Abundance First: A Reasoned Case for Sequencing AI to Solve Scarcity Before It Displaces Labor
Abstract
The order in which we deploy AI determines whether it stabilizes or fractures society. Prioritizing abundance in essentials—food, housing, energy, healthcare—before widespread labor automation prevents mass precarity and builds a stable path to a post labor future. This article outlines why this sequence is necessary, proposes a framework for implementation, and addresses key objections.
1. Introduction
The sequence of AI deployment shapes its societal impact. If AI automates labor before creating abundance in essentials (food, housing, energy, healthcare), it risks mass unemployment amid persistent scarcity. The Abundance-Driven Access Economy (ADAE) inspires a strategy to reverse this order: first, use AI to eliminate scarcity in essentials; second, establish fair access systems; and third, automate broadly. This sequencing is logically necessary, practically feasible, and politically stabilizing.
2. The Order of Operations Problem
AI has two primary effects:
• Destroys Labor Demand: Through automation, AI reduces the need for human labor.
• Destroys Scarcity: Via hyper-productive, self-repairing systems, AI can make essentials abundant.
If automation outpaces abundance, displaced workers face unemployment while still dependent on wages, leading to mass precarity. Prioritizing abundance ensures survival is delinked from income, fostering social resilience. This is akin to building a new bridge before demolishing the old one.
3. A Sequenced Deployment Framework
3.1 Phase A: Abundance Build-Out
Before broad labor displacement, AI should focus on making essentials abundant and affordable:
• Food: AI-optimized vertical farms, precision fermentation, robotic harvesting.
• Housing: AI-driven site selection, automated design for manufacturing, prefabricated and robotic assembly.
• Energy: AI-optimized grids, distributed renewables, storage forecasting, accelerated fusion R&D.
• Healthcare and Education: Preventive AI-triaged care and AI tutors for near-free, worldclass education.
3.2 Phase B: Access and Fair Allocation
Once abundance is achieved, fair access systems ensure equitable distribution:
• Zero-Knowledge Allocation: Privacy-preserving lotteries, rotations, or reputation-weighted queues for limited resources.
• Community Governance: Local councils or DAOs, aided by auditable AI, set access rules.
• Price as Last Resort: Use pricing only when fairness-based allocation fails.
3.3 Phase C: Full-Stack Automation
With survival needs met and access systems in place, automate remaining industries aggressively, as survival no longer depends on wages.
4. Objections and Responses
Objection 1: “We can’t delay automation; competition will force it anyway.”
• Response: While automation is inevitable, taxing automation profits into Abundance Funds, conditioning approvals on price reductions, and accelerating abundance sectors with public capital can align timelines.
Objection 2: “Abundance is technically uncertain (e.g., fusion, molecular manufacturing).”
• Response: Abundance can be achieved with existing technologies like vertical farming, prefab housing, and renewables. Fusion and advanced manufacturing are bonuses, not prerequisites.
Objection 3: “Elites will block a post-scarcity transition.”
• Response: Offer transitional privileges (e.g., location priority), equity in Abundance Funds, and a growth narrative to align elites with the transition.
5. Practical Policy and Engineering To-Do List
5.1 First Phase
• Launch national or city-level Abundance Acceleration Programs.
• Tax automation windfalls to fund Abundance Funds.
• Run UBI pilots alongside abundance projects.
• Mandate cost transparency dashboards for AI-influenced essentials (utilities, food, housing).
5.2 Next Phase
• Scale AI models for agriculture, energy, and logistics.
• Deploy zero-knowledge allocation pilots for limited goods.
• Introduce AI Commons Licenses for models that reduce essential costs.
5.3 Final Phase
• Codify post-scarcity constitutional amendments (access to essentials as a right).
• Transition from UBI to Universal Access as essentials near zero marginal cost.
• Institutionalize global compute and resource dividends.
6. Conclusion
If AI eliminates wages before scarcity, it risks a legitimacy crisis; prioritizing abundance first unlocks a stable path to a post-labor civilization. This abundance-first strategy is not utopian but a risk-aware approach to stability. The sequencing is designable, the levers exist, and the technology is within reach. What remains is the political will and public narrative to demand AI serves humanity before replacing it.