'The future of work and skills needed to thrive in AI'

AI can automate mundane and time-consuming processes and at the same time it can delve into data and process multiple data sources faster and more efficiently, AI techniques can also uncover hidden patterns and draw insights that humans may miss.

The impact of artificial intelligence just keeps increasing and universities are perfectly placed to unlock its potential and think through its long-term implications.

There is no doubting the growing influence of AI. Every day, the media reports on another innovative application of AI or makes another incredible prediction for AI in the future. We are seeing AI disrupting almost every sector – from helping to diagnose cancer to making public services more efficient and tailor-making insurance products.

The reason we are seeing this is that almost every type of organisation can benefit in one way or another from the use of AI. Used in the right way AI can improve operations and increase efficiency, meaning businesses who understand how to apply it effectively can expand market share, diversify product portfolios and reach new markets.

AI can automate mundane and time-consuming processes and at the same time it can delve into data and process multiple data sources faster and more efficiently, AI techniques can also uncover hidden patterns and draw insights that humans may miss.

The sheer volume of data it can process is incredible and growing, but it also can simplify processes such as sifting through client data. Meanwhile, in some industries, such as managing nuclear waste, there are huge advantages of reducing risks to humans by utilising AI.

University academics are at the absolute cutting edge of AI and its applications. Many are also working with companies to develop services and products across all sectors so can often give students valuable insights into the newest and future use of AI.

Students have a fantastic opportunity to join the AI revolution by developing the right technical and soft skills. I think we will need three types of graduates in the future and students thinking about their courses should think about their skills, strengths and interests while also carefully considering how their course will connect with the career they aspire to.

The first group of graduates will be developing the next generation of AI and data science techniques, these graduates need to have the specialist skills and detailed background knowledge to develop new methods.

The second group, will be able to apply their knowledge in different domains and have high-level understanding of techniques. There knowledge and experience of different domains means they can apply the correct techniques given a domain of application or the problem at hand. They need not have studied computer science or artificial intelligence in detail, but need to have sufficient understanding of underlying principles so they can apply the right technique to the right problem.

The third group will be domain experts who can utilise results to create reports on new products and services, and make strategic decisions. Their understanding of AI means they will be able to interpret and communicate complex insights to diverse audiences, using data visualisation where needed.

Universities need to rise to the challenge by adapting their curricula and their educational approach to the demands of AI. They should think carefully about developing courses that develop skills for the three groups I’ve described.

There will always be a need for specialist programmes on AI, related fields and the application of AI. With the need for AI skills growing we will also need conversion programmes for students who did not study AI initially, but recognise its importance or see its relevance to their sector in the future.

AI is becoming essential in almost all careers, so universities need to extend their support around AI much further than ever before. I think this means universities need to seriously consider offering data literacy courses for all students regardless of specialisation. This could possibly be in the form of shorter courses which raise awareness of the use of data and AI techniques as a first step.

Alternatively, universities can look to inject data visualisation and other relevant AI skills into courses. This would be particularly valuable in courses where making sense of large amounts of data using AI can offer significant benefits such as  business, finance and management, but could be advantageous in almost all industries.

Universities could consider introducing a module or short course (either online or self-taught) that any student can take in any course to raise awareness of techniques and improve data literacy. This should also include relevant content about the implications of using data science and AI in decision-making so students understand the ethical considerations of developing AI-powered solutions.

Universities are also well-placed to provide critical support for lifelong learning and upskilling so workers can stay up-to-date with AI advancements. With AI developing so rapidly, there is likely to be a great deal of enthusiasm for short courses, CPD and other provision including online learning. So professional level qualifications and flexible CPD and executive education options also need to be developed to upskill professionals at all levels.

Students choosing to take advantage of the opportunities offered by universities which are fully engaged with AI to develop their skills and knowledge will be ideally placed for their future career. Developing your AI knowledge might even help you shift career as AI becomes increasingly important in a range of industries and offers you a competitive advantage across healthcare, the public sector and business.

 

By- Professor Maria Fasli, Vice Chancellor- University of Essex