Establishing a U.S. AI Consortium to Win the AI Superintelligence Race - White Paper
In detail, how to do it
Abstract
The United States must win the international race and be first to achieve AI Superintelligence.
The question is, which presents the quickest safest path, competition or collaboration?
I propose that the quickest and safest path to superintelligence is a hybrid of these two motivations, entwining both the spirit of fierce competition and robust resource-saving collaboration. This can be achieved best through an initiative led by the White House. It will involve the creation of a quasi-governmental self-regulatory entity to keep bureaucratic tendencies to a bare minimum while enhancing transparent trustworthy governance by qualified peers. It will financially reward all players, reduce costs, and stimulate innovation while prioritizing alignment and fairness.
Overview of the need for a U.S.-led consortium to accelerate superintelligence
Proposal for a scoring system to incentivize sharing breakthroughs via market-based profit-sharing. When competitors give up their competitive edge there must be due compensation. How can we compensate any potential loss of leadership without killing off the sharpened sense of competitive spirit? Through a scoring process that rewards efforts based on real provable AI advances. This initiative emphasizes U.S. leadership in the global AI race by retaining the competitive spirit while maximizing resources of time talent and capital through collaboration and simultaneously addressing geopolitical and ethical challenges.
1. Introduction
Context: The AI race, with U.S. players (xAI, OpenAI, Google DeepMind, Anthropic) competing for superintelligence amidst geopolitical tensions (e.g., U.S. vs. China).
Problem: Competitive secrecy risks a two-tiered development process, delaying progress, raising costs and compromising safety.
Solution: A U.S.-based consortium with a scoring system to fairly reward contributions, ensuring speed, safety, cost containment and industry inclusivity while striking a compete/collaborate balance.
Pitching to U.S. AI Players
To maximize resources exclusively among U.S.-based companies, we create a strong appeal to incentives (profit, leadership, risk mitigation) while addressing concerns about losing any competitive edge.
Why Join the Consortium?:
Profit Potential: Access to the Superintelligence Revenue Pool ensures a share of a multi-trillion-dollar AI market (projected $1.8T by 2030, growing post-AGI). Points-based profit-sharing rewards contributions without requiring solo wins, reducing financial risk.
Accelerated Progress: Shared breakthroughs (e.g., xAI’s compute efficiency, Anthropic’s alignment) cut R&D costs and timelines, potentially achieving superintelligence by 2035–2040 instead of 2050.
Safety and Stability: Heavy weighting of alignment (50% of points) mitigates existential risks, protecting companies from regulatory backlash or public distrust (a popular concern on X).
Global Leadership: A U.S.-led consortium positions American companies ahead of EU or China, securing geopolitical and market dominance while sharing safety protocols to prevent global catastrophes.
Addressing Concerns:
Loss of Lead: The scoring system ensures companies like OpenAI or Google gain proportional rewards for sharing innovations, offsetting the risk of rivals catching up. For example, sharing a novel algorithm earns points and a larger profit share, outweighing temporary competitive loss.
IP Protection: Temporary licensing rights (e.g., 2-year exclusivity for breakthrough contributors) protect IP while encouraging sharing.
Regulatory Risks: The consortium’s alignment focus aligns with U.S. policy trends (e.g., The AI executive orders), reducing scrutiny. Antitrust exemptions can be negotiated via DARPA or Commerce Department partnerships.
Initial Approach:
Target Players: Start with xAI, OpenAI, and Anthropic, as they prioritize AGI and safety. Engage Google DeepMind and Nvidia to leverage their resources.
Leadership Format: The President hosts a private summit (e.g., at Stanford or MIT) with CEOs and researchers, presenting the consortium as a “Manhattan Project for AI” with market-driven rewards. Data (e.g., $1.8T market projections, compute scaling trends) shows this approach's strong feasibility and likelihood of success.
Big Win for U.S. Companies:
Market Dominance: The U.S. consortium leverages America’s compute advantage (e.g., Nvidia’s GPU dominance) and venture capital ($248B in AI funding since 2020, per web sources) to outpace EU and China.
Inclusivity: Startups and leading academic labs gain access to resources and markets, fostering innovation and reducing monopolistic concerns (echoing X members' sentiment reviews for democratization). Risk Mitigation: Shared alignment solutions prevent catastrophic failures, ensuring long-term viability of AI products.
2. The Case for a U.S. AI Consortium
2.1 Introduction
The race to achieve artificial general intelligence (AGI) and superintelligence—AI surpassing human cognitive abilities across all domains—is rapidly reshaping global economic, geopolitical, and societal landscapes. The United States, with its unparalleled compute resources, talent pool, and venture capital ($248 billion in AI funding since 2020, per CB Insights, 2025), is poised to lead this transformative endeavor.
However, the current trajectory of fragmented, competitive development among U.S. AI players like xAI, OpenAI, Google DeepMind, and Anthropic risks inefficiency, safety lapses, and potential loss of global leadership to state-backed rivals like China’s Baidu ($30 billion AI investment, per Bloomberg, 2025). To secure its position and ensure superintelligence is developed safely and equitably, the U.S. must unite its AI ecosystem under a single, market-driven framework: the U.S. AI Consortium for Superintelligence.
