ILN Graduation: A Stepping Sto...
We recently celebrated the graduation of our Intensive Literacy and Numeracy (ILN) students at the Royal Oak campus.
Reflections on Four Decades in Artificial Intelligence
Kathiravelu Ganeshan
Senior Lecturer, Information Technology
A practical beginning
Ganeshan鈥檚 journey with AI began in 1983, when he enrolled in a master鈥檚 programme in the UK. From the start, his work was grounded in practical applications - detecting incipient faults in large machinery such as power turbines and aircraft engines and tackling complex optimisation and scheduling problems.
Over time, his research expanded into areas such as drowning prevention and using AI to support people living with Type 2 diabetes, with an emphasis on lifestyle-based interventions over pharmaceutical dependency.
Ganeshan also had the opportunity to meet several pioneers of AI and exchange ideas with them over informal meals. His postgraduate thesis, AI Applied to Machine Health Monitoring, stood among the early examples of AI being applied to heavy engineering systems. He recalls frequently presenting his research and even defending it in contentious forums.
鈥淚n one instance, I debated a senior faculty member (an expert in mechanical bearings) who dismissed my suggestion that AI would one day match or even exceed human intelligence. The Head of Department sided with him. I stood my ground and argued that AI could at least rival human performance in specific domains. They didn鈥檛 agree,鈥� says Ganeshan.
Now, more than four decades later, even Ganeshan is struck by how rapidly the field has progressed.
鈥淢y core belief, that AI has the potential to transform the world, has remained constant. What鈥檚 changed is the pace and scale of advancement, which have far exceeded even my most optimistic projections, particularly in the past few years.鈥�
Meaningful directions in AI research
What excites Ganeshan most today is AI鈥檚 growing capacity to address urgent, large-scale, real-world problems - exactly what he hoped for back in the 1980s.
These include how we can use AI to help prevent the unintentional drowning deaths of around 250,000 people each year and how AI can assist the 800 million people living with Type 2 diabetes, many of whom rely on long-term medication.
He believes these kinds of applications should be the focus of future AI research, as they align with both social good and technological advancement.
He also notes that it鈥檚 no surprise AI has advanced rapidly in creative fields.
鈥淐reative domains are inherently data-rich and pattern-driven, making them ideal for early AI breakthroughs. Thanks to developments in natural language processing, generative models, and image synthesis, AI has been able to replicate, and even enhance, human creativity well before mastering complex physical tasks.鈥�
Where AI is heading next
While AI has countless promising directions, Ganeshan is especially invested in healthcare鈥攕pecifically the prevention and management of Type 2 diabetes.
鈥淎I can revolutionise how we detect disease early, offer lifestyle-based recommendations, and support long-term health, reducing the dependency on medications with adverse side effects.鈥�
Another area he finds particularly fascinating is the development of non-stop high-speed trains, where passengers disembark at intermediate stations via autonomous pods. This vision, powered by AI-driven simulation and control, represents the kind of seamless integration between AI and human infrastructure that he sees as the next frontier.
鈥淭hese examples point to a future where AI becomes part of the very fabric of mobility, infrastructure, and daily life. And this is just the beginning.鈥�
Risks and ethical responsibilities
Ganeshan says we need to confront AI鈥檚 role in misinformation and propaganda, the erosion of privacy and autonomy, unethical commercial targeting, and the use of AI in warfare or mass surveillance.
Other developments that raise concerns include AI-enabled crime and the use of AI in military conflicts as well as deepfakes and the manipulation of public opinion, for example by influencing elections. Another area to consider is the promotion of excessive consumption encouraged by AI-curated ads and platforms.
鈥�Ultimately, we must ensure that AI serves the collective wellbeing of society, not just the interests of a few powerful entities,鈥� says Ganeshan.
Advice for future AI professionals
For students and early-career AI professionals, Ganeshan offers two key pieces of advice: build a strong technical foundation and always apply an ethical lens to your work.
鈥淢aster the fundamentals - algorithms, data structures, core AI models, and the underlying mathematics. But just as importantly, consider the broader impacts of your work on people and the planet. Prioritise real-world, socially meaningful challenges over purely technical achievements.鈥�
