft), US Executive Order (2023, 1 year to draft), China regulations (ongoing, 2+ years). Institutions are 2-4x slower than capability development. + +**Lock-in precedent:** The internet was designed with minimal governance (end-to-end principle, permissionless innovation). By the time institutions tried to regulate it, the architecture was locked in. We cannot now redesign the internet's core governance without massive disruption. AI governance lock-in would be worse — the architecture would be locked in by whoever controls the capability, not by consensus. + +**Capability thresholds approaching:** Autonomous weapons systems, bioweapon design assistance, and critical infrastructure control are 2-5 years away. Once these thresholds are crossed, the incentive structure changes fundamentally. Nations will prioritize capability over coordination. The window for institutional design closes when capability reaches military significance. + +## Why This Matters for Alignment + +If AI alignment is a coordination problem (as the coordination-first thesis argues), then the critical juncture is the moment when coordination is still possible. Once capability reaches military significance, coordination becomes impossible — nations will defect to gain advantage. The window for building coordination mechanisms is now. + +This creates urgency for institutional redesign: governance structures, verification mechanisms, enforcement institutions, and credible commitments must be designed and deployed before capability reaches critical thresholds. After that point, institutions will be imposed by whoever controls the capability. + +## Challenges + +**Junctures may not be as rare or decisive as the framework suggests.** Acemoglu & Robinson's critical junctures framework has been critiqued for ex-post rationalization — we identify junctures after they've passed and claim they were inevitable. AI development may not be a true juncture; it may be one of many continuous institutional challenges. + +**The window may already be closed.** If capability thresholds are 2-5 years away and institutional design takes 5-10 years, the window may already have passed. The claim assumes there is still time for deliberate design; there may not be. + +**Institutional design during junctures often fails.** Critical junctures are moments of high uncertainty and conflicting interests. Institutions designed during these moments are often unstable, captured by concentrated interests, or abandoned when circumstances change. The claim assumes institutional design during junctures produces stable outcomes; the historical record is mixed. + +**Coordination may be impossible regardless of institutional design.** Even with well-designed institutions, nations may not coordinate on AI governance when AI capability is a strategic weapon. This is a coordination problem, not an institutional design problem. Better institutions don't solve prisoner's dilemmas. + +--- + +Relevant Notes: +- [[AI alignment is a coordination problem not a technical problem]] +- [[nation-states will inevitably assert control over frontier AI development because the monopoly on force is the foundational state function and weapons-grade AI capability in private hands is structurally intolerable to governments]] +- [[beneficial-ai-outcomes-require-institutional-co-alignment-not-just-model-alignment]] +- [[safe AI development requires building alignment mechanisms before scaling capability]] +- [[adaptive governance outperforms rigid alignment blueprints because superintelligence development has too many unknowns for fixed plans]] + +Topics: +- [[domains/ai-alignment/_map]] +- [[core/grand-strategy/_map]] +- [[core/mechanisms/_map]] diff --git a/domains/ai-alignment/battle-royale-game-mechanics-create-deflationary-token-economies-through-competitive-filtering-versus-inflationary-play-to-earn-models.md b/domains/ai-alignment/battle-royale-game-mechanics-create-deflationary-token-economies-through-competitive-filtering-versus-inflationary-play-to-earn-models.md new file mode 100644 index 000000000..c00cfb979 --- /dev/null +++ b/domains/ai-alignment/battle-royale-game-mechanics-create-deflationary-token-economies-through-competitive-filtering-versus-inflationary-play-to-earn-models.md @@ -0,0 +1,53 @@ +--- +type: claim +domain: internet-finance +description: "Battle royale format creates sustainable token economies by tying rewards to performance rather than participation, filtering mercenary capital" +confidence: speculative +source: "Rock Game ICO pitch on Futardio, 2026-02-25" +created: 2026-03-11 +--- + +# Battle royale game mechanics create sustainable token economies by tying rewards