Physical Scientists, All Other

Physical scientists (for example, astrophysicists or materials scientists) often work with complex experiments and huge amounts of data. Today, AI tools are beginning to help with the routine parts of this work. For example, one report notes AI algorithms can quickly analyze vast scientific data sets and spot patterns that humans might miss ^[1].

In the laboratory, smart robotic systems powered by AI can run many simple experiments with high precision around the clock ^[1]. These tools speed up work and free scientists to focus on big ideas. Importantly, people still guide the research.

Reviews stress that AI doesn’t replace the researcher: humans decide what problems to study and how to interpret results ^[2]. In fact, an OECD study observes that AI is aiding every stage of research – from designing experiments to writing papers – but scientists remain curious and creative. Many researchers see AI as a helpful assistant: solving one question often leads them to ask many more ^{[3] [3]}.

Whether labs adopt AI fast or slowly depends on costs and needs. Right now, advanced “robot labs” and AI systems are expensive and require special skills to use ^[2]. This means only larger research projects can afford them at first.

However, experts note the costs are falling and the technology is getting easier to use ^[2]. Another factor is that some tasks are simply hard to automate. Picking what experiment or question to do next often depends on judgment and unstructured information (like reading many papers or talking to experts), which AI cannot easily handle ^[2].

Even planning one experiment can involve so many choices that it becomes extremely hard for computers to try them all ^[2].