As AI becomes more capable, it may automate tasks that were once the domain of early-career researchers: image analysis, data annotation, literature reviews, and even hypothesis generation. While this offers clear efficiency gains, it also poses ethical questions around job displacement, deskilling, and the nature of scientific training. Institutions should ensure that AI augments rather than replaces human expertise, and that researchers are trained to understand, question, and improve the tools they use. Teaching scientists to critically evaluate AI systems should be seen as part of ethical research training.
The future of Science with AI AI Ethics
Overcoming Fear and Resistance
Despite the transformative potential of AI in science, there remains a deep-rooted scepticism among many in the research community. Everything from unease to full resistance. Some of this stems from a broader public anxiety surrounding AI, doubtless fuelled by dystopian media narratives. Conspiracies surrounding surveillance and automation of human jobs have all contributed to an atmosphere of mistrust. But within the scientific community AI is not just unknown, but is seen by some as a threat to intellectual authority and the traditional way research has been conducted for decades.
This fear is grounded, however, as researchers have years or even decades of training and expertise under their belts. When an AI model can seemingly replicate or accelerate tasks that once required diligent labour or hard-won precision skills, there's a natural fear and rejection response. The concern is not just about technological change, but about professional identity and the perceived erosion of hard-earned skill and station.