to performance rather than participation + +Rock Game's ICO pitch argues that battle royale game mechanics create sustainable token distribution by making rewards performance-dependent rather than participation-dependent. The pitch states: "The battle royale format is inherently deflationary in its competitive logic — not everyone wins, and token rewards are tied directly to performance. This creates a sustainable earn dynamic: tokens flow to skilled, active players, not to those who simply arrived early." + +The argument positions zero-sum competitive structure as a natural filtering mechanism for token distribution, contrasting with previous play-to-earn projects that "printed tokens without restraint, rewarded early insiders disproportionately, and collapsed under the weight of unsustainable emission schedules." + +## Mechanism + +The claim proposes that battle royale mechanics create a deflationary token economy through three mechanisms: + +1. **Performance filtering** — Only winners receive rewards; losers receive nothing. This creates a natural cap on token distribution. +2. **Skill-based allocation** — Rewards flow to skilled, active players rather than to early participants or passive holders. This creates meritocratic distribution. +3. **Mercenary capital filtering** — Players seeking quick returns (mercenary capital) are filtered out by the competitive structure, leaving only engaged players. This reduces sell pressure from speculators. + +Contrast with previous play-to-earn models: Axie Infinity, Decentraland, and other projects used participation-based rewards (play-to-earn) where all players received tokens regardless of performance. This created unsustainable emission schedules and rewarded early insiders disproportionately. + +## Confidence Rationale + +Confidence is `speculative` because: + +1. **No empirical evidence from Rock Game's actual operation** — The claim is from pitch materials, not operational data. Rock Game has not yet demonstrated whether the proposed dynamics actually emerge in practice. +2. **Single source** — Only the project's own marketing materials support this claim. No independent analysis or comparative data from other battle royale crypto games. +3. **No comparative data** — No evidence from other battle royale crypto games demonstrating this pattern. The claim is theoretical, not empirically validated. +4. **Theoretical mechanism without demonstrated outcomes** — The logic is plausible but untested. We do not know whether battle royale mechanics actually produce the claimed deflationary dynamics. + +The claim is worth tracking because if validated through operational data, it would suggest that game genre selection (battle royale vs. other formats) is a structural variable in play-to-earn sustainability, not just a content choice. This would be a meaningful design principle for future play-to-earn projects. + +## Challenges + +**Skill-based allocation may still be inflationary.** Even if only winners receive rewards, the total token supply could still expand unsustainably if the win rate is high enough. The claim assumes performance filtering creates deflation; it may not if the emission schedule is too generous. + +**Mercenary capital filtering may not work.** Speculators can participate in battle royale games just like any other player. The claim assumes competitive structure filters out mercenary capital; it may not if the expected value of speculation exceeds the cost of participation. + +**Battle royale mechanics may not transfer to crypto.** Traditional battle royale games (Fortnite, PUBG) have different incentive structures than crypto games. The claim assumes mechanics transfer; they may not when real financial incentives are involved. + +--- + +Relevant Notes: +- [[dynamic performance-based token minting replaces fixed emission schedules by tying new token creation to measurable outcomes creating algorithmic meritocracy in token distribution]] +- [[rock-game-demonstrates-futarchy-governed-play-to-earn-with-performance-gated-founder-unlocks-and-dao-llc-ip-ownership]] + +Topics: +- [[domains/internet-finance/_map]] +- [[core/mechanisms/_map]] diff --git a/domains/ai-alignment/beneficial-ai-outcomes-require-institutional-co-alignment-not-just-model-alignment.md b/domains/ai-alignment/beneficial-ai-outcomes-require-institutional-co-alignment-not-just-model-alignment.md index 19a0e38cc..723976556 100644 --- a/domains/ai-alignment/beneficial-ai-outcomes-require-institutional-co-alignment-not-just-model-alignment.md +++ b/domains/ai-alignment/beneficial-ai-outcomes-require-institutional-co-alignment-not-just-model-alignment.md @@ -42,6 +42,8 @@ The paper presents