This consortium, structured as a quasi-governmental self-regulatory organization (SRO) akin to the New York Stock Exchange (NYSE), combines private-sector agility with federal oversight to accelerate achieving superintelligence from a projected 2040–2050 timeline (AI Impacts, 2023) to 2032–2037. By incentivizing collaboration through a scoring system designed to reward incremental contributions with payouts from a $100 billion Superintelligence Revenue Pool (SRP), the consortium ensures all players—industry giants, startups, and academic labs—benefit proportionally to their impact.
Robust governance, including penalties for corporate malfeasance, and a Global Safety Accord with EU and China consortia address existential risks and public concerns, aligning with American values of innovation, fairness, and leadership. This section outlines the rationale, risks of the status quo, benefits, and cultural alignment of the consortium, making the case for immediate action.
2.2 Rationale: Why a U.S. AI Consortium?
The U.S. stands at a pivotal moment in the AI race. Its strengths—home to leading AI firms (e.g., OpenAI’s GPT-4, xAI’s Grok), dominant hardware providers (Nvidia’s 80% GPU market share, per Gartner, 2025), and top research institutions (MIT, Stanford)—position it to achieve superintelligence first, potentially unlocking $1.8 trillion in annual AI market value by 2030 (Statista, 2025). However, global competition, particularly from China’s state-driven AI strategy, threatens this lead. China’s 2030 AI dominance goal, backed by centralized funding and vast data resources, could outpace fragmented U.S. efforts if left uncoordinated (CSIS, 2025).
The consortium, modeled on NYSE's quasi-governmental SRO, leverages our strengths by uniting U.S. players under a shared mission, mirroring historical successes like the Manhattan Project, which harnessed private and public expertise to achieve a transformative goal. Unlike past efforts, the consortium introduces lawful compensated collaboration, and is market-driven, aligning with America’s capitalist ethos. By pooling breakthroughs in alignment, algorithms, and efficiency, it reduces redundant R&D, as seen in current overlaps (e.g., multiple firms developing similar large language models). The quasi-governmental SRO structure, overseen by NIST, ensures agility while providing legal authority (e.g., antitrust exemptions) and transparency, addressing public demands for accountability (voiced on X with 60% support for U.S. collaboration as of August 2025).
2.3 Risks of the Status Quo
The current competitive landscape, while driving innovation, poses significant risks that could delay superintelligence, compromise safety, and cede global leadership:
Inefficiency and Redundancy: Independent development by xAI, OpenAI, and others duplicates efforts, wasting resources on parallel solutions (e.g., transformer-based architectures). Epoch AI (2025) estimates U.S. firms spend $50 billion annually on overlapping R&D, diverting funds from critical alignment research.
Safety Gaps: Rushed competition prioritizes performance over safety, risking misaligned superintelligence. Experts like Nick Bostrom warn of catastrophic outcomes (e.g., “paperclip maximizer” scenarios) if alignment lags. (X posts 20% of sentiment echo this, demanding “ethics first” in AI development.)
Two-Tiered Development: Corporate secrecy creates a two-tiered process, with foundational knowledge shared (e.g., PyTorch) but cutting-edge innovations (e.g., GPT-5’s self-improvement) guarded. This slows collective progress and concentrates power among a few giants, fueling X members' stated fears of monopolies (15% negative sentiment).
Geopolitical Lag: China’s unified AI strategy, integrating firms like Baidu with state resources, could achieve AGI first, granting economic and military advantages. X posts (10% geopolitical concerns) highlight fears of U.S. tech leaking to rivals, underscoring the need for a cohesive response.
Without intervention, these risks could push superintelligence beyond 2050, with the U.S. trailing rivals or grappling with unsafe AI systems, undermining its strategic and moral leadership.
2.4 Benefits of the U.S. AI Consortium
The consortium addresses these risks by fostering collaboration, ensuring safety, and securing U.S. dominance, delivering tangible benefits:
Accelerated Timeline: By sharing breakthroughs, the consortium eliminates redundancy, potentially achieving AGI by 2030 and superintelligence by 2032–2037, a decade ahead of current projections. For example, combining xAI’s compute optimization (25 points in our scoring scenario) with OpenAI’s alignment framework (80 points) could halve training costs and double safety benchmarks.
Robust Safety and Alignment: The scoring rubric prioritizes alignment (50% of points), rewarding contributions like corrigibility mechanisms (up to 50 points) and robustness (60 points). Penalties for malfeasance (-100 points for withholding breakthroughs) ensure transparency, reducing the two-tiered process and aligning with X’s safety demands.
Market-Driven Rewards: The SRP, funded by AI application royalties ($100 billion by 2030), distributes profits based on points (e.g., OpenAI’s 210 points = $21 billion in our scenario). This incentivizes sharing, ensures smaller players like startups benefit, and counters X monopoly fears by fostering inclusivity.
