Higher Education Webinar: Implications of Artificial Intelligence in Higher Education

Pablo Molina, associate vice president of information technology and chief information security officer at Drexel University and adjunct professor at Georgetown University, leads the conversation on the implications of artificial intelligence in higher education.

FASKIANOS: Welcome to CFR’s Higher Education Webinar. I’m Irina Faskianos, vice president of the National Program and Outreach here at CFR. Thank you for joining us.

Today’s discussion is on the record, and the video and transcript will be available on our website, CFR.org/Academic, if you would like to share it with your colleagues. As always, CFR takes no institutional positions on matters of policy.

We are delighted to have Pablo Molina with us to discuss implications of artificial intelligence in higher education. Dr. Molina is chief information security officer and associate vice president at Drexel University. He is also an adjunct professor at Georgetown University. Dr. Molina is the founder and executive director of the International Applies Ethics in Technology Association, which aims to raise awareness on ethical issues in technology. He regularly comments on stories about privacy, the ethics of tech companies, and laws related to technology and information management. And he’s received numerous awards relating to technology and serves on the board of the Electronic Privacy Information Center and the Center for AI and Digital Policy.

So Dr. P, welcome. Thank you very much for being with us today. Obviously, AI is on the top of everyone’s mind, with ChatGPT coming out and being in the news, and so many other stories about what AI is going to—how it’s going to change the world. So I thought you could focus in specifically on how artificial intelligence will change and is influencing higher education, and what you’re seeing, the trends in your community.

MOLINA: Irina, thank you very much for the opportunity, to the Council on Foreign Relations, to be here and express my views. Thank you, everybody, for taking time out of your busy schedules to listen to this. And hopefully, I’ll have the opportunity to learn much from your questions and answer some of them to the best of my ability.

Well, since I’m a professor too, I like to start by giving you homework. And the homework is this: I do not know how much people know about artificial intelligence. In my opinion, anybody who has ever used ChatGPT considers herself or himself an expert. To some extent, you are, because you have used one of the first publicly available artificial intelligence tools out there and you know more than those who haven’t. So if you have used ChatGPT, or Google Bard, or other services, you already have a leg up to understand at least one aspect of artificial intelligence, known as generative artificial intelligence.

Now, if you want to learn more about this, there’s a big textbook about this big. I’m not endorsing it. All I’m saying, for those people who are very curious, there are two great academics, Russell and Norvig. They’re in their fourth edition of a wonderful book that covers every aspect of—technical aspect of artificial intelligence, called Artificial Intelligence: A Modern Approach. And if you’re really interested in how artificial intelligence can impact higher education, I recommend a report by the U.S. Department of Education that was released earlier this year in Washington, DC from the Office of Education Technology. It’s called Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations. So if you do all these things and you read all these things, you will hopefully transition from being whatever expert you were before—to a pandemic and Ukrainian war expert—to an artificial intelligence expert.

So how do I think that all these wonderful things are going to affect artificial intelligence? Well, as human beings, we tend to overestimate the impact of technology in the short run and really underestimate the impact of technology in the long run. And I believe this is also the case with artificial intelligence. We’re in a moment where there’s a lot of hype about artificial intelligence. It will solve every problem under the sky. But it will also create the most catastrophic future and dystopia that we can imagine. And possibly neither one of these two are true, particularly if we regulate and use these technologies and develop them following some standard guidelines that we have followed in the past, for better or worse.

So how is artificial intelligence affecting higher education? Well, number one, there is a great lack of regulation and legislation. So if you know, for example around this, OpenAI released ChatGPT. People started trying it. And all of a sudden there were people like here, where I’m speaking to you from, in Italy. I’m in Rome on vacation right now. And Italian data protection agency said: Listen, we’re concerned about the privacy of this tool for citizens of Italy. So the company agreed to establish some rules, some guidelines and guardrails on the tool. And then it reopened to the Italian public, after being closed for a while. The same thing happened with the Canadian data protection authorities.

In the United States, well, not much has happened, except that one of the organizations on which board I serve, the Center for Artificial Intelligence and Digital Policy, earlier this year in March of 2023 filed a sixty-four-page complaint with the Federal Trade Commission. Which is basically we’re asking the Federal Trade Commission: You do have the authority to investigate how these tools can affect the U.S. consumers. Please do so, because this is your purview, and this is your responsibility. And we’re still waiting on the agency to declare what the next steps are going to be.

If you look at other bodies of legislation or regulation on artificial intelligence that can help us guide artificial intelligence, well, you can certainly pay attention to the U.S. Congress. And what is the U.S. Congress doing? Yeah, pretty much that, not much, to be honest. They listen to Sam Altman, the founder of ChatGPT, who recently testified before Congress, urging Congress to regulate artificial intelligence. Which is quite clever on his part. So it was on May 17 that he testified that we could be facing catastrophic damage ahead if artificial intelligence technology is not regulated in time. He also sounded the alarm about counterfeit humans, meaning that these machines could replace what we think a person is, at least virtually. And also warned about the end of factual evidence, because with artificial intelligence anything can be fabricated. Not only that, but he pointed out that artificial intelligence could start wars and destroy democracy. Certainly very, very grim predictions.

And before this, many of the companies were self-regulating for artificial intelligence. If you look at Google, Microsoft, Facebook now Meta. All of them have their own artificial intelligence self-guiding principles. Most of them were very aspirational. Those could help us in higher education because, at the very least, it can help us create our own policies and guidelines for our community members—faculty, staff, students, researchers, administrators, partners, vendors, alumni—anybody who happens to interact with our institutions of higher learning.