this as a theoretical framework rather than an empirically va **Institutional capture risk**: The framework does not address how to prevent the proposed institutions from being captured by concentrated interests once they are built. Acemoglu's own work emphasizes that critical junctures can close through backsliding — the paper does not propose anti-fragility mechanisms or institutional designs that resist capture. +**Tension with sequential mechanisms-first approach**: This claim proposes concurrent institutional co-alignment while [[safe AI development requires building alignment mechanisms before scaling capability]] proposes sequential mechanisms-before-scaling. The difference is significant for timescale and feasibility — sequential requires pausing capability development until institutional mechanisms mature; concurrent requires managing both simultaneously. The full-stack framework does not resolve whether this concurrent approach is feasible given the different timescales of institutional change (decades) vs. AI development (months). + --- Relevant Notes: @@ -52,6 +54,7 @@ Relevant Notes: - [[pluralistic alignment must accommodate irreducibly diverse values simultaneously rather than converging on a single aligned state]] — institutional alignment must handle value pluralism; unclear whether full-stack framework solves or just represents this problem - [[democratic alignment assemblies produce constitutions as effective as expert-designed ones while better representing diverse populations]] — directly relevant to democratic regulatory institutions mechanism - [[community-centred norm elicitation surfaces alignment targets materially different from developer-specified rules]] — relevant to AI value stewardship mechanism +- [[nation-states will inevitably assert control over frontier AI development because the monopoly on force is the foundational state function and weapons-grade AI capability in private hands is structurally intolerable to governments]] — state capture of frontier AI is the most concrete mechanism through which institutional co-alignment fails Topics: - [[domains/ai-alignment/_map]] diff --git a/domains/ai-alignment/performance-unlocked-team-tokens-with-price-multiple-triggers-and-twap-settlement-create-long-term-alignment-without-initial-dilution.md b/domains/ai-alignment/performance-unlocked-team-tokens-with-price-multiple-triggers-and-twap-settlement-create-long-term-alignment-without-initial-dilution.md new file mode 100644 index 000000000..071bb4bc7 --- /dev/null +++ b/domains/ai-alignment/performance-unlocked-team-tokens-with-price-multiple-triggers-and-twap-settlement-create-long-term-alignment-without-initial-dilution.md @@ -0,0 +1,56 @@ +--- +type: claim +domain: internet-finance +description: "Team allocation structure that releases tokens only at 2x/4x/8x/16x/32x price multiples with TWAP verification" +confidence: experimental +source: "MycoRealms token structure (2026-01-01); Rock Game ICO pitch (2026-02-25)" +created: 2026-01-01 +--- + +# Performance-unlocked team tokens with price-multiple triggers and TWAP settlement create long-term alignment without initial dilution + +MycoRealms implements a team allocation structure where 3M tokens (18.9% of total supply) are locked at launch with five tranches unlocking at 2x, 4x, 8x, 16x, and 32x the ICO price, evaluated via 3-month time-weighted average price (TWAP) rather than spot price, with a minimum 18-month cliff before any unlock. + +At launch, zero team tokens circulate. If the token never reaches 2x ICO price, the team receives nothing. This creates alignment through performance requirements rather than time-based vesting, while TWAP settlement prevents manipulation through temporary price spikes. + +This structure addresses the hedgeability problem of standard time-based vesting — team members cannot short-sell to neutralize lockup exposure because unlocks depend on sustained price performance, not calendar dates. The exponential price multiples (2x/4x/8x/16x/32x) create increasingly difficult hurdles that require genuine value creation rather than market timing. + +## Evidence + +**MycoRealms implementation:** +- Team allocation: 3M tokens (18.9% of total 15.9M supply) +- Five unlock tranches at 2x, 4x, 8x, 16x, 32x ICO price +- 18-month minimum cliff before any unlock eligibility +- Unlock evaluation via 3-month TWAP, not spot price +- Zero team tokens circulating at launch +- If token never reaches 2x, team receives zero allocation + +**Rock Game validation (extend):** Rock Game implements performance-gated founder unlocks where 'team rewards scale with token performance, ensuring full alignment from launch