Policy Regulation of Artificial Intelligence: A Review of the Literature

Abstract

With the all-round penetration of new AI technologies into human society, the necessity of policy regulation is becoming more and more prominent. A review of the research results on policy regulation of AI in the West from 1992 to 2020 reveals that: the research on AI policy regulation is still in its initial stage, and researchers mostly use law, political science and management science as their research perspectives to enter the topic, and the research fields are becoming more and more diversified, but not closely connected; The research topics are still at the level of philosophical value and contingency, specifically, the value judgment of policy regulation, procedural mechanism, and ethical issues of medical application, and there are controversies among different scholars, but a basic consensus has been reached on the ethical concerns and regulatory necessity of AI. The future research trends of policy regulation of AI mainly include three aspects: multi-discipline, implementation and diffusion of policy regulation, and ethical reflection.

How Multimodal can Predict Human Judgment

“…This article is trying to explore how multimodal can evaluate creativity achievement. When it comes to innovation judgment, participants may suffer from imagining the right product by simply reading the text, now this research, giving participants images, can help them better understand what the real product is, while previous studies only focus on language (Du, M. 2023), now multimodal gain more information, and it can judge the product better as well. Moreover, we investigate how multimodal can predict marketing research outcomes by using computer vision reasoning (Karpathy, A., & Fei-Fei, L. 2015, Krishna, R., et.al 2017.…”

“…The generative AI has grow rapidly, past research shows that large language model has passed Theory of mind test (Trott, S., Jones, C., Chang, T., Michaelov, J., & Bergen, B. 2023), overcoming intuition (Hagendorff, T., Fabi, S., & Kosinski, M. 2023) and judging innovation funding (Eapen, T. T., Finkenstadt, D. J., Folk, J., & Venkataswamy, L., Du, M. 2023). Recently, some large language models added a computer vision function to them, make it multimodal.…”

“…Pattern recognition is not only a term used in computer vision, psychologists (Tversky, A. & Kahneman, D. 1983) found that people find patterns in words, such as the classic "Linda Problem", and GPT-4 can solve this now (Du, M. 2023).…”