Quarterly Review: How AI Transformed Between April and June 2024

Key Takeaways in 3 Points

• Generative AI enters classrooms: Research on its use in schools surged from 12 to 68 articles in three months, with tools to personalize learning.
• Robots become more autonomous: Studies on machines capable of acting without human intervention (Autonomous Agents) doubled, rising from 45 to 92 articles.
• AI steps into human shoes: Work on simulating human behavior (Human Behavior Simulation) exploded (+320%) to test social or medical scenarios.

AI in Schools: A Growing Presence, Not Without Debate

Researchers are exploring how AI tools, such as chatbots or exercise generators, can assist teachers. Some articles show how these technologies adapt lessons to each student’s pace by identifying their difficulties in real time. Others highlight the risks: screen dependency, biases in responses, or the loss of critical thinking. Studies are also multiplying on teacher training, ensuring they can use these tools without being replaced by them. Why does this matter in practice? Because it could reduce inequalities among students—provided these technologies are properly regulated to avoid widening gaps.

Robots That (Almost) Make Their Own Decisions

Machines capable of acting without step-by-step instructions (Autonomous Agents) are increasingly fascinating scientists. This quarter, articles on the topic nearly doubled. Some describe robots that plan their tasks, like a mechanical arm tidying a room without detailed guidance. Others explore systems that negotiate among themselves, such as autonomous cars coordinating to avoid traffic jams. Researchers are also testing limits: What happens if these agents make decisions contrary to human expectations? Why does this matter in practice? Because it could revolutionize factories, transportation, or even emergency response, making machines more responsive—but also more unpredictable.

AI Pretends to Be Human, to Better Understand Us

Simulating human behavior (Human Behavior Simulation) has become a hot topic: publications on the subject quadrupled. Some work uses AI to replicate realistic conversations, like a virtual patient responding to a trainee doctor’s questions. Others model crowds to anticipate panic movements during a concert or sports event. Researchers also use it to test public policies, such as the impact of a tax on consumption habits. Why does this matter in practice? Because it allows risk-free experimentation, whether for training professionals, designing safer cities, or predicting the effects of a reform.

Further Reading

• Generative AI in Education: A Systematic Review → An overview of AI tools transforming schools, with their promises and pitfalls.
• Autonomous Agents for Real-World Task Planning → How robots learn to organize their actions without human help, with concrete examples.
• Simulating Human Behavior in Crisis Situations → A study on AI replicating crowd reactions in emergencies to better prepare responders.
• Ethical Risks of Human-Like AI in Education → An article warning about the dangers of overly "human" chatbots in classrooms.

Next quarter, we’ll be watching whether debates on AI in schools lead to concrete recommendations and if autonomous robots move from labs to real-world testing.