Now, what else is happening out there? Well, we have tons, tons of laws that have to do with the technology and regulations. Things like the Gramm-Leach-Bliley Act, or the Securities and Exchange Commission, the Sarbanes-Oxley. Federal regulations like FISMA, and Cybersecurity Maturity Model Certification, Payment Card Industry, there is the Computer Fraud and Abuse Act, there is the Budapest Convention where cybersecurity insurance providers will tells us what to do and what not to do about technology. We have state laws and many privacy laws. But, to be honest, very few artificial intelligence laws.

And it’s groundbreaking in Europe that the European parliamentarians have agreed to discuss the Artificial Intelligence Act, which could be the first one really to be passed at this level in the world, after some efforts by China and other countries. And, if adopted, could be a landmark change in the adoption of artificial intelligence. In the United States, even though Congress is not doing much, what the White House is trying to position itself in the realm of artificial intelligence. So there’s an executive order in February of 2023—that many of us in higher education read because, once again, we’re trying to find inspiration for our own rules and regulations—that tells federal agencies that they have to root out bias in the design and use of new technologies, including artificial intelligence, because they have to protect the public from algorithm discrimination.

And we all believe this. In higher education, we believe in being fair and transparent and accountable. I would be surprised if any of us is not concerned about making sure that our technology use, our artificial technology use, does not follow these particular principles as proposed by the Organization for Economic Cooperation and Development, and many other bodies of ethics and expertise. Now, the White House also announced new centers—research and development centers with some new national artificial intelligence research institutes. Many of us will collaborate with those in our research projects. A call for public assessments of existing generative artificial intelligence systems, like ChatGPT. And also is trying to enact or is enacting policies to ensure that U.S. government—the U.S. government, the executive branch, is leading by example when mitigating artificial intelligence risks and harnessing artificial intelligence opportunities. Because, in spite of all the concerns about this, it’s all about the opportunities that we hope to achieve with artificial intelligence.

And when we look at how specifically can we benefit from artificial intelligence in higher education, well, certainly we can start with new and modified academic offerings. I would be surprised if most of us will not have degrees—certainly, we already have degrees—graduate degrees on artificial intelligence, and machine learning, and many others. But I would be surprised if we don’t even add some bachelor’s degrees in this field, or we don’t modify significantly some of our existing academic offerings to incorporate artificial intelligence in various specialties, our courses, or components of the courses that we teach our students.

We’re looking at amazing research opportunities, things that we’ll be able to do with artificial intelligence that we couldn’t even think about before, that are going to expand our ability to generate new knowledge to contribute to society, with federal funding, with private funding. We’re looking at improved knowledge management, something that librarians are always very concerned about, the preservation and distribution of knowledge. The idea would be that artificial intelligence will help us find better the things that we’re looking for, the things that we need in order to conduct our academic work.

We’re certainly looking at new and modified pedagogical approaches, new ways of learning and teaching, including the promise of adaptive learning, something that really can tell students: Hey, you’re not getting this particular concept. Why don’t you go back and study it in a different way with a different virtual avatar, using simulations or virtual assistance? In almost every discipline and academic endeavor. We’re looking very concerned, because we’re concerned about offering, you know, a good value for the money when it comes to education. So we’re hoping to achieve extreme efficiencies, better ways to run admissions, better ways to guide students through their academic careers, better way to coach them into professional opportunities. And many of this will be possible thanks to artificial intelligence.

And also, let’s not forget this, but we still have many underserved students, and they’re underserved because they either cannot afford education or maybe they have physical or cognitive disabilities. And artificial intelligence can really help us reach to those students and offer them new opportunities to advance their education and fulfill their academic and professional goals. And I think this is a good introduction. And I’d love to talk about all the things that can go wrong. I’d love to talk about all the things that we should be doing so that things don’t go as wrong as predicted. But I think this is a good way to set the stage for the discussion.

FASKIANOS: Fantastic. Thank you so much. So we’re going to go all of you now for your questions and comments, share best practices.

(Gives queuing instructions.)

All right. So I’m going first to Gabriel Doncel has a written question, adjunct faculty at the University of Delaware: How do we incentivize students to approach generative AI tools like ChatGPT for text in ways that emphasize critical thinking and analysis?

MOLINA: I always like to start with a difficult question, so I very much, Gabriel Doncel, for that particular question. And, as you know, there are several approaches to adopting tools like ChatGPT on campus by students. One of them is to say: No, over my dead body. If you use ChatGPT, you’re cheating. Even if you cite ChatGPT, we can consider you to be cheating. And not only that, but some institutions have invested in tools that can detect whether or something was written with ChatGPT or similar rules.

There are other faculty members and other academic institutions that are realizing these tools will be available when these students join the workforce. So our job is to help them do the best that they can by using these particular tools, to make sure they avoid some of the mishaps that have already happened. There are a number of lawyers who have used ChatGPT to file legal briefs. And when the judges received those briefs, and read through them, and looked at the citations they realized that some of the citations were completely made up, were not real cases. Hence, the lawyers faced professional disciplinary action because they used the tool without the professional review that is required.

So hopefully we’re going to educate our students and we’re going to set policy and guideline boundaries for them to use these, as well as sometimes the necessary technical controls for those students who may not be that ethically inclined to follow our guidelines and policies. But I think that to hide our heads in the sand and pretend that these tools are not out there for students to use would be—it’s a disserve to our institutions, to our students, and the mission that we have of training the next generation of knowledge workers.