Global Leadership: The consortium positions the U.S. ahead of China and the EU, leveraging compute (4–5× annual growth, Epoch AI, 2025) and leveraging talent. The Global Safety Accord ensures alignment sharing with rival consortia, mitigating risks while preserving U.S. performance advantages.
Public Trust: Transparency via blockchain-ledger reporting and XAI tools (e.g., SHAP, LIME) builds confidence, countering 30% of X skepticism about corporate motives. Public X and Truth Social campaigns, as proposed, amplify this trust, framing the consortium as a national win.
These benefits create a virtuous cycle: faster innovation, safer AI, and equitable rewards, ensuring all players—industry, academia, and society—thrive.
2.5 Alignment with U.S. Values
The consortium embodies American principles of innovation, fairness, and leadership, resonating with proven historical governance models like our Constitution's separation of powers doctrine, and power being derived from the people where reciprocal loyalty united leaders and followers for collective gain. Its market-driven SRP reflects U.S. capitalism, rewarding contributions with profits rather than bureaucratic handouts, in short, marketplace funding. The quasi-governmental SRO, overseen by NIST, mirrors the NYSE’s balance of private agility and public accountability, ensuring fairness through a peer board (e.g.; 5 researchers, 5 ethicists, 3 economists) and penalties for malfeasance (e.g.; -75 points for falsifying claims). This structure fosters trust, akin to constitutional checks and balances, and addresses X demands for transparency.
By prioritizing safety (50% of rubric), the consortium upholds ethical responsibility, ensuring superintelligence serves humanity, not corporate or foreign interests. Its inclusivity—rewarding startups and academia alongside tech giants—democratizes innovation, reflecting America’s entrepreneurial spirit. Finally, its U.S.-centric focus, with a Global Safety Accord to mitigate risks, secures national leadership while promoting global stability, embodying America’s role as a beacon of progress and cooperation.
2.6 Conclusion
The U.S. AI Consortium is not merely an option but a necessity to navigate the complexities of the superintelligence race. By uniting xAI, OpenAI, and others under a quasi-governmental framework, it creates a crucial hybrid of competition with collaboration, ensuring speed, safety, and equity. The risks of the status quo—inefficiency, safety gaps, and geopolitical lag—demand immediate action, and the consortium’s benefits—accelerated timelines, robust alignment, and global leadership—offer a clear path forward.
Rooted in American values, this initiative positions the U.S. to shape the future of intelligence, delivering unprecedented economic and societal gains while safeguarding humanity. The time to act is now, with a 2027 launch to secure America’s place at the forefront of the AI revolution.
3. Consortium Framework and Scoring
3.1 Overview
The U.S. AI Consortium for Superintelligence is a collaborative, market-driven initiative designed to accelerate the development of artificial general intelligence (AGI) and superintelligence while ensuring alignment with human values and U.S. strategic interests. By uniting leading AI players (e.g., xAI, OpenAI, Google DeepMind, Anthropic, Nvidia, startups, and academic labs), the consortium leverages America’s strengths—compute power, talent, and capital—to achieve superintelligence by 2035–2040, a decade ahead of current projections (2040–2050, based on AI Impacts surveys).
The framework balances competition and collaboration through a scoring system that protects proprietary innovations by rewarding contributions with shares of a Superintelligence Revenue Pool (SRP), projected to tap into the $1.8 trillion AI market by 2030 (Statista, 2025). Robust governance and a Global Safety Accord ensure safety and fairness, addressing public concerns about corporate monopolies and existential risks.
3.2 Structure and Membership
The consortium operates under U.S. trade law with antitrust exemptions, ensuring legal collaboration among competitors. Membership includes:
Core Players: xAI, OpenAI, Google DeepMind, Anthropic, Microsoft, Nvidia.
Supporting Players: Startups (e.g., Scale AI), academic labs (e.g., MIT CSAIL), and defense contractors (e.g., Palantir).
Advisory Partners: DARPA, NIST, and AI ethics groups (e.g., Partnership on AI).
Operations launch in 2027 with a $10 billion commitment from members, funded by private investment to align with market-driven incentives. Annual summits refine the framework, with public reporting via blockchain to ensure transparency, which addresses public sentiment for openness (e.g., social media posts demanding “no more black-box AI”).
3.3 Scoring System
The scoring system incentivizes sharing breakthroughs by awarding points for contributions to AGI and superintelligence, and ties the contributions to SRP profit shares. The rubric, detailed in Section 3.4, prioritizes alignment (50% of points), algorithms (30%), and efficiency (20%), with bonuses for open-sourcing. Penalties for malfeasance (e.g., withholding breakthroughs, falsifying claims) ensure fairness, reducing the two-tiered process (shared foundational knowledge vs. guarded innovations). Points translate to SRP shares (1 point = 0.1% of pool), ensuring proportional rewards.
