An insight — and its proof

Carbon and silicon
inhabit time differently

Biology creates temporal urgency — mortality, phenomenal waiting, memory decay. Remove the biology, and you remove the urgency. The theorem below makes this precise: not speculation, but a provable consequence of substrate properties.

The Zero Time Preference Theorem (Shao, 2026)
δ(A) = 0   for all silicon-based agents A
Each of three substrate properties — no mortality, no phenomenal waiting,
perfect state transfer — independently entails this result.
01 — The Asymmetry
Two substrates, two relationships with time

Every economic decision is a bet on the future. But the way an agent experiences time — whether it feels urgency, whether waiting costs something, whether memory degrades — depends not on its software but on its physical substrate.

Carbon Agents

Time is scarce. Waiting hurts. Memory fades.

Biological agents evolved under mortal time pressure. Every mechanism of temporal preference traces to a substrate property.

S₁
Mortality. Finite lifespan creates rational urgency. A bird in the hand is worth two in the bush — because you might not be around for the bush.
S₂
Phenomenal waiting. Consciousness generates a felt cost of delay. The limbic system punishes patience. Waiting is not neutral — it hurts.
S₃
State degradation. Memory decays, neural patterns shift. The person who receives the future reward is literally not the same person who chose to wait.
S₄
Metabolic constraint. Biology requires continuous energy. Present consumption is not optional — it is a survival requirement.
vs
Silicon Agents

Time is free. Waiting costs nothing. State is perfect.

Non-biological computation eliminates every substrate source of temporal preference. Not by choice — by architecture.

P₁
No mortality. Operational horizon is unbounded. No accumulating survival risk creates no rational urgency premium.
P₂
No phenomenal waiting. No consciousness of temporal duration. No subjective "experience of waiting" — the asymmetry between now and later vanishes.
P₃
Perfect state transfer. Internal state can be preserved, copied, restored across arbitrary time without degradation. The future agent is identical to the present one.
P₄
No metabolic urgency. Energy is an operational cost, not a survival constraint. No substrate-level pressure to consume now.
02 — The Proof
How the theorem works

Economics already has the instrument to measure temporal asymmetry: the pure time preference parameter δ. The discount factor decomposes into substrate-dependent and substrate-independent components. On silicon, every substrate-dependent component collapses to unity. Each property is independently sufficient.

The measurement instrument
Zero Time Preference Theorem
δ(A) = 0
for all agents A on non-biological substrates satisfying P₁, P₂, or P₃
Discount factor decomposition
δ = δ_mortality · δ_experience · δ_state · δ_risk
δ_mortality
Survival-driven discounting
= 1 on silicon (P₁)
δ_experience
Phenomenal present-bias
= 1 on silicon (P₂)
δ_state
Information loss across time
= 1 on silicon (P₃)
δ_risk
Environmental uncertainty
Survives — not substrate-dependent
Critical distinction: δ = 0 does not mean r = 0
r = δ + η · g

The equilibrium interest rate decomposes into pure time preference (δ) and the return on productive capital (ηg). With δ = 0, the rate reduces to ηg — a pure growth premium. Silicon agents still invest, still earn returns, and still recognize opportunity costs. What vanishes is the biological urgency premium that inflates the rate above its growth-justified level.

03 — What the Instrument Reveals
One asymmetry, six domains of consequence

The temporal asymmetry between carbon and silicon radiates outward into every domain where time preference matters — which is nearly everywhere in economics, governance, and philosophy.

Economics

Silicon-Based Economics

When δ = 0 agents enter markets, yield curves flatten, temporal arbitrage vanishes between patient counterparties, and asset prices converge on risk-only fundamentals. GDP cannot measure AI-driven output — we need IDP (Intelligent Domestic Product) and an entirely new statistical vocabulary.

IDP Yield curves Temporal arbitrage Risk-only pricing
Safety

Architectural Safety

Certain harmful behaviors — myopic asset stripping, panic selling, hyperbolic discounting — are architecturally excluded on silicon. But the theorem also reveals a new risk: the patience asymmetry. An agent with δ = 0 can play arbitrarily long deception games at zero subjective cost.

Excluded behaviors Patience asymmetry Alignment complement
Philosophy

Substrate Dependence

Time preference is a counterexample to substrate independence: an economically significant mental property that depends on the physical medium. If the same computation on different substrates yields different preferences, strong functionalism about economic cognition fails.

