AI and Knowledge
“Knowledge is overrated, William. What’s required is diligence and the service of a willing spirit.”
– Tom Nuttall to his son in the HBO Television Drama: Deadwood
Why this matters for AI use
In Deadwood, Tom Nuttall’s line reframes what actually matters when facing a powerful new tool—and that’s why it maps so cleanly onto AI.
- AI dramatically lowers the cost of knowledge but does not replace intent, judgment, or follow-through. Models can supply facts, drafts, code, and options instantly—but they do not decide what is worth doing, when to stop, or whether the result is good enough. That still belongs to the human.
- In short: AI amplifies effort, not entitlement. The people who benefit most aren’t the ones who know the most, but the ones willing to work, iterate, and take responsibility for outcomes. Tom Nuttall’s advice turns out to be a near-perfect operating manual for the AI age.
AI Abundance: Conservative-Optimistic Timeline
AI abundance doesn’t arrive all at once. It shows up quietly—faster services, lower costs, better tools, and fewer bottlenecks. This timeline explores how artificial intelligence may steadily improve everyday systems over the next decade, helping governments work better, education become more practical, housing more achievable, businesses more productive, and money stretch further—without assuming mass upheaval or unrealistic promises.
2025 — Tooling Becomes Normal
- Government: AI copilots adopted quietly for clerical work, regulatory drafting, and records search.
- Education: AI allowed as calculator-equivalent; emphasis on synthesis and oral defense.
- Housing: AI used in zoning analysis and permit processing.
- Commerce: White-collar AI use becomes routine with productivity stabilization.
- Money: Cost savings absorbed by firms; inflation hedged.
2026 — Institutional Catch-Up
- Government: National AI standards emerge for transparency and liability.
- Education: AI literacy becomes required curriculum.
- Housing: AI-assisted design lowers compliance and architectural costs.
- Commerce: Small businesses gain leverage through AI back-office tools.
- Money: Early AI-driven deflation offsets service inflation.
2027 — Productivity Without Shock
- Government: AI-assisted drafts published openly; hiring slows via attrition.
- Education: Credentialing shifts toward portfolios and demonstrations.
- Housing: Planning optimization modestly shortens construction timelines.
- Commerce: Output per employee rises; judgment becomes differentiator.
- Money: Purchasing power improves slightly.
2028 — Abundance Becomes Visible
- Government: AI simulations used for policy impact analysis.
- Education: Lifelong learning subscriptions expand.
- Housing: AI-guided construction reduces costs at the margin.
- Commerce: AI agents manage procurement and logistics.
- Money: Service inflation drops noticeably.
2029 — Structural Adjustment
- Government: Tax codes adapt to capital productivity gains.
- Education: Apprenticeship and mentor-based models regain prestige.
- Housing: Cost growth slows in reformed jurisdictions.
- Commerce: Management layers flatten.
- Money: Debt burdens ease relative to income.
2030 — Normalization of Abundance
- Government: AI treated as regulated infrastructure.
- Education: Modular, continuous, and cheaper education models dominate.
- Housing: Chronic shortages ease through efficiency gains.
- Commerce: Near-zero marginal cost for many digital services.
- Money: Cost of living stabilizes relative to productivity.
2031–2035 — Mature AI Abundance (Conservative Path)
- Government: Smaller but more capable bureaucracies.
- Education: Universal high baseline competence; excellence rewarded.
- Housing: Housing treated increasingly as infrastructure.
- Commerce: Entrepreneurship flourishes due to low startup friction.
- Money: Abundance expressed as time, access, and stability.
