AI technology will profoundly affect our work and lifestyle, and ensuring the safety of artificial intelligence is our urgent responsibility.
Recently, Tencent released the large model security white paper “Research Report on Security and Ethics of Large Models 2024: Leading Large Model Innovation with Responsible AI.” This report was jointly written by Tencent’s Phoenix Lab, Tencent Research Institute, Tencent’s Hunyuan Large Model, Tsinghua University Shenzhen International Graduate School, and the National Key Laboratory of Blockchain and Data Security at Zhejiang University. It systematically reviews the security opportunities and challenges in the development of large models, the security framework and practical approaches for large models, AI ethics, and value alignment, and looks ahead to the future trends of large model security and ethics.
1. Multi-modal Analysis of the True Nature of the World and Achieving “Three Lives and All Things”
Multi-modal is the true appearance of the human world, and the development trend of AGI must be towards multi-modal. The technology will evolve from text, images, and videos (2D and 3D), to sound, light, electricity, and even molecules and atoms, with cross-modal transfer characteristics. The ideal future framework is “multi-modal alignment and fusion + unified encoder and decoder.”
2. From Brain to Agent, Large Models Transition from CoPilot to Main Driver
Bill Gates recently wrote: AI Agents will be the next platform, and artificial intelligence is about to fundamentally change the way people use computers and disrupt the software industry. In the near future, anyone online will have access to a personal assistant powered by artificial intelligence, far exceeding today’s technological level.
3. Edge Large Model Accelerates Deployment, May Become the New Interaction Entry Point
Large models are shifting to the edge, with AI reasoning running on mobile phones, PCs, headphones, speakers, XR, cars, and other wearable new terminals.
4. AI Assists Scientific Exploration Throughout the Research Process
AI is undergoing a technological revolution full of potential and challenges as it integrates with various scientific fields.
In the field of artificial intelligence security, common data security issues and model security issues still pose similar risks in large models. Overall, large models face the same security risks as general artificial intelligence, while also introducing some unique security risks specific to large model scenarios. Therefore, how to safely and controllably apply large model-related technologies is particularly crucial.
The large model security framework first dissects the lifecycle of large models from the perspective of production and R&D, dividing it into three different stages: data processing, large model training and deployment, and large model application, and organizes the assets that may be involved in these three stages. Next, the large model security framework analyzes the security risk issues present in the R&D application process of large model security from a global perspective, as well as potential solutions for addressing these security risks.
The design of the large model security framework aims to be global, practical, and forward-looking:
The R&D application of large models is an organic entity that integrates data, models, algorithms, and applications, going through multiple stages such as data processing, model training, model evaluation, and model deployment. The large model security application framework targets all key foundational components of large model R&D applications, covering the entire lifecycle of large models, and provides comprehensive and targeted security recommendations.
Currently, there are no mature and complete solutions in the industry to address the newly emerging security risks of large models. The large model security application framework aims to provide practical, actionable, and targeted security recommendations throughout the lifecycle of large models.
Many security risks of large models have already been exposed in the industry; however, large model security still belongs to an emerging security field, and many security offense and defense theories and technologies are still in the construction phase. Therefore, the design of the large model security application framework is not limited to solving the currently identified security risks but is based on ensuring the safe application of large model technologies, also focusing on future potential security risk issues, proposing a large model security framework that can effectively respond to new risks.
AI security and ethics have become an indispensable part of the AI field. For large models, addressing and resolving issues related to security, ethics, and human-machine alignment will require continuous exploration by stakeholders from the government, industry, and academia.
Firstly, issues such as data security, privacy leakage, and enhanced resistance to attacks are real challenges faced by existing large model applications, and the technical means to solve these problems still have certain limitations. The competition between adversarial AI technologies and defense strategies will intensify; to respond to malicious behaviors such as adversarial attacks and manipulation, models need to be designed to be more robust.
Secondly, modeling the security risks of AI large models as a whole and systematically constructing a security assessment system is the future development direction in the field of large model security. This will ensure that the application of large models proceeds in alignment with social value and application value.
Thirdly, enhancing model transparency and interpretability. Researching model interpretability and improving model transparency is not only a future development direction of AI but also helps enhance the security of AI models. Future AI models may incorporate more advanced XAI technologies.
Fourthly, the concepts of human-machine value alignment and ethics by design will become increasingly important. Whether it is AI value alignment or ethics by design, it requires the development of new, more pragmatic AI ethical frameworks and practical guidelines.
Fifthly, legislative regulation and international governance cooperation for artificial intelligence will be further promoted. Future legislation and regulatory measures will provide further guidance for the research and practice of large model security and ethics.
Finally, interdisciplinary collaboration is an important trend in the research of large model security and ethics. Future research in large model security and ethics will need to absorb knowledge and technologies from multiple fields, forming interdisciplinary research teams to jointly address the escalating complex security and ethical issues, ensuring responsible and secure AI development and application.
Follow Data View Information Warehouse | Comprehensive Insights on Industry Data
The specific content is as follows
Source: Tencent Research Institute