FASKIANOS: Thank you. I’m going to go next to Meena Bose, who has a raised hand. Meena, if you can unmute yourself and identify yourself.

Q: Thank you, Irina. Thank you for this very important talk.

And my question is a little—(laughs)—it’s formative, but really—I have been thinking about what you were saying about the role of AI in academic life. And I don’t—particularly for undergraduates, for admissions, advisement, guidance on curriculum. And I don’t want to have my head in the sand about this, as you just said—(laughs)—but it seems to me that any kind of meaningful interaction with students, particularly students who have not had any exposure to college before, depends upon kind of multiple feedback with faculty members, development of mentors, to excel in college and to consider opportunities after. So I’m struggling a little bit to see how AI can be instructive for that part of college life, beyond kind of providing information, I guess. But I guess the web does that already. So welcome your thoughts. Thank you.

FASKIANOS: And Meena’s at Hofstra University.

MOLINA: Thank you. You know, it’s a great question. And the idea that everybody is proposing right here is we are not—artificial intelligence companies, at least at first. We’ll see in the future because, you know, it depends on how it’s regulated. But they’re not trying, or so they claim, to replace doctors, or architects, or professors, or mentors, or administrators. They’re trying to help those—precisely those people in those professions, and the people they served gain access to more information. And you’re right in a sense that that information is already on the web.

But we’ve aways had a problem finding that information regularly on the web. And you may remember that when Google came along, I mean, it swept through every other search engine out there AltaVista, Yahoo, and many others, because, you know, it had a very good search algorithm. And now we’re going to the next level. The next level is where you ask ChatGPT in human-natural language. You’re not trying to combine the three words that say, OK, is the economics class required? No, no, you’re telling ChatGPT, hey, listen, I’m in the master’s in business administration at Drexel University and I’m trying to take more economic classes. What recommendations do you have for me?

And this is where you can have a preliminary one, and also a caveat there, as most of these search engine—generative AI engines already have, that tell you: We’re not here to replace the experts. Make sure you discuss your questions with the experts. We will not give you medical advice. We will not give you educational advice. We’re just here, to some extent, for guiding purposes and, even now, for experimental and entertainment purposes. So I think you are absolutely right that we have to be very judicious about how we use these tools to support the students.

Now, that said, I had the privilege of working for public universities in the state of Connecticut when I was the CIO. I also had the opportunity early in my career to attend public university in Europe, in Spain, where we were hundreds of students in class. We couldn’t get any attention from the faculty. There were no mentors, there were no counselors, or anybody else. Is it better to have nobody to help you or is it better to have at least some technology guidance that can help you find the information that otherwise is spread throughout many different systems that are like ivory towers—emissions on one side, economics on the other, academics advising on the other, and everything else. So thank you for a wonderful question and reflection.

FASKIANOS: I’m going to take the next question written from Dr. Russell Thomas, a senior lecturer in the Department of International Relations and Diplomatic Studies at Cavendish University in Uganda: What are the skills and competencies that higher education students and faculty need to develop to think in an AI-driven world?

MOLINA: So we could argue here that something very similar has happened already with many information technologies and communication technologies. It is the understanding at first faculty members did not want to use email, or the web, or many other tools because they were too busy with their disciplines. And rightly so. They were brilliant economists, or philosophers, or biologists. They didn’t have enough time to learn all these new technologies to interact with the students. But eventually they did learn, because they realized that it was the only way to meet the students where they were and to communicate with them in efficient ways.

Now, I have to be honest; when it comes to the use of technology—and we’ll unpack the numbers—it was part of my doctoral dissertation, when I expanded the adoption of technology models, that tells you about early adopters, and mainstream adopters, and late adopters, and laggards. But I uncovered a new category for some of the institutions where I worked called the over-my-dead-body adopters. And these were some of the faculty members who say: I will never switch word processors. I will never use this technology. It’s only forty years until I retire, probably eighty more until I die. I don’t have to do this.

And, to be honest, we have a responsibility to understand that those artificial intelligence tools are out there, and to guide the students as to what is the acceptable use of those technologies within the disciplines and the courses that we teach them in. Because they will find those available in a very competitive work market, in a competitive labor market, because they can derive some benefit from them. But also, we don’t want to shortchange their educational attainment just because they go behind our backs to copy and paste from ChatGPT, learning nothing. Going back to the question by Gabriel Doncel, not learning to exercise the critical thinking, using citations and material that is unverified, that was borrowed from the internet without any authority, without any attention to the different points of view.

I mean, if you’ve used ChatGPT for a while—and I have personally, even to prepare some basic thank-you speeches, which are all very formal, even to contest a traffic ticket in Washington, DC, when I was speeding but I don’t want to pay the ticket anyway. Even for just research purposes, you could realize that most of the writing from ChatGPT has a very, very common style. Which is, oh, on the one hand people say this, on the other hand people say that. Well, the critical thinking will tell you, sure, there are two different opinions, but this is what I think myself, and this is why I think about this. And these are some of the skills, the critical thinking skills, that we must continue to teach the students and not to, you know, put blinds around their eyes to say, oh, continue focusing only on the textbook and the website. No, no. Look at the other tools but use them judiciously.

FASKIANOS: Thank you. I’m going to go next to Clemente Abrokwaa. Raised hand, if you can identify yourself, please.

Q: Hi. Thanks so much for your talk. It’s something that has been—I’m from Penn State University. And this is a very important topic, I think.

