Generative artificial intelligence (AI) is changing how we teach, learn, conduct research and work. At McMaster, that change is already underway, bringing both opportunities and risks. 

Faculty are experimenting with AI in teaching and research. Students are using new tools to support their learning. Staff and units across the university are exploring how AI might improve processes and services. 

As a faculty Special Advisor to the Provost on AI, Professor Bhagwati Gupta will help bring these conversations together and support a more coordinated approach to AI across the university. 

He joins a broader network of AI leadership and engagement underway across McMaster. This includes work led by Stephanie Verkoeyen, a staff Special Advisor to the Provost on Generative AI, as well as the AI Advisory Committee, campus-wide consultations and events exploring the opportunities and challenges associated with AI. 

Gupta, a professor of Biology and former president of the McMaster University Faculty Association, shares his perspective on the opportunities AI presents for research and education, and why good judgment remains essential.

What will you focus on in your new role? 

My role is about helping McMaster develop a broader and more coherent approach to generative AI. 

It is about listening, understanding what is working and identifying gaps and concerns. 

I will work with the Provost, Deputy Provost and others to strengthen our support, guidance, planning, policies and future activities related to AI. 

It is also important to leave room for experimentation. Different disciplines have different needs, and there will not necessarily be one approach that works for everyone. 

Why does McMaster need this role now?

The pace of change is probably the biggest reason. 

When generative AI first became widely available, much of the discussion focused on ChatGPT, student assignments and academic integrity. Those questions are still important, but the conversation has become much bigger. AI is now touching almost every aspect of university work. 

There is a lot happening at McMaster, but people do not always know what others are doing, where to find guidance or what support is available. We need to look at these issues in a coordinated way and think about what McMaster will need over the next several years. 

Where do you see the greatest opportunities? 

I see opportunities almost everywhere, but research and education are particularly important to me. 

For researchers, AI can provide new ways of working with large and complex datasets and identifying patterns much faster. Some of our researchers, including those in health sciences and drug discovery, are already using AI effectively. 

For students, we need to help them learn how to use these tools well, but also when not to use them. They need to understand the limitations of AI, know when to question its output and develop the ability to think critically. 

There are opportunities in university operations, too. AI could help improve processes and services while keeping human judgment and accountability at the centre of important decisions. 

What should universities be thinking about beyond academic integrity? 

One of the biggest questions is what learning should look like when students have easy access to increasingly capable AI tools. 

What should students learn on their own? What should happen in the classroom? What skills should they develop? How do we use AI without compromising critical thinking, independent decision-making and problem solving? 

Research raises other questions. We need to provide researchers with access to AI tools and the infrastructure, expertise and data needed to use them effectively. 

There are also practical considerations around data privacy, intellectual property, research integrity, cybersecurity and accountability. 

But we need to look beyond managing risks. As a university, our role is to generate knowledge, make discoveries and prepare students for the future. We should help shape the development and use of AI, rather than simply react to it. 

How has your experience as MUFA president shaped your approach?

My time as MUFA president gave me a much broader view of McMaster. I became more aware of how differently faculty across the university teach, conduct research and work with students, and how institutional decisions can affect people in different ways. 

That perspective is useful in this role. AI offers significant benefits, but it is also creating additional work for faculty, who are revising assessments, addressing academic integrity questions and deciding what uses of AI are appropriate in their disciplines. 

One thing I learned through MUFA is the importance of involving people in decisions that affect their work. That will be important as we think about how AI is used and supported at McMaster. 

How are you using AI in your own research?

My research uses nematodes as animal models to study stress, health and aging. We do a lot of microscopy and generate large-scale genomics and proteomics datasets. 

We have started using computational and AI-based tools to analyze these images and datasets. They are helping us identify trends and patterns faster and reveal relationships we might not have noticed otherwise. 

I also use generative AI for researching the field, exploring questions, looking at experimental results from different angles, synthesizing information and for everyday tasks. 

I have found these tools very useful and, in some cases, remarkably powerful. But they have also made me more aware of their limitations. 

You still need to know your subject, think independently and be critical about what AI gives you.  

What do you hope McMaster can accomplish with AI?

We have an opportunity to help shape McMaster as AI becomes more deeply integrated into academic life. 

In teaching, we can use AI-enabled technologies to prepare students for a world where these tools will be part of their work. In research, AI is changing how we analyze data, generate hypotheses and approach difficult problems. 

There are opportunities in university operations as well, from improving services to making processes more efficient. 

We also do not have to do this alone. Universities across Ontario and Canada are facing many of the same questions. We can learn from each other and identify where collaboration makes sense. 

Learn More

McMaster’s work on artificial intelligence extends beyond this appointment and includes: 

• The AI Advisory Committee, which brings together representatives from across the university to explore opportunities, risks and institutional priorities related to AI. 

• Expert panels and consultations that help inform McMaster’s approach to AI in teaching, learning, research and operations. 

• “(Gen)AI at McMaster” events and campus-wide conversations that showcase projects, research and emerging practices from across the university community.