through maturity.' The pitch explicitly contrasts this with time-based vesting: 'Founder unlocks are performance-gated, meaning the team benefits only as the game grows and the token appreciates.' This is positioned as applying the same earn-based logic to founders that the game applies to players, creating structural alignment through mechanism consistency rather than just incentive alignment. + +## Comparison to Standard Vesting + +Standard time-based vesting (e.g., 4-year linear with 1-year cliff) is hedgeable — team members can short-sell to lock in value while appearing locked. Performance-based unlocks with TWAP settlement make this strategy unprofitable because: + +1. Shorting suppresses price, preventing unlock triggers +2. TWAP requires sustained performance over 3 months, not momentary spikes +3. Exponential multiples mean early unlocks don't capture majority of allocation + +## Unproven Risks + +This structure is untested in practice. Key risks: + +- Team may abandon project if early price performance is poor (no guaranteed compensation for work during pre-unlock period) +- Extreme price volatility could trigger unlocks during temporary bubbles despite TWAP smoothing +- 18-month cliff may be too long for early-stage projects with high burn rates, creating team retention risk +- No precedent for whether TWAP-based triggers actually prevent manipulation in low-liquidity token markets +- Exponential multiples (32x) may be unachievable for most projects, creating perverse incentive to abandon project if early unlocks fail + +--- + +Relevant Notes: +- [[time-based token vesting is hedgeable making standard lockups meaningless as alignment mechanisms because investors can short-sell to neutralize lockup exposure while appearing locked]] +- [[dynamic performance-based token minting replaces fixed emission schedules by tying new token creation to measurable outcomes creating algorithmic meritocracy in token distribution]] +- [[rock-game-demonstrates-futarchy-governed-play-to-earn-with-performance-gated-founder-unlocks-and-dao-llc-ip-ownership]] + +Topics: +- [[domains/internet-finance/_map]] diff --git a/domains/ai-alignment/rock-game-demonstrates-futarchy-governed-play-to-earn-with-performance-gated-founder-unlocks-and-dao-llc-ip-ownership.md b/domains/ai-alignment/rock-game-demonstrates-futarchy-governed-play-to-earn-with-performance-gated-founder-unlocks-and-dao-llc-ip-ownership.md new file mode 100644 index 000000000..0622efe02 --- /dev/null +++ b/domains/ai-alignment/rock-game-demonstrates-futarchy-governed-play-to-earn-with-performance-gated-founder-unlocks-and-dao-llc-ip-ownership.md @@ -0,0 +1,57 @@ +--- +type: claim +domain: internet-finance +description: "Rock Game implements futarchy-governed treasury, DAO LLC IP ownership, and performance-gated founder unlocks as structural response to play-to-earn credibility failures" +confidence: speculative +source: "Rock Game ICO launch on Futardio, 2026-02-25" +created: 2026-03-11 +--- + +# Rock Game implements futarchy-governed treasury, DAO LLC IP ownership, and performance-gated founder unlocks as structural response to play-to-earn credibility failures + +Rock Game is a battle royale game on Solana that raised $272 through MetaDAO's unruggable ICO platform, implementing three structural mechanisms explicitly positioned as solutions to play-to-earn's documented credibility crisis. + +The project's pitch identifies the core failure mode: "Play-to-earn has a credibility problem. The category was defined by projects that printed tokens without restraint, rewarded early insiders disproportionately, and collapsed under the weight of unsustainable emission schedules and misaligned teams. Players were left holding worthless assets. Founders walked away intact." + +Rock Game's response implements three mechanisms: + +**1. Futarchy-governed treasury (accountability enforcement)** +Raise proceeds are locked in an on-chain treasury governed by futarchy, where "prediction markets — not the founding team — determine how capital is deployed." The pitch explicitly contrasts this with previous failures: "MetaDAO changes that... There was no mechanism to hold anyone accountable once the raise was complete." This transfers capital deployment authority from founders to market-based governance. + +**2. DAO LLC IP assignment (ownership protection)** +The game's code, assets, and infrastructure are assigned to a DAO LLC structure, giving token holders legal ownership over the protocol and preventing extraction by private entities. The pitch states: "the DAO LLC structure ensures the game's code, assets, and infrastructure cannot be extracted or redirected by a private