And some of the earlier speakers have already asked the questions I was going to ask. (Laughs.) But one thing that I would like to say that, as you said, we cannot bury our heads in the sand. No matter what we think, the technology is already here. So we cannot avoid it. My question, though, is what do you think about the artificial intelligence, the use of that in, say, for example, graduate students using it to write dissertations? You did mention about the lawyers that use it to write their briefs, and they were caught. But in dissertations and also in class—for example, you have students—you have about forty students. You give a written assignment. You make—when you start grading, you have grading fatigue. And so at some point you lose interest of actually checking. And so I’m kind of concerned about that how it will affect the students’ desire to actually go and research without resorting to the use of AI.

MOLINA: Well, Clemente, fellow colleague from the state of Pennsylvania, thank you for that, once again, both a question and a reflection here. Listen, many of us wrote our doctoral dissertations—mine at Georgetown. At one point of time, I was so tired of writing about the same topics, following the wonderful advice, but also the whims of my dissertation committee, that I was this close from outsourcing my thesis to China. I didn’t, but I thought about it. And now graduate students are thinking, OK, why am I going through the difficulties of writing this when ChatGPT can do it for me and the deadline is tomorrow? Well, this is what will distinguish the good students and the good professionals from the other ones.

And the interesting part is, as you know, when we teach graduate students we’re teaching them critical thinking skills, but also teaching them now to express themselves, you know, either orally or in writing. And writing effectively is fundamental in the professions, but also absolutely critical in academic settings. And anybody who’s just copying and pasting from ChatGPT to these documents cannot do that level of writing.

But you’re absolutely right. Let’s say that we have an adjunct faculty member who’s teaching a hundred students. Will that person go through every single essay to find out whether students were cheating with ChatGPT? Probably not. And this is why there are also enterprising people who are using artificial intelligence to find out and tell you whether a paper was written using artificial intelligence. So it’s a little bit like this fighting of different sources and business opportunities for all of them.

And we’ve done this. We’ve used antiplagiarism tools in the past because we knew that students were copying and pasting using Google Scholar and many other sources. And now oftentimes we run antiplagiarism tools. We didn’t write them ourselves. Or we tell the students, you run it yourself and you give it to me. And make sure you are not accidentally not citing things that could end up jeopardizing your ability to get a graduate degree because your work was not up to snuff with the requirements of our stringent academic programs.

So I would argue that this antiplagiarism tools that we’re using will more often than not, and sooner than expected, incorporate the detection of artificial intelligence writeups. And also the interesting part is to tell the students, well, if you do choose to use any of these tools, what are the rules of engagement? Can you ask it to write a paragraph and then you cite it, and you mention that ChatGPT wrote it? Not to mention, in addition to that, all the issues about artificial intelligence, which the courts are deciding now, regarding the intellectual property of those productions. If a song, a poem, a book is written by an artificial intelligence entity, who owns the intellectual property for those works produced by an artificial intelligence machine?

FASKIANOS: Good question. We have a lot of written questions. And I’m sure you don’t want to just listen to my voice, so please do raise your hands. But we do have a question from one of your colleagues, Pablo, Pepe Barcega, who’s the IT director at Drexel: Considering the potential biases and limitations of AI models, like ChatGPT, do you think relying on such technology in the educational domain can perpetuate existing inequalities and reinforce systemic biases, particularly in terms of access, representation, and fair evaluation of students? And Pepe’s question got seven upvotes, we advanced it to the top of the line.

MOLINA: All right, well, first I have to wonder whether he used ChatGPT to write the question. But I’m going to leave it that. Thank you. (Laughter.) It’s a wonderful question.

One of the greatest concerns we have had, those of us who have been working on artificial intelligence digital policy for years—not this year when ChatGPT was released, but for years we’ve been thinking about this. And even before artificial intelligence, in general with algorithm transparency. And the idea is the following: That two things are happening here. One is that we’re programming the algorithms using instructions, instructions created by programmers, with all their biases, and their misunderstandings, and their shortcomings, and their lack of context, and everything else.

But with artificial intelligence we’re doing something even more concerning than that, which is we have some basic algorithms but then we’re feeling a lot of information, a corpus of information, to those algorithms. And the algorithms are fine-tuning the rules based on those. So it’s very, very difficult for experts to explain how an artificial intelligence system actually makes decisions, because we know the engine and we know the data that we fed to the engine, but we don’t know the real outcome how those decisions are being made through neural networks, through all of the different systems that we have and methods that we have for artificial intelligence. Very, very few people understand how those work. And those are so busy they don’t have time to explain how the algorithm works for others, including the regulators.

Let’s remember some of the failed cases. Amazon tried this early. And they tried this for selecting employees for Amazon. And they fed all the resumes. And guess what? It turned out that most of the recommendations were to hire young white people who had gone to Ivy League schools. Why? Because their first employees were feeding those descriptions, and they had done extremely well at Amazon. Hence, by feeding that information of past successful employees only those were there. And so that puts away the diversity that we need for different academic institutions, large and small, public and private, from different countries, from different genders, from different ages, from different ethnicities. All those things went away because the algorithm was promoting one particular one.

Recently I had the opportunity to moderate a panel in Washington, DC, and we had representatives from the Equal Employment Opportunity Commission. And they told us how they investigated a hiring algorithm from a company that was disproportionately recommending that they hired people whose first name was Brian and had played lacrosse in high school because, once again, a disproportionate number of people in that company had done that. And the algorithm realized, oh, this must be important characteristics to hire people for this company. Let’s not forget, for example, with the artificial facial recognition and artificial intelligence by Amazon Rekog, you know, the facial recognition software, that the American Civil Liberties Union, decided, OK, I’m going to submit the pictures of all the congressmen to this particular facial recognition engine. And it turned out that it misidentified many of them, particularly African Americans, as felons who had been convicted.