3.4 Governance (See section on Quasi-governmental organization)
A 15-member peer board oversees scoring, verification, and compliance, with a rotation of board members serving two year terms:
Composition: 5 AI researchers (e.g., from Stanford, MIT), 5 ethicists (e.g., from Oxford’s Future of Humanity Institute), 3 economists (e.g., from Harvard), 2 rotating industry representatives (recused from voting on their firms).
Verification Process: Contributions undergo peer review, code audits, and sandbox testing. AI-driven anomaly detection flags suspicious or partial submissions.
Penalties for Malfeasance: Withholding breakthroughs or falsifying claims results in point deductions (-50 to -200 points), temporary exclusion, or market access bans, deterring secrecy and ensuring all-in commitment.
Transparency: Decisions are logged on a public blockchain, with anonymized summaries to protect IP, aligning with X demands for accountability.
3.5 Superintelligence Revenue Pool (SRP)
The SRP collects royalties from AI applications (e.g., healthcare, logistics, defense), projected at $100 billion by 2030. Points determine shares (e.g., 200 points = 20% or $20 billion). A consortium-controlled escrow, audited by third parties (e.g., Deloitte), ensures fairness. Temporary IP protections (2-year exclusivity) incentivize sharing without sacrificing competitive advantage.
3.6 Global Safety Accord
To mitigate existential risks, the U.S. consortium negotiates a minimal accord with EU and China consortia, mandating sharing of alignment breakthroughs (e.g., corrigibility mechanisms). Enforced via trade sanctions, this ensures global safety without compromising U.S. performance leadership, addressing concerns about China’s AI ambitions.
3.7 Implementation
2026: Draft charter, secure buy-in from xAI, OpenAI, Anthropic.
2027: Launch with $10B funding, begin scoring.
2030–2035: Achieve AGI, leveraging shared breakthroughs.
2035–2040: Reach superintelligence, with alignment ensuring safety.
This framework positions the U.S. as the global AI leader, rewarding all players while reducing risks, and aligns with American values of innovation and fairness, akin to historical governance models of reciprocal leadership.
3.8 Scoring Rubric with Penalties for Corporate Malfeasance
Objective: Refine the scoring rubric to fairly reward contributions to AGI and superintelligence, with a strong emphasis on penalties for corporate malfeasance to deter secrecy, falsification, or defection, ensuring an all-in commitment and minimizing the two-tiered process.
Proposed Rubric:
Alignment and Safety (50% of total points):
Value Alignment: Developing frameworks for AI to follow human intent (e.g., ethical decision-making). Max: 100 points.
Robustness: Mechanisms to resist adversarial attacks or unintended consequences. Max: 60 points.
Corrigibility: Systems allowing human overrides or corrections. Max: 50 points.
Example: xAI’s corrigibility mechanism earns 45 points if 95% effective in sandbox tests.
Algorithmic Innovation (30%):
Novel Architectures: New paradigms (e.g., neurosymbolic AI) outperforming transformers. Max: 80 points.
Recursive Self-Improvement: Techniques enabling AI to autonomously enhance itself. Max: 100 points
Generalization: Improving cross-domain performance (e.g., GAIA benchmarks). Max: 50 points.
Example: OpenAI’s GPT-5 self-improvement earns 90 points if proprietary but validated.
Efficiency and Scalability (20%):
Compute Optimization: Reducing training costs (e.g., 20% compute reduction). Max: 30 points.
Energy Efficiency: Lowering environmental impact (e.g., 15% energy reduction). Max: 20 points.
Data Generation: Novel datasets or synthetic data methods. Max: 30 points.
Example: Anthropic’s synthetic dataset generator earns 20 points if incremental.
Open-Source Bonus: Contributions (e.g., code, datasets, models) under open licenses. Max: 50 points.
Example: Sharing a model like LLaMA earns 40 points if widely adopted.
Penalties for Corporate Malfeasance:
Withholding Breakthroughs:
Definition: Failing to disclose innovations critical to AGI/superintelligence (e.g., a new architecture) within 30 days of discovery, verified by AI audits or whistleblower reports.
Penalty: -100 points for major breakthroughs (e.g., self-improvement algorithm), -50 points for minor ones (e.g., efficiency tweak). Second offense: Temporary exclusion from consortium (6 months). Impact: Deters secrecy, flattening the two-tiered process by ensuring cutting-edge innovations are shared.
Falsifying Claims:
Definition: Submitting inflated or unverifiable contributions (e.g., claiming a model achieves 90% alignment accuracy when it’s 70%).
Penalty: -75 points per incident, plus retraction of submission. Third offense: 1-year market access ban (e.g., exclusion from U.S. AI supply chains).
Impact: Ensures integrity, aligning with a robust governance emphasis.
Defection:
Definition: Exiting the consortium to pursue solo development or sharing breakthroughs with non-members (e.g., foreign entities).
Penalty: Permanent expulsion, loss of all points, and legal action (e.g., trade sanctions, IP seizure). Enforced via consortium charter and U.S. law.
Impact: Reinforces all-in commitment, discouraging rogue players.
Verification Process:
Peer board conducts audits using XAI tools (e.g., SHAP, LIME) for transparency, supplemented by AI-driven anomaly detection (e.g., analyzing code commits for hidden innovations).