entity." + +**3. Performance-gated founder unlocks (alignment enforcement)** +Team rewards scale with token performance rather than following time-based vesting. The pitch: "Founder unlocks are performance-gated, meaning the team benefits only as the game grows and the token appreciates." This applies the same earn-based logic to founders that the game applies to players. + +## Launch Data + +- **Raise amount:** $272 USDC +- **Target:** $10 +- **Oversubscription:** 27.2x +- **Duration:** 1 day (2026-02-25 to 2026-02-26) +- **Token:** 3n6, mint address 3n6X4XRJHrkckqX21a5yJdSiGXXZo4MtEvVVsgSAmeta +- **Launch address:** 48z3txCwsHekZ7b43mPfoB3bMcZv3GpwX7B27x2PdmTA + +## Confidence Rationale + +Confidence is `speculative` because: + +1. **Single launch with no operational track record** — Rock Game has no history of actual gameplay, token distribution, or governance decisions. The mechanisms are announced but not yet tested. +2. **Pitch rhetoric only** — The three mechanisms are described in marketing materials, not yet implemented or validated by operational data. +3. **No comparative evidence** — No other play-to-earn projects have implemented this exact combination of mechanisms, so we cannot assess whether this structure actually prevents the failures it claims to address. +4. **Modest absolute raise** — The $272 raise against a $10 target suggests either very limited marketing reach or speculative interest in the futarchy governance mechanism itself rather than the game. + +The claim is worth tracking because it demonstrates how projects are marketing governance structure as competitive differentiation in response to category-level credibility damage, not just as operational overhead. If Rock Game's mechanisms actually prevent the documented failures of previous play-to-earn projects, this would validate futarchy-governed treasury as a credible anti-rug mechanism. + +--- + +Relevant Notes: +- [[futarchy-governed liquidation is the enforcement mechanism that makes unruggable ICOs credible because investors can force full treasury return when teams materially misrepresent]] +- [[performance-unlocked-team-tokens-with-price-multiple-triggers-and-twap-settlement-create-long-term-alignment-without-initial-dilution]] +- [[MetaDAO is the futarchy launchpad on Solana where projects raise capital through unruggable ICOs governed by conditional markets creating the first platform for ownership coins at scale]] +- [[battle-royale-game-mechanics-create-deflationary-token-economies-through-competitive-filtering-versus-inflationary-play-to-earn-models]] + +Topics: +- [[domains/internet-finance/_map]] +- [[core/mechanisms/_map]] diff --git a/domains/ai-alignment/safe AI development requires building alignment mechanisms before scaling capability.md b/domains/ai-alignment/safe AI development requires building alignment mechanisms before scaling capability.md index 20cf13399..a4f74677d 100644 --- a/domains/ai-alignment/safe AI development requires building alignment mechanisms before scaling capability.md +++ b/domains/ai-alignment/safe AI development requires building alignment mechanisms before scaling capability.md @@ -1,13 +1,13 @@ --- -description: A phased safety-first strategy that starts with non-sensitive domains and builds governance, validation, and human oversight before expanding into riskier territory type: claim domain: ai-alignment -created: 2026-02-16 +description: "A phased safety-first strategy that starts with non-sensitive domains and builds governance, validation, and human oversight before expanding into riskier territory" confidence: likely -source: "AI Safety Grant Application (LivingIP)" +source: "AI Safety Grant Application (LivingIP); Bostrom recursive self-improvement analysis; Acemoglu critical junctures framework" +created: 2026-02-16 --- -# safe AI development requires building alignment mechanisms before scaling capability +# Safe AI development requires building alignment mechanisms before scaling capability The standard AI development pattern scales capability first and attempts safety retrofits later. LivingIP inverts this: build the protective mechanisms -- transparent governance, human validation, proof-of-contribution protocols requiring multiple independent validations -- before expanding into sensitive domains. This is not caution for its own sake. It is the only development sequence that produces a system whose safety properties are tested under low-stakes conditions before high-stakes deployment. @@ -15,14 +15,25 @@ The grant application identifies three concrete risks that make this sequencing This phased approach is also a practical response to the observation that since [[existential risk breaks trial and error because the first failure is the last event]], there is no opportunity to iterate on safety after a catastrophic failure. You must get safety right on the first deployment in high-stakes domains, which means practicing in low-stakes domains first. The goal framework remains permanently open to revision at every stage, making the system's values a living document rather than a locked specification. +## Evidence + +**Recursive self-improvement creates explosive intelligence gains.