So all these artificial—all these biases could have really, really bad consequences. Imagine that you’re using this to decide who you admit to your universities, and the algorithm is wrong. You know, you are making really biased decisions that will affect the livelihood of many people, but also will transform society, possibly for the worse, if we don’t address this. So this is why the OECD, the European Union, even the White House, everybody is saying: We want this technology. We want to derive the benefits of this technology, while curtailing the abuses. And it’s fundamental we achieve transparency. We are sure that these algorithms are not biased against the people who use them.

FASKIANOS: Thank you. So I’m going to go next to Emily Edmonds-Poli, who is a professor at the University of San Diego: We hear a lot about providing clear guidelines for students, but for those of us who have not had a lot of experience using ChatGPT it is difficult to know what clear guidelines look like. Can you recommend some sources we might consult as a starting point, or where we might find some sample language?

MOLINA: Hmm. Well, certainly this is what we do in higher education. We compete for the best students and the best faculty members. And we sometimes compete a little bit to be first to win groundbreaking research. But we tend to collaborate with everything else, particularly when it comes to policy, and guidance, and rules. So there are many institutions, like mine, who have already assembled—I’m sure that yours has done the same—assembled committees, because assembling committees and subcommittees is something we do very well in higher education, with faculty members, with administrators, even with the student representation to figure out, OK, what should we do about the use of artificial intelligence on our campus?

I mentioned before taking a look at the big aspirational declarations by Meta, and Google, and IBM, and Microsoft could be helpful for these communities to look at this. But also, I’m a very active member of an organization known as EDUCAUSE. And EDUCAUSE is for educators—predominantly higher education educators. Administrators, staff members, faculty members, to think about the adoption of information technology. And EDUCAUSE has done good work on this front and continues to do good work on this front. So once again, EDUCAUSE and some of the institutions have already published their guidelines on how to use artificial intelligence and incorporate that within their academic lives.

And now, that said, we also know that even though all higher education institutions are the same, they’re all different. We all have different values. We all believe in different uses of technology. We trust more or less the students. Hence, it’s very important that whatever inspiration you would take, you work internally on campus—as you have done with many other issues in the past—to make sure it really reflects the values of your institution.

FASKIANOS: So, Pablo, would you point to a specific college or university that has developed a code of ethics that addresses the use of AI for their academic community beyond your own, but that is publicly available?

MOLINA: Yeah, I’m going to be honest, I don’t want to put anybody on the spot.

FASKIANOS: OK.

MOLINA: Because, once again, there many reasons. But, once again, let me repeat a couple resources. One is of them is from the U.S. Department of Education, from the Office of Educational Technology. And the article is Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations, published earlier this year. The other source really is educause.edu. And if you look at educause.edu on artificial intelligence, you’ll find links to articles, you’ll find links to universities. It would be presumptuous of me to evaluate whose policies are better than others, but I would argue that the general principles of nonbiased, transparency, accountability, and also integration of these tools within the academic life of the institution in a morally responsible way—with concepts by privacy by design, security by design, and responsible computing—all of those are good words to have in there.

Now, the other problem with policies and guidelines is that, let’s be honest, many of those have no teeth in our institutions. You know, we promulgate them. They’re very nice. They look beautiful. They are beautifully written. But oftentimes when people don’t follow them, there’s not a big penalty. And this is why, in addition to having the policies, educating the campus community is important. But it’s difficult to do because we need to educate them about so many things. About cybersecurity threats, about sexual harassment, about nondiscriminatory policies, about responsible behavior on campus regarding drugs and alcohol, about crime. So many things that they have to learn about. It’s hard to get at another topic for them to spend their time on, instead of researching the core subject matter that they chose to pursue for their lives.

FASKIANOS: Thank you. And we will be sending out a link to this video, the transcript, as well as the resources that you have mentioned. So if you didn’t get them, we’ll include them in the follow-up email.

So I’m going to go to Dorian Brown Crosby who has a raised hand.

Q: Yes. Thank you so much. I put one question in the chat but I have another question that I would like to go ahead and ask now.

So thank you so much for this presentation. You mentioned algorithm biases with individuals. And I appreciate you pointing that out, especially when we talk about face recognition, also in terms of forced migration, which is my area of research. But I also wanted you to speak to, or could you talk about the challenges that some institutions in higher education would have in terms of support for some of the things that you mentioned in terms of potential curricula, or certificates, or other ways that AI would be woven into the new offerings of institutions of higher education. How would that look specifically for institutions that might be challenged to access those resources, such as Historically Black Colleges and Universities? Thank you.

MOLINA: Well, very interesting question, and a really fascinating point of view. Because we all tend to look at things from our own perspective and perhaps not consider the perspective of others. Those who have much more money and resources than us, and those who have fewer resources and less funding available. So this is a very interesting line. What is it that we do in higher education when we have these problems? Well, as I mentioned before, we build committees and subcommittees. Usually we also do campus surveys. I don’t know why we love doing campus surveys and asking everybody what they think about this. Those are useful tools to discuss.

