Nanyang MBA

Beyond the Hype: Generative AI’s Impact on Policy, Education and People

Generative artificial intelligence (GenAI) is reshaping how we work and think. And a heavy helping of hype has followed: an endless rotation of pundits continues to sing the technology’s praises online.

But, in reality, it’s too early to see clearly beyond the chatter. Like any generation caught in the middle of disruptive technology, we can only wait and see how the benefits of GenAI measure up against its risks.

To understand GenAI’s promise and potential pitfalls, we talked with Prof. Goh Kim Huat, Associate Dean (Graduate Studies) at Nanyang Business School (NBS), who develops clinical AI algorithms when he’s not overseeing NBS’s MBA programmes.

AI’s impact – fast and slow

Prof. Goh is an old hand at AI: “I started doing analytics and AI work about 20 years ago,” he recalled. “Back then, it wasn’t called AI; it was called computer science, statistics or even econometrics.”

In Prof. Goh’s graduate school days, the large language models (LLMs) behind today’s GenAI didn’t exist. It was only in the late 2010s when transformer-based deep learning architecture made LLMs possible, leading to the 2020s’ generative AI boom.

GenAI is so new, it’s still not yet made a decisive impact on the way we work and think. “Change takes time to percolate through industries,” he explained.

Prof. Goh suggests we’ll see a phased impact of GenAI on the business world. Currently, AI automates existing business processes, focusing on incremental efficiency improvements without fundamentally transforming business operations.

“[AI will] start to change business models – you’ll start to see industries get progressively disrupted, or new industries emerge,” Prof. Goh explained, citing image protection software Nightshade and companies that provide data labelling services as examples of the latter. “Industry-level impact will take much longer because new technology often has indirect effects.”

And as GenAI increasingly takes over the cognitive labour previously reserved for humans, existing industries will find their business models disrupted.

“I tried using AI for programming in Python, and it generated excellent code, which could have a big impact on firms that rely on offshore programming,” Prof. Goh recalled. “Low-end programming jobs, I think, will be greatly impacted.” 

GenAI’s human impact

Lost jobs are just the first in a long line of unpredictable impacts that GenAI will have on people.

“Humans live in the short term, whereas companies and economies operate in the mid to long term,” explained Prof. Goh. “When a person loses a job, one or two years of unemployment is a very long time, but from an economic standpoint, a temporary increase in job losses may be seen as beneficial for the country if the nation is able to reskill and redeploy structurally displaced individuals to other job roles.”

As with any new tech, the ethics of GenAI remain a work in progress – regulators, educators, and ethicists will have their hands full in the next few years responding to GenAI’s impact on labour and other intractable moral dilemmas:

• Protecting creator rights: AI-driven changes are blurring the boundaries of creative ownership and payment. “If creators can’t protect their work, there’s no motivation to create, so the market will fail eventually,” explained Prof. Goh.
• Deepfakes and trust: Scammers increasingly use AI-generated “deepfakes” to scam their victims out of their hard-earned cash. “Over time, this technology might create a generation that struggles with trust because they can’t tell if images or videos are real.”
• Inequality: If AI becomes another form of capital – or a finite resource that produces value in an economy – Prof. Goh believes the technology could exacerbate income inequality over time. “If you only have certain individuals or companies with access to AI, that will affect wealth distribution across people, nations, and geographic locations,” he explained.

To ensure AI delivers on its potential, regulators must walk a fine line between fostering innovation and addressing potential risks – something he’s witnessed in his work with regulators from Singapore and abroad.

“Policymakers must balance how tightly they want to govern AI,” Prof. Goh explained. “For example, if you get too strict (for example, not allowing data to be used in LLMs because it could be shared), then you will not be able to use the technology.”

The right regulatory balance allows experimentation while ensuring ethical use and mitigating potential harms. Prof. Goh observed that Singapore – its pragmatic reputation aside – generally adopts a pro-technology stance. “Many tech innovations in Singapore, we allow to a point. We clamp down only when we see some problems,” he explained.

For issues like deepfakes, Prof. Goh prefers education over regulation to tackle the problem. “Regulation is going to be very difficult, especially with open access to the technology,” he explained. “We’re generally proactive about regulation in Singapore, but education may be the most important tool here—helping people understand that what they see may not be true.”

Addressing the cognitive offloading problem

Educators must strike a different balance between teaching GenAI as an essential future technology and ensuring it becomes a tool, not a crutch.

“We wouldn’t say, ‘Don’t use AI because it impedes learning’,” Prof. Goh said. “It’s like telling people to stop using Google and go back to libraries – it won’t work. But I think the idea that ChatGPT can solve everything is just naive.”

Prof. Goh raises concerns about cognitive offloading to AI and its effect on developing critical thinking skills as AI becomes more prevalent in business.

Before GenAI, students learned inductive reasoning on their own. However, today’s students and workers often delegate analysis to an AI chatbot. “It reduces our need for inductive thinking,” Prof. Goh explained. And just as muscles weaken without exercise, cognitive skills can weaken when not regularly used. “If one hasn’t been trained in the basics and then forced to use AI, the mind may not fully develop,” Prof. Goh explained.

Prof. Goh suggests a two-part solution to allow AI in coursework without the risk of detrimental cognitive offloading. “First, you must teach the fundamentals of individual thinking, the general principles,” he explained. “Then, build on GenAI’s capability to say, ‘This can now be done much faster.’”

Building a long-term AI curriculum

As NBS’s Associate Dean, Prof. Goh is helping NBS situate GenAI in the curriculum and align the technology with the school’s goals. “A lot of our primary research in AI is done through CCDS, the College of Computing and Data Science, where they focus on foundational AI research,” Prof. Goh explained. “At NBS, my colleagues and I conduct applied AI research.”

Universities must stay ahead of the curve on GenAI’s emergence as a transformative trend, but not too far ahead; when the hype eventually dies down, nobody wants to be left with a degree in a stagnant technology (MS in the Metaverse, anyone?).

“We need to ensure that it’s sustainable: it can’t be too applied to the point where it’s just a ‘flavour of the year’,” explained Prof. Goh. “We need to have something enduring over a long period of time.”

However, long-term trends look favourable for GenAI. “Over the last two years, many universities worldwide have created courses dedicated to AI. This usually signals a paradigm shift,” concluded Prof. Goh. “When entire colleges are created around GenAI, it will be here for a long time – this is a global trend.”

The Nanyang MBA is a flexible 12-month or 18-month programme designed to fuel your growth into a future-ready leader equipped with the skills needed to excel in a global, digital environment. The programme aims to develop impactful, culturally adept leaders who embrace the connection between business, technology, and innovation to excel in global environments and adapt to each new wave of digital change.