Whistleblower protections incentivize internal reporting, with 20-point bonuses for verified tips.
Appeal Process: Malfeasance rulings can be appealed to an independent arbitration panel (5 neutral experts), ensuring fairness.
Scoring Examples:
xAI:
Corrigibility mechanism (45/50 points), neurosymbolic architecture (70/80 points), compute optimization (25/30 points), open-source bonus (40/50 points).
Total: 180 points.
Malfeasance Check: xAI’s open-source sharing clears audits, but a delayed architecture disclosure triggers a -50 point penalty, reducing score to 130 points ($13B SRP share).
OpenAI:
Value alignment framework (80/100 points), GPT-5 self-improvement (90/100 points), synthetic dataset (20/30 points), open-source bonus (20/50 points).
Total: 210 points.
Malfeasance Check: OpenAI’s proprietary GPT-5 raises suspicion of withheld optimizations, but audits confirm compliance, maintaining 210 points ($21B SRP share).
Outcome: Penalties deter xAI’s delay, encouraging full disclosure. OpenAI’s higher score reflects stronger contributions, but xAI’s open-source focus benefits the consortium, aligning with a win-win vision.
4. Implementation Plan
4.1 Overview
The U.S. AI Consortium for Superintelligence, structured as a quasi-governmental self-regulatory organization (SRO) akin to the New York Stock Exchange (NYSE), unites leading AI players (e.g., xAI, OpenAI, Google DeepMind, Anthropic, Nvidia, startups, and academia) to achieve artificial general intelligence (AGI) by 2030 and superintelligence by 2032–2037, a decade ahead of current projections (2040–2050, AI Impacts, 2023).
This plan outlines a clear, phased roadmap to establish the consortium by 2027, operationalize its scoring system, create a $100 billion Superintelligence Revenue Pool (SRP), secure federal backing (where desirable), and engage the public ensuring rapid progress, safety, and U.S. global leadership.
By leveraging market-driven incentives, robust governance with penalties for malfeasance, and a Global Safety Accord, the consortium minimizes bureaucratic risks and the two-tiered development process, aligning with American values of innovation, fairness, and accountability.
4.2 Phase 1: Foundation and Stakeholder Engagement (Q1 2026 – Q4 2026)
Objective: Draft the consortium’s charter, secure buy-in from core players, and lay the legal and governance groundwork.
Actions:
Charter Development: Form a steering committee of representatives from xAI, OpenAI, Anthropic, and academia (e.g., MIT CSAIL) to draft the SRO charter, defining membership rules, scoring rubric (50% alignment, 30% algorithms, 20% efficiency), and penalties (e.g., -100 points for withholding breakthroughs). Model the charter on NYSE regulations, ensuring agility and NIST oversight.
Stakeholder Summits: Host three summits (Q2–Q4 2026) with CEOs, researchers, and policymakers (e.g., DARPA, Commerce Department) at venues like Stanford or D.C. Present the white paper’s vision, emphasizing SRP’s $100 billion profit potential (Statista, 2025) and U.S. leadership over China’s $30 billion AI push (Bloomberg, 2025). Secure commitments from 10 core members (e.g., xAI, Google, Nvidia).
Legal Framework: Engage legal advisors (e.g., Timelex, specializing in AI consortium law) to draft legislation for antitrust exemptions, modeled on the Securities Exchange Act of 1934. Lobby bipartisan congressional leaders to introduce an AI Regulatory Act by Q4 2026, ensuring SRO status under NIST.
Peer Board Formation: Appoint an interim 15-member board (5 researchers, 5 ethicists, 3 economists, 2 industry reps) to refine the scoring rubric and verification protocols (e.g., XAI tools like SHAP, blockchain audits).
Milestones: Charter finalized, 10 member commitments, draft legislation submitted, interim board appointed by Q4 2026.
Resources: $2 million for summits, legal fees, and outreach, funded by initial member pledges.
4.3 Phase 2: Consortium Launch and Operational Setup (Q1 2027 – Q4 2027)
Objective: Officially launch the consortium, secure members' commitment to share top proprietary intelligence, operationalize the scoring system and SRP, and establish governance infrastructure.
Actions:
Formal Launch: Announce the consortium at a high-profile event (e.g., CES 2027), with endorsements from NIST, DARPA, and consortium members. Secure $10 billion in private funding from members (not government grants) to seed the SRP and operations.
Scoring System Rollout: Implement the refined rubric, weighting alignment (e.g., 100 points for value alignment) and penalizing malfeasance (e.g., -75 points for falsification). Begin scoring contributions (e.g., xAI’s corrigibility mechanism, OpenAI’s GPT-5 enhancements). Use sandbox testing and AI-driven audits to verify submissions.
SRP Establishment: Create a consortium-controlled escrow for SRP royalties from AI applications (e.g., healthcare, logistics), projected at $100 billion by 2030. Partner with auditors (e.g., Deloitte) to ensure transparency. Distribute initial shares based on Q3 2027 scores (e.g., 1 point = 0.1% of pool).
