Artificial intelligence is changing the way scientific and technical work is carried out. From analysing large datasets to supporting research, automating processes and assisting with complex scientific tasks, AI is becoming another tool in the professional toolbox. But as AI becomes increasingly capable, an important question needs to be asked:
Does professional judgement still matter? For scientific and technical professionals, the answer increasingly depends on how we use AI – not simply what it can do. Artificial intelligence is changing the way scientific and technical work is carried out. From analysing large datasets to supporting research, automating processes and assisting with complex scientific tasks, AI is becoming another tool in the professional toolbox.
But there is an important distinction between using AI and understanding how to use it responsibly.
That was a key theme of the Science Council’s Entwined Evolution of AI and the Science Workforce summit, which brought together representatives from across the UK science and research community to consider how AI is changing the workforce and the skills professionals will need. The message is increasingly clear: AI literacy is becoming part of being a modern science and technical professional.
There is an understandable temptation to treat an AI-generated answer as authoritative simply because it looks convincing. For scientific and technical professionals, that isn’t enough. AI-generated outputs still need to be questioned, checked and understood in context. Is the underlying data reliable? Could there be bias in the model or dataset? Are the results reproducible? Has the system been used for the right purpose? And, perhaps most importantly, does the result make sense from a scientific or technical perspective? These are professional judgement questions, and they remain the responsibility of people.
The technician’s role is changing too
AI discussions often focus on scientists, researchers and data specialists. But technical professionals are equally important. Technicians are frequently the people who generate, prepare, validate and manage the data that scientific systems depend upon. They operate equipment, maintain processes, monitor quality and understand the practical realities behind the numbers.
As AI becomes embedded in these workflows, technical professionals may increasingly need to understand not only how a system works, but also how to recognise when its output should be questioned. That could mean developing knowledge around data quality, model limitations, verification, bias and appropriate use.
It doesn’t mean every technician needs to become an AI developer. It means having enough understanding to remain an informed professional in an increasingly AI-enabled workplace.
There is another challenge.
If AI can produce an answer instantly, how do early-career professionals develop the knowledge and judgement that comes from working through problems themselves? Automation can undoubtedly remove repetitive work and improve productivity. But some of the tasks that appear inefficient can also be valuable learning opportunities. The challenge is therefore finding the right balance. AI can support learning and professional practice, but organisations need to make sure that developing professionals still have opportunities to experiment, investigate, make decisions and learn from mistakes.
This is where professional development becomes particularly important.
Scientific and technical professionals have always had to keep learning. New instruments, standards, techniques and technologies continually change the way work is done. AI is another part of that evolution.
For professionals, this means continuing to develop technical knowledge while also building the judgement needed to use new technologies appropriately.
For employers, it means recognising that AI adoption isn’t simply a technology investment.
Professional recognition for a changing workforce
Professional registration provides one way of demonstrating that technical and scientific professionals are maintaining their competence as their roles evolve.
Through the IST, professionals can work towards the Science Council’s three professional registers:
- Registered Science Technician (RSciTech), recognising competent technical professionals applying scientific knowledge and skills in practice.
- Registered Scientist (RSci), recognising professionals working with greater autonomy, responsibility and professional judgement.
- Chartered Scientist (CSci), recognising senior scientific professionals and leaders demonstrating high-level expertise, strategic responsibility and professional impact.
The pathway reflects an important principle: professional competence isn’t static.
As responsibility increases, so does the expectation for autonomy, judgement, accountability and continued professional development. In an AI-enabled world, that principle becomes even more relevant. The technology may change quickly, but the need for people who can understand, question and take responsibility for the work they do remains.
Source & further reading
sciencecouncil.org – Science Council, The Entwined Evolution of AI and the Science Workforce: Shaping the Future.
Professional registration through the IST: The Institute of Science & Technology is licensed by the Science Council to award RSciTech, RSci and CSci.
IST STEMM Professional Registers
IST RSciTech: Registered Science Technician