Human-AI Cooperation in Education: Human in Loop and Teaching as leadership

Using the differences and complementarities between human intelligence and artificial intelligence(AI),a hybrid-augmented intelligence,that is both stronger than human intelligence and AI,is created through Human-AI Cooperation(HAC)for teaching and learning.Human-AI Cooperation is infiltrating into all links of education,and recent research has focused a lot on the impact of teaching,learning,management,and evaluation with Human-AI Cooperation.However,AI still has its limits of intelligence,and cannot cooperate as humans.Thus,it is critical to study the obstacles of Human-AI Cooperation in education,as AI plays a role as a partner,not a tool.This study discussed for the first time how teachers and AI cooperate based on Multiple Intelligences of AI proposed by Andrzej Cichocki and puts forward a new Human-AI Cooperation teaching mode:human in the loop and teaching as leadership.It is proposed that humans in the loop and teaching as leadership can solve the problem that AI cannot cope with complex and dynamic teaching tasks in open situations,as well as the limits of intelligence for AI.

Chatbots:a critical look into the future of the academia

Like every other societal domain,science faces yet another reckoning caused by a bot called ChatGPT(Chat Generative Pre-Trained Transformer).ChatGPT was introduced in November 2022 to produce messages that seem like they were written by humans and are conversational.With the release of the latest version of ChatGPT called GPT-4,and other similar models such as Google Bard,Chatsonic,Collosal Chat,these chatbots combine several(about 175 billion)neural networks pre-trained on large Language Models(LLMs),allowing them to respond to user promptings just like humans.GPT-4 for example can admit its mistakes and confront false assumptions thanks to the dialogue style,which also enables it to write essays and to keep track of the context of a discussion while it is happening.However,users may be deceived by the human-like text structure of the AI models to believe that it came from a human origin[1].These chatbot models could be better,even though they generate text with a high level of accuracy.Occasionally,they produce inappropriate or wrong responses,resulting in faulty inferences or ethical issues.This article will discuss some fundamental strengths and weaknesses of this Artificial intelligence(AI)system concerning scientific research.