The power of the generalist  

March 13, 2024 | By Dean Sevin Yeltekin

In this Q&A, technology strategist Aditya Singh’08S (MBA) reflects on how generative AI is changing the world of work and predicts who will succeed in the new normal. 

Sevin Yeltekin: What brought you to Simon? 

Aditya Singh: I moved to the U.S. to complete a master’s degree in computer science and found myself at a crossroads. I could become a subject matter expert and lean into more technical work, or I could move into a business role and help clients leverage technology to achieve their goals. I found the business path more appealing, which is how I ended up at Simon to pursue an MBA. I naturally gravitated toward Simon’s data-driven, analytical approach because of my background. What I found was that Simon doesn’t just give you a skillset—it teaches you to think in a certain way. Being called upon to solve problems you know nothing about creates discomfort that leads to growth. That is how you thrive in future positions. 

SY: Now you’re a leader in technology strategy at Microsoft. What does your role entail?

AS: Within Microsoft’s Financial Services Industry sales team, my role is to help clients leverage our full technology suite to achieve their goals. I am a generalist, not a deep subject matter expert. My job is to put all the technology in front of the client like pieces of a Lego set and help them build something meaningful. 

SY: When did generative AI first come onto your radar, and how is it changing the nature of your work?

AS:I was introduced to the concept of AI in the early 2000s when I was doing my master’s degree. I was familiar with models that could be trained to make inferences, but everything changed when companies like Open AI began training Large Language Models (LLMs) with sweeping applications. Now we have a tool that doesn’t just scour transport data or climate data; it is trained on the entire universe of written language. At Microsoft, I have the privilege of trying new technology before it is commercialized, so there are plenty of generative AI tools that are still in development. But I can say that I currently use M365 Copilot, our AI assistant, to do things like produce meeting transcripts and set reminders. Generative AI is particularly useful for noticing things that happen on a schedule, like when someone sends an expense email every month around the same time. The AI tool might take notice and ask to automate it. If you say yes, that’s one more task off your plate for the day. This is just one example of the many repetitive tasks that AI will soon take over.

SY: How should we fill the time saved by using generative AI to do more routine tasks? 

AS: As time goes by, generative AI will leave humans more productive for things that matter. There will certainly be more opportunities for deep, strategic thinking. But that doesn’t necessarily have to take place in an office. We are all better when we have space to let our minds roam—whether that looks like thinking through a client’s problem on a long walk or spending more time with family. AI creates less pressure to do mundane tasks, but the answer is not to replace every mundane task with another task. That’s not good for people and their organizations in the long run. 

SY: How are your clients using generative AI to enhance their work?

AS: My clients in the financial services industry are using generative AI to tackle a broad range of problems. I often help them leverage our tools to improve employee productivity and reduce communication barriers on platforms like Outlook, Teams, and PowerPoint, where people spend most of their workday. My clients are also looking to embed the power of LLMs into very complex systems so they can in turn serve their own clients more effectively. A lot of this is not visible to the public—it is part of their secret sauce. Overall, I have noted an eagerness in my clients to understand how competitors are using generative AI. This desire to maintain a competitive edge is driving adoption and innovation in an industry that can be slow to evolve. Nothing happens with the snap of a finger, but as AI tools are gradually baked into day-to-day work, people notice colleagues trying them and decide to take the plunge themselves. Then, over time, the entire culture changes. 

SY: When it comes to generative AI, what kind of skills would you want a new hire to bring to the table? 

AS: Generative AI is changing the entire fabric of the global workforce. It will create new industries and require new skills in ways we can’t even predict. But what will stay the same is the kind of employee that companies like Microsoft want to hire. It is the generalist, the person who is trained in multiple areas and has multiple skillsets, who brings the most value to the table. Generalists will combine the power of AI with the weight of their varied, rich experiences to solve problems in a way that a machine never could. When it comes to being nimble and adaptive in solving out-of-the-box challenges, there is still no match for the human mind.

Sevin Yeltekin is the Dean of Simon Business School. 

Follow the Dean’s Corner blog for more expert commentary on timely topics in business, economics, policy, and management education. To view other blogs in this series, visit the Dean's Corner Main Page.

 What ChatGPT means for higher education

April 26, 2023 | By Dean Sevin Yeltekin

ChatGPT, a chatbot released by Open AI last November, has captured the world’s attention with its uncanny ability to compose essays, write song lyrics, play games, answer test questions, and take on other tasks traditionally associated with human intelligence.

The academic community has responded to the advent of this new technology with a mixture of fascination and concern, keenly aware of its potential to transform the way knowledge is produced, conveyed, and retained.

In the Q&A below, Mitch Lovett, senior associate dean of education and innovation at Simon Business School, weighs in on the potential impact of Chat GPT on higher education.

What do you view as ChatGPT’s primary strengths and weaknesses?