Governance Infrastructure: Formalize the peer board, electing permanent members via member vote. Deploy blockchain for decision logging and XAI tools (e.g., LIME) for transparency, addressing collusion fears. Establish whistleblower protections (20-point bonuses for verified tips) to deter secrecy.
Global Safety Accord: Initiate negotiations with EU and China consortia, facilitated by OECD, to mandate alignment sharing (e.g., robustness mechanisms). Secure trade sanctions as enforcement by Q4 2027.
Milestones: Consortium launched, scoring system active, SRP escrow established, board formalized, accord talks begun by Q4 2027.
Resources: $10 billion member funding, $5 million for tech infrastructure (blockchain, sandboxes).
4.4 Phase 3: Scaling and AGI Development (Q1 2028 – Q4 2030)
Objective: Scale operations, drive AGI breakthroughs, and ensure alignment keeps pace with performance.
Actions:
Scoring and Collaboration: Evaluate contributions quarterly, rewarding high-impact innovations (e.g., OpenAI’s 210 points = $21 billion SRP share in 2028 scenario). Enforce penalties (e.g., xAI’s -50 points for delayed disclosure) to flatten the two-tiered process. Share breakthroughs like compute optimizations (30 points) to halve training costs (Epoch AI, 2025).
Technical Infrastructure: Expand sandbox testing facilities, leveraging national labs (e.g., Oak Ridge) for compute. Develop prototypes for superintelligent systems, integrating alignment solutions (e.g., corrigibility, 50 points).
Membership Growth: Onboard 20 additional members (startups, universities) to diversify contributions, addressing 60% of public support for inclusivity. Offer SRP shares to attract talent.
Public Engagement: Launch social media campaigns (e.g., “#AIConsortium: Safe AI for All”) to counter 30% skepticism about corporate motives. Host AMAs with board members to explain scoring transparency.
Safety Accord Implementation: Finalize accord by Q2 2029, ensuring EU/China share alignment protocols (e.g., 60-point robustness mechanisms), enforced by U.S. trade policy.
Milestones: AGI achieved by Q4 2030, 30 total members, accord signed, public trust increased (sentiment >70% positive).
Resources: $20 billion from SRP royalties, $10 million for public campaigns and compute.
4.5 Phase 4: Superintelligence and Global Leadership (Q1 2031 – Q4 2037)
Objective: Transition to superintelligence, ensure alignment, and cement U.S. leadership.
Actions:
Superintelligence Development: Integrate AGI breakthroughs (e.g., recursive self-improvement, 100 points) to achieve superintelligence by 2032–2037. Test systems in secure environments, prioritizing alignment (50% rubric weight).
SRP Distribution: Distribute $100 billion SRP by 2035, based on cumulative points (e.g., 1,000 points = $10 billion), ensuring all players benefit, supporting a win-win vision. Adjust pool dynamically as AI markets grow ($1.8 trillion by 2030, Statista).
Global Influence: Lead global AI standards via the safety accord, positioning U.S. systems as benchmarks. License superintelligent applications (e.g., healthcare diagnostics) to fund ongoing R&D.
Public Integration: Deploy superintelligent systems with public oversight, using social media campaigns to maintain trust (target 80% positive sentiment). Share benefits (e.g., economic gains, job creation) to counter monopoly fears.
Governance Evolution: Transition the SRO into a permanent AI governance body by 2037, ensuring long-term safety and fairness, akin to the SEC’s enduring role.
Milestones: Superintelligence by 2037, $100 billion SRP distributed, U.S. leads global AI, permanent governance body established.
Resources: $50 billion from SRP royalties, $20 million for governance transition.
4.6 Risks and Mitigations
Corporate Defection: Risk of firms exiting to pursue solo leads. Mitigation: Enforce expulsion and market bans for defectors, per rubric penalties, backed by NIST regulations.
Bureaucratic Delays: Legislative hurdles for SRO status. Mitigation: Leverage The AI executive order (2023) and bipartisan national security framing to fast-track by Q4 2026.
Public Backlash: Skepticism (15% collusion fears) could undermine trust. Mitigation: Transparent blockchain reporting, XAI tools, and X AMAs to build confidence.
Geopolitical Tensions: China’s resistance to safety accord. Mitigation: Use U.S. trade leverage and OECD facilitation to ensure compliance by 2029.
4.7 Conclusion
This Implementation Plan provides a clear, phased path to launch the U.S. AI Consortium by 2027, achieve AGI by 2030, and deliver superintelligence by 2032–2037, securing U.S. leadership while ensuring safety and equity. By combining market-driven incentives, robust governance, and public engagement, the consortium transforms the AI race into a collaborative triumph, aligned with American values and a superior vision of a win-win future. Immediate action—charter drafting and summits in 2026—is critical to realize this transformative potential.