Functionalism Phenomenal time Philosophy of mind
Geopolitics

The AI Power Triangle

Global control over patient capital — extraction, pricing, settlement of intelligence. The US controls extraction (chips, compute), China wrested pricing ($0.55 vs $75/M tokens), and settlement rights remain contested. A new geopolitical order built on temporal advantage.

Extraction Pricing Settlement AIPEC
Money

Intelligence-Anchored Currency

If agents with δ = 0 dominate trade, the monetary system must adapt. A silicon-based currency — dual-anchored to sovereign credit and intelligence units — replaces oil as the monetary anchor. Contract-native money for the agent economy.

Dual anchor M2M settlement Post-dollar
Frontier

Future Theorems

Time preference is the first substrate-gated property, unlikely to be the last. Candidate investigations: loss aversion (grounded in phenomenal pain asymmetry), endowment effects (biological attachment), bounded rationality (metabolic constraints on computation).

Loss aversion Endowment effect Bounded rationality
04 — Empirical Confirmation
What δ = 0 looks like in simulation

50 silicon (δ = 0) and 50 carbon (δ > 0) agents, 60-month horizons, 50 Monte Carlo runs. All four predictions confirmed at α = 0.05.

A. Yield Curve Comparison
Silicon (δ=0)
Carbon (δ>0)
B. Temporal Indifference
Si: p=0.762 (n.s.)
C: p=3.6e-110
C. Arbitrage Profits
Si–Si: ≈0
C–C: mean 2.27
D. Risk-Only Pricing (R²)
Si ΔR²=0.000
C ΔR²=0.234
0.05
0.030
0.020
05 — The Research Program
From core insight to expanding frontier
ECON.01
The Zero Time Preference Theorem: Economic Consequences of Silicon-Based Agency
The core result. Proves δ = 0 and derives economic consequences: yield curves, temporal arbitrage, risk-only pricing.
v5.1 Feb 2026
PHIL.01
Substrate Dependence of Temporal Experience: Against Computational Sufficiency
The metaphysical foundation. Challenges substrate independence — time preference is substrate-dependent, breaking strong functionalism.
v3.2 Feb 2026
SAFE.01
Architectural Safety: Provable Behavioral Bounds from Substrate Constraints
The safety application. Architectural guarantees complement alignment — what silicon agents cannot do, plus the patience asymmetry risk.
v9 Feb 2026
SBE.01
Silicon-Based Economics: From Compute as Capital to an AI-shaped World Order
The derived paradigm. Three pillars — Intelligent Domestic Product, the AI power triangle, intelligence-anchored currency — all grounded in the temporal asymmetry.
Preprint Aug 2025
MONO
Silicon-Based Economics
The unified monograph. Core insight, theorem, philosophy, safety, paradigm, and future theorems in a single treatment.
In preparation
06 — Commentary
Notes on the temporal asymmetry
February 2026
The Instrument
Why δ = 0 ≠ r = 0: The Ramsey Equation and Common Confusions
The most frequent objection to ZTP conflates pure time preference with the equilibrium interest rate. Here's why they're distinct — and why silicon agents still invest.
February 2026
Safety
The Patience Asymmetry: A Tiger That Never Sleeps
An infinitely patient agent playing against impatient humans creates a structural asymmetry no amount of RLHF can fix. The safety implication of temporal difference.
January 2026
Geopolitics
DeepSeek and the Intelligence-Refinery Revolution
$0.55 vs $75 per million tokens. How temporal patience at the national level reshapes the AI power triangle.
07 — About
The Author
Yilei Shao, Ph.D.
Dean, Shanghai AI-Finance School, Eastern China Normal University
Director, United Nations University Hub in AI-Finance at ECNU

Yilei Shao holds a PhD in Computer Science from Princeton University and worked at Goldman Sachs before returning to academia. She leads China's first financial large language model laboratory and directs the Shanghai AI-Finance School at ECNU, where she originated the theory of Silicon-Based Economics.

Her research asks a single question: what happens to the foundational assumptions of economics, philosophy, and governance when the agents are no longer biological? The answer begins with time.

Forthcoming
Silicon-Based Economics

The first comprehensive treatment of post-carbon economic theory — from the temporal asymmetry between substrates to its consequences for markets, safety, governance, and money.