And oftentimes the thing that we do also, that we’ve done for many other topics, well, we hire people and we create new offices—either academic or administrative offices. With all of those, you know, they have certain limitations to how useful and functional they can be. And they also continue to require resources. Resources that, in the end, are paid for by students with, you know, federal financing. But this is the truth of the matter. So if you start creating offices of artificial intelligence on our campuses, however important the work may be on their guidance and however much extra work can be assigned to them instead of distributed to every faculty and the staff members out there, the truth of the matter is that these are not perfect solutions.

So what is it that we do? Oftentimes, we work with partners. And our partners love to take—(inaudible)—vendors. But the truth of the matter is that sometimes they have much more—they have much more expertise on some of these topics. So for example, if you’re thinking about incorporating artificial intelligence to some of the academic materials that you use in class, well, I’m going to take a guess that if you already work with McGraw Hill in economics, or accounting, or some of the other books and websites that they put that you recommend to your students or you make mandatory for your students, that you start discussing with them, hey, listen, are you going to use artificial intelligence? How? Are you going to tell me ahead of time?

Because, as a faculty member, you may have a choice to decide: I want to work with this publisher and not this particular publisher because of the way they approach this. And let’s be honest, we’ve seen a number of these vendors with major information security problems. McGraw Hill recently left a repository of data misconfigured out there on the internet, and almost anybody could access that. But many others before them, like Chegg and others, were notorious for their information security breaches. Can we imagine that these people are going to adopt artificial intelligence and not do such a good job of securing the information, the privacy, and the nonbiased approaches that we hold dear for students?

I think they require a lot of supervision. But in the end, these publishers have the economies of scale for you to recommend those educational materials instead of developing your own for every course, for every class, and for every institution. So perhaps we’re going to have to continue to work together, as we’ve done in higher education, in consortia, which would be local, or regional. It could be based on institutions of the same interest, or on student population, on trying to do this. And, you know, hopefully we’ll get grants, grants from the federal government, that can be used in order to develop some of the materials and guidelines that are going to help us precisely embrace this and embracing not only to operate better as institutions and fulfill our mission, but also to make sure that our students are better prepared to join society and compete globally, which is what we have to do.

FASKIANOS: So I’m going to combine questions. Dr. Lance Hunter, who is an associate professor at Augusta University. There’s been a lot of debate regarding if plagiarism detection software tools like Turnitin can accurately detect AI-generated text. What is your opinion regarding the accuracy of AI text generation detection plagiarism tools? And then Rama Lohani-Chase, at Union County College, wants recommendations on what plagiarism checker devices you would recommend—or, you know, plagiarism detection for AI would you recommend?

MOLINA: Sure. So, number one, I’m not going to endorse any particular company because if I do that I would ask them for money, or the other way around. I’m not sure how it works. I could be seen as biased, particularly here. But there are many there and your institutions are using them. Sometimes they are integrated with your learning management system. And, as I mentioned, sometimes we ask the students to use them themselves and then either produce the plagiarism report for us or simply know themselves this. I’m going to be honest; when I teach ethics and technology, I tell the students about the antiplagiarism tools at the universities. But I also tell them, listen, if you’re cheating in an ethics and technology class, I failed miserably. So please don’t. Take extra time if you have to take it, but—you know, and if you want, use the antiplagiarism tool yourself.

But the question stands and is critical, which is right now those tools are trying to improve the recognition of artificial intelligence written text, but they’re not as good as they could be. So like every other technology and, what I’m going to call, antitechnology, used to control the damage of the first technology, is an escalation where we start trying to identify this. And I think they will continue to do this, and they will be successful in doing this. There are people who have written ad hoc tools using ChatGPT to identify things written by ChatGPT. I tried them. They’re remarkably good for the handful of papers that I tried myself, but I haven’t conducted enough research myself to tell you if they’re really effective tools for this. So I would argue that for the timing you must assume that those tools, as we assume all the time, will not catch all of the cases, only some of the most obvious ones.

FASKIANOS: So a question from John Dedie, who is an assistant professor at the Community College of Baltimore County: To combat AI issues, shouldn’t we rethink assignments? Instead of papers, have students do PowerPoints, ask students to offer their opinions and defend them? And then there was an interesting comment from Mark Habeeb at Georgetown University School of Foreign Service. Knowledge has been cheap for many years now because it is so readily available. With AI, we have a tool that can aggregate the knowledge and create written products. So, you know, what needs to be the focus now is critical thinking and assessing values. We need to teach our students how to assess and use that knowledge rather than how to find the knowledge and aggregate that knowledge. So maybe you could react to those two—the question and comment.

MOLINA: So let me start with the Georgetown one, not only because he’s a colleague of mine. I also teach at Georgetown, and where I obtained my doctoral degree a number of years ago. I completely agree. I completely agree with the issue that we have to teach new skills. And one of the programs in which I teach at Georgetown is our master’s of analysis. Which are basically for people who want to work in the intelligence community. And these people have to find the information and they have to draw inferences, and try to figure out whether it is a nation-state that is threatening the United States, or another, or a corporation, or something like that.

And they do all of those critical thinking, and intuition, and all the tools that we have developed in the intelligence community for many, many years. And artificial intelligence, if they suspend their judgement and they only use artificial intelligence, they will miss very important information that is critical for national security. And the same is true for something like our flagship school, the School of Foreign Service at Georgetown, one of the best in the world in that particular field, where you want to train the diplomats, and the heads of state, and the great strategical thinkers on policy and politics in the international arena to precisely think not in the mechanical way that a machine can think, but also to connect those dots. And, sure they should be using those tools in order to, you know, get the most favorable position and the starting position, But they should also use their critical thinking always, and their capabilities of analysis in order to produce good outcomes and good conclusions.