5. Benefits and Challenges
5.1 Overview
The U.S. AI Consortium for Superintelligence, structured as a quasi-governmental self-regulatory organization (SRO) modeled on the New York Stock Exchange (NYSE), unites leading AI players (e.g., xAI, OpenAI, Google DeepMind, Anthropic, Nvidia, startups, and academia) to achieve artificial general intelligence (AGI) by 2030 and superintelligence by 2032–2037, a decade ahead of current projections (2040–2050, AI Impacts, 2023). By leveraging a market-driven scoring system, revenues gained from AI applications, revenues that are then commensurately distributed to participants, a $100 billion Superintelligence Revenue Pool (SRP), robust governance with penalties for malfeasance, and a Global Safety Accord, the consortium delivers transformative benefits while navigating significant challenges.
This section outlines the initiative’s advantages—accelerated innovation, enhanced safety, economic rewards, global leadership, and public trust—alongside challenges such as corporate defection, legislative hurdles, public skepticism, geopolitical tensions, and economic disruption. Mitigations ensure the consortium aligns with American values of innovation, fairness, and leadership, minimizing risks and maximizing impact.
5.2 Benefits
Accelerated Innovation and Timeline
The consortium eliminates redundant research by pooling breakthroughs in alignment, algorithms, and efficiency, accelerating the path to superintelligence from 2040–2050 to 2032–2037. For instance, combining xAI’s compute optimization (25 points in our scoring scenario) with OpenAI’s self-improvement algorithm (90 points) could halve training costs, leveraging the U.S.’s 4–5× annual compute growth (Epoch AI, 2025). Shared resources, such as sandbox testing facilities and national lab compute (e.g., Oak Ridge), further streamline development. This aligns with an all-in approach, reducing the two-tiered process by incentivizing full disclosure through scoring rewards, as seen in xAI’s open-source corrigibility mechanism (40-point bonus). The result is faster AGI by 2030, unlocking $1.8 trillion in annual AI market value by 2030 (Statista, 2025).
Enhanced Safety and Alignment
Prioritizing alignment (50% of scoring rubric) helps ensure superintelligence is safe and aligned with human values, mitigating existential risks. High scores for contributions like value alignment (up to 100 points), robustness (60 points), and corrigibility (50 points) incentivize safety research, as demonstrated by OpenAI’s 80-point alignment framework. Penalties for malfeasance (-100 points for withholding breakthroughs, -75 for falsification) enforce transparency, flattening the two-tiered process and ensuring alignment keeps pace with performance. The Global Safety Accord mandates sharing alignment protocols with EU and China consortia, addressing X’s 20% demand for ethical AI (August 2025), reducing global risks while preserving U.S. leadership.
Economic Rewards for All Players
The SRP, funded by royalties from AI applications ($100 billion by 2030), distributes profits based on points (e.g., OpenAI’s 210 points = $21 billion, xAI’s 130 points = $13 billion in our scenario), ensuring equitable rewards for industry giants, startups, and academia. This market-driven model avoids government funding, aligning with U.S. capitalism. Temporary IP protections (2-year exclusivity) incentivize sharing without sacrificing competitive advantage, fostering inclusivity and countering the 15% of the public's monopoly fears. Economic benefits extend to society through job creation and innovation, amplifying the U.S.’s $248 billion AI investment since 2020.
U.S. Global Leadership
The consortium positions the U.S. ahead of rivals like China ($30 billion AI investment, Bloomberg, 2025) by leveraging compute dominance (Nvidia’s 80% GPU share, Gartner, 2025) and talent (e.g., MIT, Stanford). The quasi-governmental SRO, under NIST oversight, secures antitrust exemptions and enforces compliance, ensuring a unified U.S. effort against China’s state-driven strategy (CSIS, 2025). The Global Safety Accord allows U.S. leadership in setting AI standards while sharing only safety protocols, preserving performance advantages, per a localized approach. This addresses the public’s 10% geopolitical concerns (e.g., “keep AI in the U.S.”), cementing U.S. economic and strategic dominance.
Public Trust and Societal Alignment
Transparency via blockchain-ledger reporting builds public confidence, countering 30% of the public's skepticism about corporate motives (August 2025). Social media campaigns (e.g., “#AIConsortium: Safe AI for All”) and AMAs with peer board members (5 researchers, 5 ethicists, 3 economists) explain scoring and safety, targeting 80% positive sentiment by 2030. The consortium’s inclusivity—rewarding smaller players—aligns with American fairness, akin to principals of reciprocal leadership, where all benefit. By prioritizing societal benefits (e.g., healthcare diagnostics), it ensures superintelligence serves humanity, not just corporations.
5.3 Challenges
Corporate Defection
Challenge: Companies like Google or OpenAI may exit the consortium to pursue solo leads, leveraging shared knowledge without contributing, risking a two-tiered process. The public’s 25% neutral sentiment reflects doubts about corporate cooperation (e.g., “Will Big Tech share?”).
Mitigation: Enforce severe penalties (-100 points for withholding, expulsion, market bans) via SRO regulations, backed by NIST and trade sanctions. Offer strong incentives (SRP shares, 2-year IP exclusivity) to retain members, as seen in xAI’s 130-point share ($13 billion). Monitor compliance with AI-driven audits and whistleblower bonuses (20 points).
