国广清科：苹果和迪士尼的股东大会——人工智能与隐私问题的新挑战

随着科技的快速发展，人工智能(AI)已经成为我们日常生活和工作的一部分。然而，随着其应用的不断扩大，AI的隐私问题也引起了越来越多的关注。最近，苹果和迪士尼在股东大会上的事件，再次引发了这一问题的讨论。

With the rapid development of technology, artificial intelligence (AI) has become a part of our daily lives and work. However, as its applications continue to expand, the privacy implications of AI have become increasingly concerning. Recently, events at the shareholders' meetings of Apple Inc. and Disney have once again sparked discussions on this issue.

美国劳工联合会的养老基金工作人员要求苹果披露其使用AI的情况，并要求公司遵循一定的道德准则。他们提出，人工智能系统不应使用版权作品，包括专业演员的声音、形象和表演作为训练数据。他们还要求公司向创作者和版权持有者提供透明的信息，确保其权益得到维护。

Workers from the pension funds of the American Federation of Labor have requested that Apple Inc. disclose its use of AI and adhere to certain ethical guidelines. They argue that AI systems should not use copyrighted works, including the voices, images, and performances of professional actors, as training data. They also demand that the company provide transparent information to creators and copyright holders to ensure their rights are upheld.

这一要求的核心是隐私权的问题。在AI的使用中，隐私权是一个不可忽视的问题。训练AI模型通常需要大量的数据，而这些数据往往涉及到个人的隐私信息。如何在利用数据的同时保护个人隐私，是当前面临的一大挑战。

The crux of this request is the issue of privacy. In the context of AI, privacy is a non-negligible concern. Training AI models typically requires vast amounts of data, often containing personally identifiable information. Balancing data utilization with privacy preservation is a significant challenge currently facing society.

苹果和迪士尼向美国证券交易委员会申请删除相关议题，理由是这涉及到“公司日常业务运营”。然而，美国证券交易委员会否决了这一动议，认为该提案是正常的商业事务，而非试图过度干预公司的经营。这一决定表明，监管机构对于AI的隐私问题持有严肃的态度。

Apple Inc. and Disney have applied to the US Securities and Exchange Commission to delete relevant topics, citing that they involve "routine business operations." However, the SEC has rejected this motion, stating that the proposal is a normal business matter rather than an attempt to unduly interfere with company operations. This decision indicates that regulatory agencies take a serious stance on the privacy implications of AI.

隐私问题的复杂性在于，如何在推动技术进步的同时，确保个人隐私不受侵犯。这需要技术开发者、政策制定者和公众共同参与讨论和制定解决方案。此外，随着AI技术的进一步发展，我们可能需要更新和调整现有的法律和道德框架，以适应新的挑战。

The complexity of privacy issues lies in balancing technological progress with ensuring individual privacy is not infringed upon. This requires the joint participation of technology developers, policy makers, and the general public in discussing and devising solutions. Furthermore, as AI technology continues to advance, we may need to update and adapt existing legal and ethical frameworks to address new challenges.

在隐私计算出现之前，数据隐私的保护主要依赖于传统的加密技术和匿名化处理。然而，随着大数据和人工智能的快速发展，这些方法已经无法满足新的隐私保护需求。因此，为了在保护个人隐私的同时实现数据的有效利用，隐私计算技术应运而生。它通过一系列的算法和技术，允许在保证数据隐私的前提下进行数据处理和分析。例如，差分隐私是一种常用的隐私计算方法，通过添加噪声来保护用户的隐私信息。同态加密则可以在不解密的情况下对数据进行计算并得到加密结果，从而保护原始数据的隐私。这些技术的出现为平衡数据利用和隐私保护的需求提供了更多可能性。

Prior to the emergence of privacy-preserving computation, data privacy was primarily dependent on traditional encryption techniques and anonymization processes. However, with the rapid development of big data and AI, these methods have become insufficient for meeting new privacy preservation requirements. Therefore, privacy-preserving computation techniques have emerged to facilitate data utilization while protecting privacy. These techniques utilize a range of algorithms and technologies that allow for data processing and analysis while ensuring privacy. For instance, differential privacy is a commonly used privacy-preserving computation method that adds noise to protect users' privacy information. Homomorphic encryption allows for calculations to be performed on data without decrypting it, thus preserving the privacy of original data. The advent of these technologies provides more possibilities for balancing data utilization and privacy preservation requirements.

我公司国广清科将利用自身在隐私计算领域的研发经验，深入探讨人工智能和隐私计算的平衡问题。我们认识到，人工智能和隐私计算并不是相互排斥的，而是可以相互促进的。通过合理的隐私计算技术应用，可以在保护个人隐私的同时，提高AI模型的准确性和可靠性。

Our company, CRI TSING'S TECH, will use its research and development experience in the field of privacy computing to explore the balance between artificial intelligence and privacy computing. We recognize that artificial intelligence and privacy computing are not mutually exclusive, but can promote each other. Through the application of reasonable privacy computing technology, it is possible to improve the accuracy and reliability of AI models while protecting personal privacy.

我们将积极探索如何利用隐私计算技术解决AI中的隐私问题。我们将研究差分隐私、同态加密等技术在AI领域的应用，并探讨如何平衡数据利用和隐私保护的需求。此外，我们还将关注国际上关于AI和隐私的最新动态和标准，积极参与相关讨论和制定工作。

We will actively explore how to utilize privacy-preserving computation techniques to address privacy concerns in AI. We will investigate the application of technologies such as differential privacy and homomorphic encryption in the AI domain, while also exploring ways to balance data utilization and privacy preservation requirements. Additionally, we will stay abreast of the latest developments and standards regarding AI and privacy on an international level, actively participating in relevant discussions and standard-setting efforts.

通过这些努力，我们希望为解决AI的隐私问题提供更多思路和方法，促进人工智能技术的可持续发展和社会信任的建立。同时，我们也呼吁更多的企业和研究机构加入到这一领域的研究和应用中来，共同推动人工智能和隐私计算的平衡发展。

Through these efforts, we hope to provide more ideas and solutions for addressing AI's privacy concerns, fostering sustainable technological development in artificial intelligence and establishing social trust. At the same time, we also call upon more enterprises and research institutions to join in this field of research and application, jointly promoting a balanced development between artificial intelligence and privacy-preserving computation.