As Innovation Lead for Precision Medicine at Innovate UK I am sometimes asked about the best STEM subjects to study, usually by parents wanting to help their children select the best university courses.
Something they’re really interested in, I have tended to say, but now add that something involving AI (Artificial Intelligence) might be a very wise choice.
Vital to future prospects for Precision Medicine
AI’s nothing new, but now seems on the verge of making a big impact in clinical settings, reflected in our competition applications in the area of precision medicine. Innovate UK has funded a lot of AI projects, not just in medicine but also areas such as:
Many roles for AI in medicine
There are many ways AI can play a role in the medical arena, where being able to find patterns and associations in large data sets is fundamental to developing new technologies and services.
These large data sets include disparate patient information, such as the increasing levels of genetic information we will have about patients, and linking it to phenotypic information (observable physical properties e.g. height, eye colour) and patient medical records.
AI and Precision Medicine
In my area of precision medicine, we are very interested in advanced diagnostics that allow us to understand the mechanisms causing a disease rather than just looking at the symptoms, allowing the most appropriate or personalised treatment to be selected.
Areas such as digital pathology are being revolutionised by using image analysis, a form of AI, to review patient scans to detect issues such as cancerous tumours. On top of this, machine learning can use the knowledge of thousands of experts to improve detection accuracy and process efficiencies.
So what is Artificial Intelligence?
AI is something of an umbrella term which includes areas such as machine learning (for example, deep learning which is based on neural networks), planning, computer vision and speech recognition.
The Engineering and Physical Sciences Research Council (EPSRC) defines AI as Artificial Intelligence technologies aim to reproduce or surpass abilities (in computational systems) that would require intelligence if humans were to perform them. These include:
- learning and adaptation
- sensory understanding and interaction
- reasoning and planning
- optimisation of procedures and parameters
- autonomy; creativity
- extracting knowledge and predictions from large, diverse digital data.
Essentially, it is about computers undertaking tasks that would normally be associated with animal (typically human) intelligence.
We need to be AI literate as well as expert
There is a need for the UK to produce more AI experts to drive the development of new AI techniques to be able to achieve better results in a wide range of industries. But there is also a need to develop the skills of people who can apply these AI techniques to specific area.
Experts in areas such as genetics will need to be able to understand and apply AI in their area to link genetic information to patient health records and outcomes in order to derive clinically actionable information. As such we are not just looking for new experts in AI, but AI should be taught to a much wider community that has an expertise in something where AI techniques could be applied.
STEM and AI
There will be a growing need for people working in STEM areas to be AI literate, similar to how we currently need to have basic computer skills and work with software packages such as MS Word and Excel.
Therefore, it is important to train new students with a particular interest in AI but also making sure training in AI goes much wider. It also means that those of us that went to university before there was an internet should consider learning more about AI.
Career path & current infrastructure
The UK now has around 1.6 million digital tech jobs and with the increase in AI activity the demand for talent is increasing beyond the level of supply. This means wages for experts in this area are set to increase in the short to medium term.
Expertise in AI is also a very transferable skill, leading to wider career development and growth options.
There are many ways to learn about AI, with increasing numbers of university courses, including PhDs, Masters and undergraduate courses.
There are an increasing number of courses for those who want to add skills to their current expertise, through such courses as MOOCs (massive open online course).
Don’t delay - take action today
So if you are a student thinking about what university course to take then AI or computer science (enabling specialisation in AI) might be worth considering. If you are looking to study another subject it might be worth looking at whether AI will play a role in the future of this subject, and whether there is an AI component to the course you want to do.
Even if you can only just remember your student days, there are many other options to expand your knowledge of how AI works and how it could be applied to your areas of expertise.
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