NDAI Agreements
Matthew Stephenson, Andrew Miller, Xyn Sun, Bhargav Annem, Rohan, Parikh

TL;DR
This paper proposes that trusted execution environments combined with AI agents can effectively solve the longstanding problem of inventors needing to disclose ideas without risking expropriation, thus enabling efficient innovation and collaboration.
Contribution
It introduces a novel model where TEEs and AI agents facilitate secure disclosure, fully or partially, improving upon traditional NDA challenges in innovation economics.
Findings
TEEs enable full disclosure without expropriation risk
Partial disclosure still improves outcomes when TEEs are limited
Budget caps and thresholds maintain efficiency gains despite AI imperfections
Abstract
We study a fundamental challenge in the economics of innovation: an inventor must reveal details of a new idea to secure compensation or funding, yet such disclosure risks expropriation. We present a model in which a seller (inventor) and buyer (investor) bargain over an information good under the threat of hold-up. In the classical setting, the seller withholds disclosure to avoid misappropriation, leading to inefficiency. We show that trusted execution environments (TEEs) combined with AI agents can mitigate and even fully eliminate this hold-up problem. By delegating the disclosure and payment decisions to tamper-proof programs, the seller can safely reveal the invention without risking expropriation, achieving full disclosure and an efficient ex post transfer. Moreover, even if the invention's value exceeds a threshold that TEEs can fully secure, partial disclosure still improves…
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Taxonomy
TopicsIntellectual Property and Patents · Auction Theory and Applications · Blockchain Technology Applications and Security
