Glossary

A software system that uses AI to pursue goals with some autonomy — perceiving, planning, using tools, and acting over multiple steps. In the machine economy, the entity that holds a wallet and transacts.

Reconstructing a data series' historical values so a new metric or definition has comparable back-data. Distinct from the futures-planning sense — and, for on-chain data, often exact rather than estimated.

The difference between the MEI's arithmetic and geometric averages, published alongside the headline. It quantifies how much the index is being held back by imbalance among the four rails.

Holding a metric's last known value when a fresh one isn't yet available, flagged as stale — never fabricated, never dropped. In the MEI, the rule also forbids the one shortcut that would flatter the index.

A single summary measure built by combining several indicators, used to represent a multidimensional concept no single metric captures. Inherently shaped by methodological choices, which is why transparency matters.

The degree to which a metric actually measures the concept it claims to, rather than something else. The MEI operationalizes it through a "freeze test" that every metric must pass to enter the index.

Assigning the same weight to every component of a composite index — a transparent default that declines to assert one component matters more than another, rather than hiding a judgment inside arbitrary numbers.

An average found by multiplying values and taking a root rather than adding and dividing. It penalizes imbalance — a very low component pulls the whole result down — which is why it suits indices whose parts are complements.

A conceptual analogy — the idea of measuring total autonomous-machine economic output the way GDP measures a national economy. No one credibly computes it, and the MEI deliberately does not claim to.

A direct exchange of data or value between two devices or software agents, with no human approving the individual exchange. The definitional core of the machine economy.

An open standard, introduced by Anthropic, that gives AI agents a universal interface for connecting to external tools, data, and services — the "USB-C port" for AI integration.

MachineEconomy.ai's composite index measuring the health, scale, and maturity of the machine economy on a single 1–100 scale — built from four equally weighted components (three infrastructure rails plus realized demand) combined with a geometric mean, and published on a versioned methodology.

A part of the machine economy the MEI's framework calls for but has no verifiable metric to measure — so the platform discloses it publicly as a limitation rather than filling it with an unreliable proxy.

Rescaling indicators measured in different units onto a common scale so they can be combined. The choice of method and bounds shapes the result — which is why the MEI publishes its bounds and uses a unit-invariant method.

A metric that is published but temporarily excluded from the MEI while its normalization bounds are being calibrated from real data. It joins the composite only once its calibration window closes.

Saturation is when a metric pins at the top of its scale and stops registering growth; rebasing resets the scale to fix it. How rebasing is governed — especially on the downside — is what separates an honest index from a tunable one.

MachineEconomy.ai's analytical model for the machine economy — organizing machine economy infrastructure into three interdependent rails: Payment (how machines pay), Physical (what machines run on), and Legal (what machines are allowed to do).