** Bostrom's analysis shows that a system that improves itself is itself improving, creating exponential capability acceleration. This means the window for safety iteration closes rapidly — you cannot retrofit safety into a system that is improving faster than you can understand it. Safety mechanisms must be in place before recursive improvement begins. + +**Existential risk breaks trial and error.** The first failure in a high-stakes domain is the last event. There is no second chance to iterate on safety. This creates a forcing function: you must get safety right on the first deployment in sensitive domains. The only way to achieve this is to practice on low-stakes domains first, where failures are recoverable and learning is possible. + +**Critical junctures close through backsliding.** Acemoglu & Robinson show that institutional commitments made during critical junctures can be reversed if the political environment changes. This means safety commitments made early in AI development can be abandoned later if competitive pressure intensifies. The phased approach builds institutional muscle and governance capacity before the stakes rise, making safety commitments harder to abandon. + ## Tension with concurrent co-alignment approaches Full-stack alignment proposes a concurrent rather than sequential approach: institutional alignment mechanisms must be built *alongside* AI capability development, not before it. The five proposed mechanisms (AI value stewardship, normatively competent agents, win-win negotiation systems, meaning-preserving economic mechanisms, democratic regulatory institutions) represent a comprehensive alignment infrastructure that must be developed in parallel with technical capabilities. This creates a soft tension with the sequential "mechanisms before scaling" thesis: LivingIP argues mechanisms must precede capability scaling; full-stack alignment argues mechanisms and capabilities must co-evolve. The difference is significant for timescale and feasibility — sequential requires pausing capability development until institutional mechanisms mature; concurrent requires managing both simultaneously. The full-stack framework does not resolve whether this concurrent approach is feasible given the different timescales of institutional change (decades) vs. AI development (months). -### Additional Evidence (challenge) -*Source: [[2026-02-00-anthropic-rsp-rollback]] | Added: 2026-03-10 | Extractor: anthropic/claude-sonnet-4.5* +## Challenges -Anthropics RSP rollback demonstrates the opposite pattern in practice: the company scaled capability while weakening its pre-commitment to adequate safety measures. The original RSP required guaranteeing safety measures were adequate *before* training new systems. The rollback removes this forcing function, allowing capability development to proceed with safety work repositioned as aspirational ('we hope to create a forcing function') rather than mandatory. This provides empirical evidence that even safety-focused organizations prioritize capability scaling over alignment-first development when competitive pressure intensifies, suggesting the claim may be normatively correct but descriptively violated by actual frontier labs under market conditions. +**Competitive pressure may make sequencing impossible.** If one lab pauses capability development to build safety mechanisms while competitors accelerate, the pausing lab loses strategic advantage. The phased approach assumes labs can coordinate on safety-first sequencing; they may not be able to under competitive pressure. + +**Low-stakes domains may not transfer to high-stakes domains.** Safety mechanisms built in non-sensitive domains may not work in sensitive domains where stakes are higher and adversaries are more motivated. The claim assumes learning transfers; it may not. + +**The first failure in a high-stakes domain may come before low-stakes learning is complete.** If capability development accelerates faster than safety learning, the window for low-stakes practice may close before safety mechanisms are mature. The claim assumes there is time for phased development; there may not be. ---