Where ChatGPT seems to excel the most is predicting text that might be useful to the user based on information that is available. A student taking a finance class, for example, might ask it to explain and contrast specific kinds of financial tools. ChatGPT might not produce the most elegant answer, but it will produce a B+ answer in a short amount of time. On the flipside, ChatGPT will often make up sources or information while trying to predict something—and, so far, it’s not particularly good at math. It is also not as useful when information doesn’t exist, like in a situation in which someone needs to write the website copy for a brand-new product. When ChatGPT tries to venture outside the space of prediction, it becomes less effective.

Do you think it can ever fully replace human intelligence?

No, but I would be wary of underestimating technology like ChatGPT. A few years ago, we never would have expected to encounter an AI program that can create something people struggle to discern from human art. Over time, it will become capable of more and more. Right now, though, it is just making predictions. It knows that certain things go with other things, but it does not know truth from lies. It doesn’t have a sense of ethics. That’s an area where human judgment is indispensable.

What I think is most profound is how it is going to redefine expertise in some fields. We are going to use ChatGPT to write things for us—text, code, outlines—so that we can complete our work faster. That means some skills will become less important and others more important.

What are some ways ChatGPT can improve the quality of education at Simon?

For both students and professors, one of its primary functions will be to assist in search. Constructing literature reviews will become significantly less time-intensive when using ChatGPT to aggregate sources and summarize information on a given topic. And when we think about ways to integrate it into classroom assignments, like using it to write code or organize information to help solve a case study, it is clear that students will be able to go further in the topics they are learning about. They will be able to do more in an assignment and do it more efficiently. They may not be able to learn more information overall, because the human brain can only absorb so much in a short time, but they will learn different information and get more practice designing solutions rather than implementing them.

I can also imagine ChatGPT serving as a first-line teaching assistant (TA) or discussion board assistant in order to help students taking asynchronous classes more quickly and efficiently than their professors and human TAs. Having an outside curator of information to post questions, responses, and comments will enrich the asynchronous interactions that take place.

What are some of the downsides or pitfalls of using ChatGPT in an academic setting?

There are significant implications when it comes to academic honesty. Theoretically, a student taking an online asynchronous course could use ChatGPT to complete all their assignments and take their exams. Many faculty members at Simon already use various analytics tools to detect plagiarism—for example, by comparing student answers to see if any are unreasonably similar. But as ChatGPT produces writing that is increasingly indistinguishable from something a student would produce, it will become an arms race to detect the use of AI. Some professors will address this by switching to in-person, handwritten exams whenever possible, while also ensuring that the course content is so specific that ChatGPT becomes ineffective. These are strategies that involve trying to block ChatGPT. Others will embrace the use of ChatGPT, but will do so by adjusting assignments and exams to compensate, similar to the concept of allowing a one-page cheat sheet on an exam or holding an open book exam.

Of course, there is also the danger of placing too much trust in ChatGPT. A student taking an introductory course in accounting, for example, might ask it to answer an accounting-related question but lack the base knowledge to discern the accuracy of its answers. Without any background in the subject matter, it can be difficult to know if ChatGPT is producing an A- answer or a complete fabrication. This is where our definition of expertise becomes important. Part of educating students is helping them understand how best to use AI and evaluate when the AI might be producing meaningless or less valuable responses.

How do you expect ChatGPT to change the way students learn?

I find it helpful to think about the analogy of using calculators in math. My children’s elementary school found that allowing students to use calculators from an early age weakened their ability to do simple computations in their head, a skill that is helpful in doing more advanced math. In the same way, the introduction of ChatGPT might weaken students’ ability to write. Writing is certainly something we have traditionally viewed as an important skill. But how important is it in relation to the tasks we need people to be able to do in a world with AI?

If ChatGPT is always creating a generic setup to tailor, it allows students to avoid the mundane and repetitive—but doing mundane, repetitive tasks over and over might be helping them develop intuition and judgment. One of the most important tasks that confronts us as educators is figuring out how much of this mundane work is needed to become an expert when AI is available.

On the other hand, we may be overreacting to the fact that future students will learn differently from their predecessors. To be considered an expert on something, it will be less essential to recall facts that will always be at their fingertips and more important to apply judgment and critical thinking. There is little chance of stopping the integration of AI tools like ChatGPT into education, so our job is to decide what fundamental knowledge is necessary for mastering a subject and learn to train students accordingly.

What questions are we not asking about ChatGPT that we should be asking?

ChatGPT raises fundamental questions about truth that we must grapple with. This technology produces text that may or may not be accurate and presents it as fact. When asked the same question twice, it may produce contradictory answers if it incorporates new information in between searches. Will truth start becoming blurrier for the people who use it?

I also think about how search engines like Google form a layer between the user and a website. ChatGPT, on the other hand, will put a filtered version of a website in front of you. You won’t even need to visit a website directly. What are the implications when it gets things wrong? Where do we draw a boundary line between what is a search and what is not? There are plenty of legal questions to consider surrounding ownership and responsibility for the information that is presented.

Mitch Lovett is the senior associate dean of education and innovation and a professor of marketing at Simon Business School.

Follow the Dean’s Corner blog for more expert commentary on timely topics in business, economics, policy, and management education. To view other blogs in this series, visit the Dean's Corner Main Page.