保密信息喂养AI，是保护还是反噬？

Core Viewpoint - The article discusses the challenges and implications of using trade secret law to protect AI innovations, highlighting the tension between the need for innovation protection and the demand for transparency in AI technology [1][5][14]. Group 1: Trade Secret Law and AI Protection - The U.S. Patent and Trademark Office and Copyright Office have issued guidelines limiting patent and copyright protections for AI-generated innovations, making trade secret law a crucial tool for protecting AI-related innovations [1]. - Trade secret law offers broad protection for sensitive information related to AI, such as training data and model weights, which are not covered by patents or copyrights [1][5]. - The application of trade secret law in AI faces challenges, including insufficient technical transparency and potential misuse of legal protections [5][6]. Group 2: Ethical and Social Implications - The rapid development of AI creates a conflict between the insatiable demand for data and the need for transparency, potentially leading to ethical and social issues [2]. - The use of confidential data to train generative AI (GenAI) has been deemed illegal in multiple jurisdictions, posing irreversible leakage risks [3][4]. - High-profile cases, such as data leaks involving major companies, underscore the risks associated with using public AI tools with sensitive data [4]. Group 3: Transparency and Governance Challenges - The "black box" nature of AI technology conflicts with the need for transparency, particularly in high-stakes areas like healthcare and justice, which could lead to severe consequences [6][9]. - The expansion of trade secret protections can lead to monopolistic practices, limiting competition and innovation, particularly disadvantaging small and medium enterprises [7][13]. - A lack of transparency in AI systems can erode public trust and obscure the risks of technology misuse [7][9]. Group 4: Recommendations for Balancing Interests - To mitigate the negative effects of trade secret law on AI innovation, it is essential to redefine its boundaries, ensuring it only covers genuinely valuable and non-public information [13][14]. - Implementing mandatory transparency requirements and establishing a tiered disclosure system for high-risk AI applications can help balance corporate interests with public needs [10][11]. - The introduction of a compulsory licensing system in emergencies can ensure that critical AI technologies serve public interests while providing fair compensation to developers [10][14].