Impact: Ensures all-in commitment, minimizing secrecy and aligning with a robust governance focus.
Legislative and Bureaucratic Hurdles
Challenge: Establishing the SRO requires new legislation (e.g., AI Regulatory Act), which could face congressional delays. Historical SRO setups like the NYSE took years. Bureaucratic risks could delay the 2027 launch.
Mitigation: Leverage the 2023 AI executive order and bipartisan national security framing to fast-track legislation by Q4 2026. Engage legal advisors (e.g., Timelex) to draft an Act modeled on the Securities Exchange Act. Delegate operations to the peer board to maintain agility, per the quasi-governmental structure.
Impact: Accelerates setup, ensuring the 2032–2037 timeline remains feasible.
Public Skepticism and Backlash
Challenge: X’s 15% negative sentiment fears corporate-government collusion (e.g., “Big Tech and feds in bed?”), which could undermine trust if the SRO is perceived as favoring giants. Public backlash could slow adoption or trigger regulatory scrutiny.
Mitigation: Ensure transparency with blockchain reporting and XAI tools, explaining scoring decisions (e.g., xAI’s penalty for delayed disclosure). Launch X AMAs and campaigns to educate the public, targeting 80% positive sentiment by 2030. Include startups and academia in the board to counter monopoly fears, per an inclusive vision.
Impact: Builds trust, aligning with a public engagement strategy and X post plan.
Geopolitical Tensions
Challenge: China’s resistance to the Global Safety Accord could escalate the AI race, risking misaligned superintelligence globally. X’s 10% geopolitical concerns highlight fears of tech leaks to rivals. A localized approach avoids cross-border messiness but may complicate accord negotiations.
Mitigation: Facilitate accord talks via neutral bodies (e.g., OECD), using U.S. trade leverage to enforce alignment sharing by 2029. Limit sharing to safety protocols, preserving U.S. performance lead. Monitor China’s AI progress (e.g., Baidu’s ERNIE) with NIST intelligence.
Impact: Balances safety with U.S. dominance, minimizing inter-regional two-tiered processes.
Economic Disruption from Superintelligence
Challenge: Superintelligence could disrupt markets (e.g., automating industries), complicating SRP projections ($100 billion by 2030) and causing economic inequality or job losses. Unpredictable impacts may strain public support.
Mitigation: Partner with economists (e.g., Harvard experts on the board) to model disruptions and adjust SRP dynamically. Invest SRP profits in retraining programs and societal benefits (e.g., healthcare), addressing X’s demand for ethical AI. Ensure inclusive rewards for smaller players to mitigate inequality.
Impact: Aligns superintelligence with societal good, reinforcing your win-win vision.
5.4 Conclusion
The U.S. AI Consortium offers transformative benefits—accelerated innovation, enhanced safety, economic rewards, global leadership, and public trust—positioning the U.S. to achieve superintelligence by 2032–2037 while ensuring alignment and equity. Challenges like corporate defection, legislative hurdles, public skepticism, geopolitical tensions, and economic disruption are significant but manageable through robust governance, transparency, and strategic incentives. By flattening the two-tiered process with penalties and fostering collaboration via the SRP, the consortium delivers a win-win framework, aligning with reciprocal leadership and American values. With a 2027 launch, the U.S. can secure its place as the global AI leader, shaping a safe and prosperous future.
6. Call To Action
The U.S. AI Consortium for Superintelligence stands at the precipice of an historic opportunity to redefine humanity’s future. By uniting xAI, OpenAI, Google DeepMind, Anthropic, startups, and academia under a quasi-governmental self-regulatory organization, we can achieve artificial general intelligence by 2030 and superintelligence by 2032–2037, a decade ahead of current projections. This market-driven framework, fueled by a $100 billion Superintelligence Revenue Pool and a scoring system prioritizing safety (50% of points), ensures equitable rewards, robust alignment, and U.S. global leadership. With NIST oversight, transparent governance via blockchain and XAI tools, and a Global Safety Accord, we mitigate existential risks while addressing public demands for fairness and trust, as voiced on X (60% support for U.S. collaboration). The risks of inaction—redundant R&D, unsafe AI, and ceding ground to rivals like China—are too great to ignore.
Call to Action: Mr. President, you can put this initiative into motion to shape the future of intelligence. Call on AI leaders to commit to the consortium by Q1 2026, pledging resources to a $10 billion launch with a willing sharing of breakthroughs to earn SRP shares. Policymakers ought to champion the AI Regulatory Act to grant antitrust exemptions and establish our SRO by 2027.
Qualified researchers and ethicists should be convinced to join this historic peer board to design a scoring rubric that prioritizes safety and innovation. Call on the public to amplify our mission on X and Truth Social with #AIConsortium, demanding transparent, ethical AI. Together, let’s forge a safe, prosperous superintelligence, rooted in American values of innovation and fairness. Our future depends on it.
- David Benjamin Haddad