Artificial intelligence has been part of our lives for years, but its rapidly expanding power and reach are transforming our homes, workplaces and classrooms. In part 1 of this special two-part edition of the Engagement Ring, Dr. Mila Gascó-Hernández and Dr. Hany Elgala, associate directors of UAlbany’s AI & Society College, discuss what makes this moment in AI different, what the technology can and cannot do, and how the University at Albany is integrating AI education across its nine schools and colleges. They also explain why preparing students to use AI responsibly — and for the benefit of people and society — is essential.
Part Two of this podcast: Developed by Humans, for Humans: Living, Learning and Working with AI
Dr. Mila Gascó-Hernández, Professor, Department of Public Administration & Policy, Rockefeller College of Public Affairs & Policy; Research Director, Center for Technology in Government (CTG); Associate Director, AI & Society College
Hany Elgala, Associate Professor, Department of Electrical & Computer Engineering, College of Nanotechnology, Science, and Engineering (CNSE); and Associate Director, AI & Society College
AI & Society College at UAlbany
Center for Technology in Government (CTG)
From the UAlbany News Center: UAlbany Launches New AI & Society College, Research Center
Definition of AI from the OECD:
“An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.”
OECD stands for the Organisation for Economic Co-operation and Development. It is an international organization through which governments cooperate, study public-policy challenges and develop shared standards and recommendations.
It currently has 38 member countries, including the United States. Its work covers areas such as education, economics, employment, taxation, technology and artificial intelligence.
Special thanks to our recording engineer Scott Freedman of the University at Albany's Digital Media Services.
The Engagement Ring, Episode 44:
Developed by Humans, for Humans, Part One: Understanding This Moment in AI’s Evolution
[Lively, upbeat theme music plays as program host Mary Hunt introduces the program and plays excerpts from the program.]
ANNOUNCER/MARY HUNT:
Welcome to The Engagement Ring, your connection to an ever-widening network of higher education professionals, scholars, and community partners working to make the world a better place. I'm Mary Hunt. Today on the podcast…
MILA GASCÓ-HERNÁNDEZ:
AI is our competitive advantage or can become our competitive advantage. We're a pioneer, and we are being acknowledged and recognize as such.
HANY ELGALA:
It's good to work together as a community and fulfill the mission of New Albany and higher education by facilitating the knowledge and the resources and the skill sets so as to be ahead of the game in terms of AI.
ANNOUNCER/MARY HUNT:
Artificial intelligence is everywhere these days-in the home, in the workplace, and now in the classroom. I'll talk with Dr. Mila Gascó-Hernández and Dr. Hany Elgala, associate directors of the University at Albany's AI and Society College, about how the college is helping students, faculty, and staff prepare for a world increasingly shaped by AI. With a strong emphasis on trustworthiness, equity, privacy, and accountability, the college integrates AI education across all nine schools and colleges at the university, ensuring that every student, whether they are pursuing a degree in STEM, business, social sciences, or the arts, has access to AI-infused learning. But teaching students how to use AI is only part of the equation. Just as important is helping them understand how to use it responsibly, and how to harness its potential to benefit people and society.
HANY ELGALA:
It's pure mathematics, so we shouldn't consider these human characteristics as something that AI should provide.
MILA GASCÓ-HERNÁNDEZ:
I think that human thinking and analysis and interpretation and an understanding of things is something that AI cannot still do, and I'm not sure it will do. And if it does, I'm not sure it should be doing it.
ANNOUNCER/MARY HUNT:
There was so much to talk about. We decided we needed two episodes of The Engagement Ring. Here's part one of my conversation with Mila Gascó-Hernandez and Hany Elgala.
[Music fades]
MARY HUNT:
Artificial intelligence… it's actually been part of our world for a long time now, often in ways that many of us may not have even recognized as AI. We use it as part of our daily lives, but it seems in the last few years, or particularly now, things are changing, or the pace of AI development is really picking up. What has changed, and what makes this moment in AI particularly significant?
HANY ELGALA:
Actually, now there is a lot of investment and activity, and models are improving and actually self-improving. So, we have, every couple of weeks or every month, announcements about new models, new apps, and yeah, that's why it's not easy to cope with the pace of the progress. But that's the nature of the intelligence here. It's about maybe we have reached the point of self-improving. That's why we see progress in a pace where it feels like a non-human progress. I think that's the reason, and it will get even faster moving forward. So, for your audience, they should expect that this should be continuing like this, but they shouldn't be overwhelmed. And hopefully today we are going to clarify things.
