The Massry School of Business at the University at Albany is introducing a new Master's program, designed to equip students with tools to use AI for innovation and organizational growth. WAMC's Maryam Ahmad spoke to its Dean, Dr. Sanjay Goel, about the goals of the program and how AI is transforming business education.
What is the goal with this new program?
The goal with the new program really is a little bit transformative. If you look at what's happening, AI is coming into the industry, and a lot of people are kind of panicking – “Oh my god, how is this going to change the industry?” So in some ways, it's a very critical, transformative movement for the industry. There are people who will embrace it and who will really thrive, and the people who are not able to embrace it will not be able to thrive or survive over the next decade or so. So the goal here is to prepare the next generation of workforce and to retrain the existing workforce so that they're able to leverage AI better for the businesses.
What's one example of a way that people can leverage AI for a business specifically?
If you look at what's happening, for instance, a lot of the marketing campaigns, they can be developed purely using AI right now, right? If you look at a lot of financial analysis that can be done using AI, a lot of data analysis and cyber security can be done using AI. So AI is all pervasive. A lot of people fear that AI is just going to take over their jobs. That is not the case.
What's going to happen is AI is going to make everybody in their jobs a lot more efficient, which means something that required five people will now require maybe one or two people. There'll be a shrinkage of workforce, not the way people think that AI is just going to take over their job, but it will make them a lot more efficient in being able to do what they do.
A portion of this master's program is also addressing these like specific technical tools like Python and R. How do you plan to teach people to utilize those for business and organizational growth?
The way we have structured this program is really we built it in layers. We firmly believe that fundamentals for the programming or the training for AI needs to be there before people start leveraging it. We don't want people giving a monkey a typewriter and start typing in - you want to make sure that people understand the nuances: how programs are built, how AI models are built, and then leverage them further, and without understanding the fundamentals of some programming languages, some AI modeling, they're not going to be able to do that. So that's why we built it in layers.
And what was your role in making this program?
I designed it from scratch. I've been working in the field of AI way before it became popular over the last 20-25 years. My dissertation was in the field of AI. I used AI for engineering design. At this point, AI has become very popular, but the core fundamentals still are the same. The new thing that has come in is basically generative AI, where it's able to mimic and think like humans. So I think that's what we are leveraging now in terms of AI, and that's what's making a lot more popular.
You talked about how you've worked in this field for several years. What specifically about generative AI has proven so transformative in the past few years?
People always had this utopian vision that at some point machines are going to be able to think like humans, be able to act like humans - well they have, using generative AI. I think that's a transformative movement. People never believed in this whole vision. Why this is happening is because we have this massive computing power that is available right now to be able to train the large models. If you look at a human brain, it has a billion neurons to be able to train something to that larger level, requiring a huge processing capacity.
And now we do the model, with AI Anthropic and all the other OpenAI building, they have the capacity to be able to mimic human. They already are, if you look at the test of human intelligence, the Turing test. These models have already passed the Turing test, so we have reached the stage when a brain can think like (a) human. Now it cannot feel, the AI model cannot feel like humans. But that's a different story. You never know when we'll be able to come up with feelings for the machines.
And what specifically about that distinction is important? There are people, as you mentioned, that are worried about AI taking their jobs, or AI replacing certain professions, but you said that it was more about efficiency. What do you think distinguishes the human thinking versus artificial intelligence thinking right now?
So human thinking has always been about creativity, right? Where people struggle with a mundane, repetitive task, they get tired. A machine doesn't get tired. That's where the big difference is, that a lot of the repetitive things which people were doing, only humans could do it, because it required some thinking that can all be done using generative AI. Given that it can do it, so we still need a human directing generative AI in understanding, describing the problem and what not to be able to solve. But once it knows how to do it, it can do it very rapidly and over time, again and again and again, without getting tired. I think that's going to be a big deal.
There was also mention of teaching students about the ethical and societal implications of artificial intelligence. What exactly would that look like in this program?
AI is going to come everywhere. But there are lot of societal implications to that. The first societal implication is, I'll give an example. Today, Let's say, using AI, we are able to have self-driving cars, right? How many drivers are there in the world? Several, several 100 million drivers. What happens to them? What happens to all of the jobs that are going to get eliminated, not by AI taking over, by making people more efficient? Will there be an employment crisis?
Let's look at a third existential threat. You and I, we work really hard in our academics because we wanted to achieve something. We wanted to get better and better, to make a name for ourselves in our careers. If everything that we can do, AI can do it just a little bit better, do you and I have incentive to get an education?
There are long-term fundamental thought processes that need to readjust. Now, humans are resilient. They'll be able to overcome this, but I think that's where the fundamental challenge lies. Our goal in the program is to basically teach them all the societal challenge that will come along with that, think longer term vision, how society gets impacted, and how we need to put the either brakes in place or mechanisms in place so that we don't have the negative sides.
That's one part of ethics. The other part of ethics is AI is very data-based, right? If there are deficiencies in the data, if there are biases in the data, they're going to reflect in the final models. We want to make sure that if there are criminal justice systems which are being automated, are not targeting specific population, if there are admissions processes being done, we don't target specific genders or discriminate against specific genders. These are the kind of issues that we need to address going forward, and we'll teach them in the program.
How else is the Massry School looking to incorporate AI into their education?
That's a very good question. I was just working on it myself. This is our graduate level. At the undergraduate level, we have a business administration program. We're starting a new concentration in AI. There are a lot of people who are taking domain concentration, like finance and whatnot. They can take a co-concentration in AI and be able to be AI finance, or AI marketing, or AI management. That will give them domain knowledge, and at the same time, it will give them knowledge about AI. Basically, they can leverage across each other.
What do you envision for the students who are taking this program and going into the workforce in the future?
Now, see, we graduate people across the board, across all different business disciplines. The whole idea here is that learning AI, plus the domain knowledge that they have, either through the undergraduate program or through the graduate program, is going to help them grow in their own profession. If they are marketing, they'll be among the top marketing recruits. If they're human resources, they'll be among the best performers and human resources. The idea is to be able to leverage these tools with the domain knowledge that they have to be the best in the field.
