Daniel McCoppin is a first-year student who is majoring in global affairs and earning a minor in Chinese.
In a quaint coffee shop off the streets of Rome this past summer, I stared at my computer screen, overwhelmed by the myriad class choices. One course stood out to me above the rest: Keough School Professor Yong Suk Lee’s Application, Ethics, and Governance of AI. Timely, I thought. Timely it was — and a heck of a lot more.
The class turned out to be a much deeper exploration of general ethics and AI than I expected, but the frequent philosophical debates we held quickly became shining moments of intellectual challenge on my Monday and Wednesday afternoons. Having peers who not only were concerned about the ramifications of AI development but also wanted to approach it in a thorough, ethics-centered way, was incredibly promising.
One of my most important takeaways from the class was the importance of having comprehensive ethical frameworks for evaluating AI regulations. In the context of the current AI arms race and competition between different AI companies, I was fairly skeptical at first that ethics would even be taken into consideration by companies and governments; I quickly learned how wrong I was.
We discussed the big bucks tech companies are putting into hiring AI ethicists and also the debates countries are engaged in over ethical regulations of AI. Most importantly, public pressure is mounting domestically for increased regulation, especially as under-tested chatbot models continue to cause emotional harm, create sexually explicit content, libel and hallucinate. Notre Dame’s own DELTA framework is a promising reflection of the role of Catholic morality in this discussion that also highlights the broad lack of consensus around regulations stemming from differing value systems.
Global perspectives on AI
These debates were enhanced even further by the variety of perspectives in the class; students ranged from first-year undergraduates to master’s level and came from Brazil, Argentina, South Africa, the Gambia, Pakistan and other countries. In this context, many seemingly abstract debates became much more tangible, namely the potential for influencing other countries’ values, public perceptions, and causing cultural hegemonization that AI has, and the soft-power capabilities that arise with that power.
I was surprised by how much less concern other countries’ citizens had about data privacy and potential government surveillance, especially in countries where governments are seen as too inefficient or corrupt to care about surveilling their citizens. At the same time, I often found in my own research that many less developed authoritarian countries are looking into strengthening AI-powered surveillance, often with the help of a key foreign influence: China.
The elephant (panda?) in the room
China’s role surfaced in nearly every classroom discussion. As a global affairs and Chinese double major, most of my in-class work was centered around China’s role in all this chaos. My main takeaways? The U.S is lucky, but China is smart. Technologically, the two are neck-and-neck; almost everywhere else, the U.S is way, way behind.
One of the most interesting differences we discussed is one of the U.S.’ biggest advantages: America has money – a lot of money– in the hands of private entities. The American model of venture capitalists throwing cash at a hundred AI start-ups, waiting to hit a unicorn or two, is completely different from China’s ultra-competitive, succeed-or-die market model.
That being said, that doesn’t mean China can’t pull out ahead. We’ve seen it happen with clean energy: government initiatives propelled China to global dominance on manufacturing in solar, electric vehicles and other sectors. And China also has its own multinational tech behemoths that do their fair share of innovation — and soft power growth.
In our panel discussions on different research topics, my group discussed how China and Chinese companies are miles ahead of the U.S. in terms of intentionally using AI technologies and infrastructure as a soft power tool. They’ve invested billions around the world over the past two decades, largely as part of the Belt and Road Initiative, and have focused investment in areas where American support has been historically lacking, particularly in parts of Asia and Africa.
Where the U.S. is falling behind most, however, isn’t abroad — it’s right here at home. China is already piloting various retraining programs for millions of workers, and has implemented much more comprehensive national AI-education policies. While it’s good for the U.S. to be careful about their own policies, we’re doing it in a way that isn’t adequately preparing teachers, or students, to handle AI in the classroom.
Ultimately, the class made me realize just how difficult it will be to agree on the ethics of these sorely needed AI policies. But at the same time, I think my classmates and I can all recognize the abundance of common ground most people share; now, we just need to act.
Originally published by at keough.nd.edu on March 05, 2026.