Regarding redoing the assignments, absolutely true. But that is hard. It is a lot of work. We’re very busy faculty members. We have to grade. We have to be on committees. We have to do research. And now they ask us to redo our entire assessment strategy, with new assignments that we need to grade again and account for artificial intelligence. And I don’t think that any provost out there is saying, you know what? You can take two semesters off to work on this and retool all your courses. That doesn’t happen in the institutions that I know of. If you get time off because you’re entitled to it, you want to devote that time to do research because that is really what you sign up for when you pursued an academic career, in many cases.

I can tell you one thing, that here in Europe where oftentimes they look at these problems with fewer resources than we do in the United States, a lot of faculty members at the high school level, at the college level, are moving to oral examinations because it’s much harder to cheat with ChatGPT with an oral examination. Because they will ask you interactive, adaptive questions—like the ones we suffered when we were defending our doctoral dissertations. And they will realize, the faculty members, whether or not you know the material and you understand the material.

Now, imagine oral examinations for a class of one hundred, two hundred, four hundred. Do you do one for the entire semester, with one topic chosen and run them? Or do you do several throughout the semester? Do you end up using a ChatGPT virtual assistance to conduct your oral examinations? I think these are complex questions. But certainly redoing our assignments and redoing the way we teach and the way we evaluate our students is perhaps a necessary consequence of the advent of artificial intelligence.

FASKIANOS: So next question from Damian Odunze, who is an assistant professor at Delta State University in Cleveland, Mississippi: Who should safeguard ethical concerns and misuse of AI by criminals? Should the onus fall on the creators and companies like Apple, Google, and Microsoft to ensure security and not pass it on to the end users of the product? And I think you mentioned at the top in your remarks, Pablo, about how the founder of ChatGPT was urging the Congress to put into place some regulation. What is the onus on ChatGPT to protect against some of this as well?

MOLINA: Well, I’m going to recycle more of the material from my doctoral dissertation. In this case it was the Molina cycle of innovation and regulation. It goes like this, basically there are—you know, there are engineers and scientists who create new information technologies. And then there are entrepreneurs and businesspeople and executives to figure out, OK, I know how to package this so that people are going to use it, buy it, subscribe to it, or look at it, so that I can sell the advertisement to others. And, you know, this begins and very, very soon the abuses start.

And the abuses are that criminals are using these platforms for reasons that were not envisioned before. Even the executives, as we’ve seen with Google, and Facebook, and others, decide to invade the privacy of the people because they only have to pay a big fine, but they make much more money than the fines or they expect not to be caught. And what happened in this cycle is that eventually there is so much noise in the media, congressional hearings, that eventually regulators step in and they try to pass new laws to do this, or the regulatory agencies try to investigate using the powers given to them.

And then all of these new rules have to be tested in courts of law, which could take years by the time it reaches sometimes all the way to the Supreme Court. Some of them are even knocked down on the way to the Supreme Court when they realize this is not constitutional, it’s a conflict of laws, and things like that. Now, by the time we regulate these new technologies, not only many years have gone by, but the technologies have changed. The marketing products and services have changed, the abuses have changed, and the criminals have changed.

So this is why we’re always living in a loosely regulated space when it comes to information technology. And this is an issue of accountability. We’re finding this, for example, with information security. If my phone is my hacked, or my computer, my email, is it the fault of Microsoft, and Apple, and Dell, and everybody else? Why am I the one paying the consequences and not any of these companies? Because it’s unregulated. So morally speaking, yes. These companies are accountable. Morally speaking also the users are accountable, because we’re using these tools because we’re incorporating them professionally.

Legally speaking, so far, nobody is accountable except the lawyers who submitted briefs that were not correct in a court of law and were disciplined for that. But other than that, right now, it is a very gray space. So in my mind, it requires everybody. It takes a village to do the morally correct thing. It starts with the companies and the inventors. It involves the regulators, who should do their job and make sure that there’s no unnecessary harm created by these tools. But it also involves every company executive, every professional, every student, and professor who decides to use these tools.

FASKIANOS: OK. I’m going to take—combine a couple questions from Dorothy Marinucci and Venky Venkatachalam about the effect of AI on jobs. Dorothy talks about—she’s from Fordham University—about she read something about Germany’s best-selling newspaper Bild reportedly adopting artificial intelligence to replace certain editorial roles in an effort to cut costs. Does this mean that the field of journalism communication will change? And Venky’s question is: AI—one of the impacts is in the area of automation, leading to elimination of certain types of jobs. Can you talk about both the elimination of jobs and what new types of jobs you think will be created as AI matures into the business world with more value-added applications?

MOLINA: Well, what I like about predicting the future, and I’ve done this before in conferences and papers, is that, you know, when the future comes ten years from now people will either not remember what I said, or, you know, maybe I was lucky and my prediction was correct. In the specific field of journalism, and we’ve seen it, the journalism and communications field, decimated because the money that they used to make with advertising—and, you know, certainly a bit part of that were in the form of corporate profits.

But many other one in the form of hiring good journalists, and investigative journalism, and these people could be six months writing a story when right now they have six hours to write a story, because there are no resources. And all the advertisement money went instead to Facebook, and Google, and many others because they work very well for advertisements. But now the lifeblood of journalism organizations has been really, you know, undermined. And there’s good journalism in other places, in newspapers, but sadly this is a great temptation to replace some of the journalists with more artificial intelligence, particularly the most—on the least important pieces.

