用可信执行环境与AI代理解决发明披露被窃取的难题。
NDAI Agreements
- 将披露和支付交给不可篡改的程序，避免信息被滥用。
- 完全披露可实现高效交易，即使价值超安全阈值也优于不披露。
- 对AI错误有容错机制，适合政策制定与技术合作场景。
我们研究创新经济学中的核心挑战：发明人需披露新想法以获得补偿或资金，但披露可能引发被侵占风险。本文构建一个卖方（发明人）与买方（投资者）在威胁持留（hold-up）下的信息商品谈判模型。传统情形下，卖方因规避侵占而隐瞒披露，导致效率损失。我们证明，结合可信执行环境（TEEs）与AI代理可缓解甚至彻底消除该持留问题。通过将披露与付款决策委托给防篡改程序，卖方可安全披露发明，实现完全披露与高效事后转移。即使发明价值超过TEEs可保障的阈值，部分披露仍优于完全不披露。考虑到真实AI代理存在误差，我们引入支付或披露错误模型，并证明预算上限与接受阈值足以保留大部分效率收益。结果表明，密码学或硬件解决方案可充当‘铁律式保密协议’，显著缓解Arrow（1962）与Nelson（1959）首次提出的披露-侵占悖论，对促进研发、技术转移与协作具有深远政策意义。
原文摘要 · Abstract (English)
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.
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