Why do you care about AI Existential Safety?

With the continuous deployment of new large language models and large vision-language models that demonstrate human-level or even superhuman language processing capabilities, I become increasingly concerned about our lacking understanding of these models. How should we interpret the model behaviors? Do the models adopt cognitive processes similarly to humans? Can we still reliably distinguish between human-generated and AI-generated content? What can we do to prevent AI systems from misleading humans? I aim to contribute technical innovations that help answer these questions.

Please give at least one example of your research interests related to AI existential safety:

My research interests lie in computational linguistics and natural language processing, where I use computational models to deepen our understanding of natural language, the human language processing mechanism, and how these insights can inform the design of more efficient, effective, safe, and trustworthy NLP and AI systems. Particularly, my focus has been on grounded language learning, linking language with real-world contexts across various modalities.

Currently, we lack a thorough understanding of the cognitive processes underlying both human and machine language comprehension. To address the problem, my past has been in the following lines, which I will continue pursuing in the future:

• Benchmarking and analyzing the behavioral similarities and differences between humans and AI systems in various complex reasoning tasks.
• Understanding AI system behaviors by finding the accountable intermediate representations.
• Enhancing the faithfulness of AI systems by linking language to real-world knowledge and multi-modal contexts.