NDAI Agreements

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 outcomes compared to no disclosure. Recognizing that real AI agents are imperfect, we model "agent errors" in payments or disclosures and demonstrate that budget caps and acceptance thresholds suffice to preserve most of the efficiency gains. Our results imply that cryptographic or hardware-based solutions can function as an "ironclad NDA," substantially mitigating the fundamental disclosure-appropriation paradox first identified by Arrow (1962) and Nelson (1959). This has far-reaching policy implications for fostering R&D, technology transfer, and collaboration.