MILA GASCÓ-HERNÁNDEZ:
I think there are two important things that are different. One is the speed, as Hany was mentioning. Things are happening much faster now, and we are not realizing about the changes, and they're already here. But the second thing with AI, I believe is its reach. AI before was maybe limited to specific organizations, industry, maybe some governments, but now AI is all over society, and we are, as you were saying before, using AI with Siri, maybe taking an autonomous vehicle, even having a robot at home, and we are getting used to that, and therefore I don't know if this is a right word, but AI is being democratized, if you will, and made accessible to everyone.
MARY HUNT:
And where are we? Do you think in its evolution? Are we at the beginning? Are we in the middle? We're certainly not close to maximizing its potential. But
HANY ELGALA:
I mean, historically, AI started in the 50s, yeah, when this term was coined, yeah. And then there were ups and downs, and but I think it's a pivotal moment is 2022. Yeah, this is when the very first product was available to the public to try and work with. Yeah, from there things like took over in terms of the potential of generating. It's not… no longer about like you have your like data and you're trying to make a decision supported by the artificial intelligence. No, you can generate things. Yeah, and I think this is mainly what made the difference. You can generate like text, image, video, code, websites, many things. I think this is the main difference starting 2022. So, it's a short period of time actually. So we are at the very beginning, like four years, and with the acceleration that I mentioned earlier, like you never know what the future will bring here. But hopefully the acceleration will be more focused on society and solving bigger problem, and yeah, this this should be like the impact we see a positive impact of the technology.
MARY HUNT:
When you say 2022, was that ChatGPT? Is that when the… you said the product?
HANY ELGALA:
Yeah, yeah, that's the ChatGPT, which is a product from one of the like companies that came in specifically on November 2022.
MARY HUNT:
What's something AI is remarkably good at maybe that surprises you, and something it's remarkably bad at that people assume it can do. Is there anything comes to mind?
[Laughter]
MILA GASCÓ-HERNÁNDEZ:
I would say that it's very good at collecting information. Like before, when you know I was writing, for example, an article, and I had to look for sources of information for other articles, for journals, whatever. Of course, you had to do it more manually. You could still use Google, you could still use the database from the university, but you had to spend much more time in identifying sources of information. Now it is much easier for me to just ask Microsoft Copilot or Claude or, those are the two tools I use mainly, and have the tool identify many sources of information that I can go to and look at, and I get that information right away. So, for me, collecting information in a faster way is one of the things that, and of course, that has to be checked. Right? It's not that I take the source of information as the right one, but it's an ability that the tool has, and that has helped me a lot in being more productive in the end.
MARY HUNT:
Hany, how about something it's not quite there yet with that? People may just have this assumption it can do anything. But what isn't it so great at?
HANY ELGALA:
I think what's not great is this human touch, like human social component that is very important to humans. Even if it can mimic this thing, we see several people like use it for mental health consulting and so on, like this could still have a potential if it is controlled and should go through a solid approved process, but like caring and honesty and trustworthy and all these aspects, you can you can feel as if this AI is trying to reflect on these things, but actually, and when we talk a bit technically, it's pure mathematics that is going on behind the scenes So, we shouldn't consider these human characteristics as something that the AI should provide.
MARY HUNT:
I want to talk some more about that… yeah, Mila, go ahead.
MILA GASCÓ-HERNÁNDEZ:
I wanted to also add, and it is very related to what Hany is saying. I think that AI cannot replace human thinking. We always say AI is about identifying patterns, but the identification of patterns does not… it brings you information about whatever topic you want to know about, but it doesn't mean that this is the type of thinking that you, as a human, need to do about a certain issue that it's of interest to you or that you're working on. So, in addition to relationships, I think that human thinking and analysis and interpretation and understanding of things is something that AI cannot still do, and I'm not sure it will do. And if it does, I'm not sure it should be doing it.
MARY HUNT:
We're going to talk about that too. So let me ask you this, though. UAlbany is really leaning into AI right now, in its teaching, its research, the way it's looking at the disciplines. Though the technology is still evolving, evolving quickly, we don't know what lies ahead, why was this the time for the university to really focus on AI through all those ways—teaching, learning, experiential learning, research—and what kind of changes did you make to do that?
HANY ELGALA:
I think… remember when we mentioned ChatGPT that came out in November? Actually, the university started even before the ChatGPT moment. Yeah, so I think it was in in June, July 2022 that the AI Plus initiative started at the university. I think it's critical because artificial intelligence, especially in higher education, it's not just like a technology where you just deploy. So, it's not a technology project. It's going to change several like aspects of higher education, and so it has to be taking time, enough time. Yeah, it's a strategic, futuristic approach to start as early as possible thinking about AI, experimenting about AI, empowering the community, faculty, students to get engaged with AI because it takes time. It takes time to prepare faculty. It takes time to change the curriculum and infuse it. It takes time to evaluate and do several iterations instead of just like waiting and trying to catch up later. Yeah. So, we have enough time to really do it pedagogically, establish the governance based on our values at UAlbany, so I think that's the advantage of starting even before the ChatGPT moment.
