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Conceptual framework outlines the economic and legal impacts of synthetic media on human identity, highlighting new liability models for artificial intelligence attribution.
Description This working paper introduces the Human Presence Economy — a framework for examining how artificial intelligence is changing the economics of human representation. As synthetic reproductions of voices, faces, writing, expertise, and identity become abundant, inexpensive, and increasingly convincing, this paper proposes that certain attributes of authenticated human reality — verified identity, physical presence, lived experience, accountable authorship, and provenance — may become comparatively scarce, and therefore economically significant in new ways. The paper argues this shift creates a second-order problem: when a synthetic representation can plausibly speak, act, or decide on a person's behalf, the operative question is no longer simply whether AI generated the content, but who was represented, who authorized it, who deployed it, who relied on it, and who bears responsibility when the chain of attribution fails. To address this, the paper introduces a preliminary analytical architecture — including the Human Scarcity Principle, Human Presence Premium, Decision Provenance, and an eight-layer Human Reality Liability Architecture (Creation, Identity, Authorization, Deployment, Reliance, Consequence, Harm, Control) — and sets out the Global AI Liability Consortium's (GAILC) proposed 2026–2036 research program: conceptual development, sectoral mapping, measurement, liability mapping, and institutionalization. This is a foundational position paper and research-program statement, not an empirical study. Its constructs are deliberately provisional, offered as hypotheses for testing rather than validated findings or established legal doctrine. The paper states explicit conditions under which its central thesis could be weakened or falsified, and identifies its intellectual debts to prior work on authenticity and experience economics, media theory, and deepfake liability scholarship. Its purpose is not to conclude this inquiry, but to establish where GAILC's decade-long research program begins.
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Deusdedit Ruhangariyo (2026) studied this question.
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