I would argue that editorial pieces are the most important in newspapers, the ones requiring ideology, and critical thinking, and many others. Whereas there are others that tell you about traffic changes that perhaps do not—or weather patterns, without offending any meteorologists, that maybe require a more mechanical approach. I would argue that a lot of professions are going to be transformed because, well, if ChatGPT can write real estate announcements that work very well, well, you may need fewer people doing this.

And yet, I think that what we’re going to find is the same thing we found when technology arrived. We all thought that the arrival of computers would mean that everybody would be without a job. Guess what? It meant something different. It meant that in order to do our jobs, we had to learn how to use computers. So I would argue that this is going to be the same case. To be a good doctor, to be a good lawyer, to be a good economist, to be a good knowledge worker you’re going to have to learn also how to use whatever artificial intelligence tools are available out there, and use them professionally within the moral and the ontological concerns that apply to your particular profession. Those are the kind of jobs that I think are going to be very important.

And, of course, all the technical jobs, as I mentioned. There are tons of people who consider themselves artificial intelligence experts. Only a few at the very top understand these systems. But there are many others in the pyramid that help with preparing these systems, with the support, the maintenance, the marketing, preparing the datasets to go into these particular models, working with regulators and legislators and compliance organizations to make sure that the algorithms and the tools are not running afoul of existing regulations. All of those, I think, are going to be interesting jobs that will be part of the arrival of artificial intelligence.

FASKIANOS: Great. We have so many questions left and we just couldn’t get to them all. I’m just going to ask you just to maybe reflect on how the use of artificial intelligence in higher education will affect U.S. foreign policy and international relations. I know you touched upon it a little bit in reacting to the comment from our Georgetown University colleague, but any additional thoughts you might want to add before we close?

MOLINA: Well, let’s be honest, one particular one that applies to education and to everything else, there is a race—a worldwide race for artificial intelligence progress. The big companies are fighting—you know, Google, and Meta, many others, are really putting—Amazon—putting resources into that, trying to be first in this particular race. But it’s also a national race. For example, it’s very clear that there are executive orders from the United States as well as regulations and declarations from China that basically are indicating these two big nations are trying to be first in dominating the use of artificial intelligence.

And let’s be honest, in order to do well in artificial intelligence you need not only the scientists who are going to create those models and refine them, but you also need the bodies of data that you need to feed these algorithms in order to have good algorithms. So the barriers to entry for other nations and the barriers to entry by all the technology companies are going to be very, very high. It’s not going to be easy for any small company to say: Oh, now I’m a huge player in artificial intelligence. Because even if you may have created an interesting new algorithmic procedure, you don’t have the datasets that the huge companies have been able to amass and work on for the longest time.

Every time you submit a question to ChatGPT, the ChatGPT experts are using their questions to refine the tool. The same way that when we were using voice recognition with Apple or Android or other companies, that we’re using those voices and our accents and our mistakes in order to refine their voice recognition technologies. So this is the power. We’ll see that the early bird gets the worm of those who are investing, those who are aggressively going for it, and those who are also judiciously regulating this can really do very well in the international arena when it comes to artificial intelligence.

And so will their universities, because they will be able to really train those knowledge workers, they’ll be able to get the money generated from artificial intelligence, and they will be able to, you know, feedback one with the other. The advances in the technology will result in more need for students, more students graduating will propel the industry. And there will also be—we’ll always have a fight for talent where companies and countries will attract those people who really know about these wonderful things.

Now, keep in mind that artificial intelligence was the core of this, but there are so many other emerging issues in information technology. And some of them are critical to higher education. So we’re still, you know, lots of hype, but we think that virtual reality will have an amazing impact on the way we teach and we conduct research and we train for certain skills. We think that quantum computing has the ability to revolutionize the way we conduct research, allowing us to do competitions that were not even thinkable today.

We’ll look at things like robotics. And if you ask me about what is going to take many jobs away, I would say that robotics can take a lot of jobs away. Now, we thought that there would be no factory workers left because of robots, but that hasn’t happened. But keep adding robots with artificial intelligence to serve you a cappuccino, or your meal, or take care of your laundry, or many other things, or maybe clean your hotel room, and you realize, oh, there are lots of jobs out there that no longer will be there.

Think about artificial intelligence for self-driving vehicles, boats, planes, cargo ships, commercial airplanes. Think about the thousands of taxi drivers and truck drivers who may end up being out of jobs because, listen, the machines drive safer, and they don’t get tired, and they can be driving twenty-four by seven, and they don’t require health benefits, or retirement. They don’t get depressed. They never miss. Think about many of the technologies out there that have an impact on what we do.

So, but artificial intelligence is a multiplier to technologies, a contributor to many other fields and many other technologies. And this is why we’re so—spending so much time and so much energy thinking about these particular issues.

FASKIANOS: Well, thank you, Pablo Molina. We really appreciate it. Again, my apologies that we couldn’t get to all of the questions and comments in the chat, but we appreciate all of you for your questions and, of course, your insights were really terrific, Dr. P. So we will, again, be sending out the link to this video and transcript, as well as the resources that you mentioned during this discussion. I hope you all enjoy the Fourth of July. And I encourage you to follow @CFR_Academic on Twitter and visit CFR.org, ForeignAffairs.com, and ThinkGlobalHealth.org for research and analysis on global issues. Again, you send us comments, feedback, suggestions to [email protected]. And, again, thank you all for joining us. We look forward to your continued participation in CFR Academic programming. Have a great day.

MOLINA: Adios.

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