MILA GASCÓ-HERNÁNDEZ:
I also think that for the University at Albany, investing in AI was kind of identifying a competitive advantage. Often there have been discussions about what is that we do that is unique in comparison to other higher education institutions, and we have had several, you know, answers to that, but there was never a common answer this is what characterizes us, and I think that now with AI, it is much clearer that AI is our competitive advantage or can become our competitive advantage. We are a pioneer, as Hany was explaining, and we are being acknowledged and recognized as such. And therefore, for the students, for faculty who want to work here, they might want to come to UAlbany precisely because of the work that we are doing on AI.
MARY HUNT:
Is there a risk in a university not acting aggressively enough at this time, or not really jumping in and starting to address it? As you say, Hany, it's going to take years. You can't fall behind.
HANY ELGALA:
Yeah, you can't fall behind, and you have to acknowledge that it's accessible by students, accessible by faculty. So it's good to be transparent and work together as a community, and fulfill the mission of UAlbany and the higher education by facilitating the knowledge and the resources and the skill sets, so as to be ahead of the game in terms of AI, whether it's being efficient in using AI, whether we are talking about generative AI like proper prompting and how to evaluate the output and several other things, maybe being responsible, so like how to disclose the disclosure of the use of AI or related activities, as well as ethical also, because we like there are several topics under ethical, whether it's the impact on environment, whether it's the IP and how data was scraped from the internet, and also the bias that this could create based on the data as one source of bias that was used, as well as also inequality in terms of access, yeah. Whether it has to do with like teaching or even conducting research, because if UAlbany, as Mila was saying, is not providing resources to the faculty conducting research and teaching, the gap is going to be widening, and we do not want to have this happening.
MILA GASCÓ-HERNÁNDEZ:
And I think that we acknowledge that there might be faculty, there might be students… there have been so many complaints by students, by the way, in the graduation ceremonies last May, that do not want to use AI. What I think we are trying to do at UAlbany is not to push AI. Of course, we're giving resources to everyone who wants to use AI, but for those who don't want to use AI who are still skeptical or fearful of AI, still we want to have them join critical conversations about AI, and this is something that we have done during the AI academies that we have been teaching during the summer. There were many participants who were not on board with using AI, with students using AI, and yet we had fantastic conversations with them about thinking critically about AI.
MARY HUNT:
How have you prepared the university for the effort and for this commitment in terms of, say, investment, technology, teaching, learning, collaboration across the disciplines. I know that's important. What changes have you made?
HANY ELGALA:
Actually, like on the AI and society level, I mean, before the college, we had this 27-cluster hire. So already the faculty member who had expertise in AI on different disciplines came to UAlbany, but as a college, I will mention the four pillars that that we always use to highlight the mission and the vision of the of the college. Educate, so first is like several initiatives to infuse the curriculum, like whether through the microcredentials that we are actively working on, also like working with the nine schools and colleges. Just for your audience to know, we are not… our name is AI and Society College, but we are not enrolling students in the college. We belong to all nine different schools and colleges, and we work with them to come up with new courses, new programs, new minors, new certificates. So, this is about education, and when we are working on education, we try to not just to create these like courses and programs as a sort of a classical way of designing a course, but we would like to have an experiential learning component in the course, project-based learning in the course, interdisciplinary team-taught courses if possible. So, this is like the criteria that we try to push when it comes to education. I mean, we have three more pillars. I will mention the second one, and I will let Mila talk about the third and the fourth one. The other pillar, which is also starts with E, all the four pillars, they start with E, is empower. So, we are empowering our community members, whether faculty members through like a fellowship program. We have in the in the previous academic year, creation of four new courses, one microcredential, as well as two different tools of AI, one AI tutoring and one research-based learning or project-based learning. We also have doctoral dissertation fellows where we also support PhD students. We work with them on projects, their research project at the intersection between AI and society, as well as also we engage them in teaching one of our microcredentials, one of the courses that that is part of the microcredential. We also had the experiential learning… masters experiential learning fellowships, and I experienced this actually firsthand. We were talking about a student who maybe having a mixed feeling about AI, maybe curious and at the same time skeptical, and they don't feel confident. Actually, two of the four students they didn't have a STEM background. Like one of them, she was from the public affairs and policy, and the other one was business, the Massry School of Business, and they developed for the college tools and apps without knowing how to code. And at the beginning, they were like afraid of taking the step and doing this, you know, this term vibe coding things. But with. The proper motivation and like guidance, where to start, what tools to start, and so on and so forth, they were able to produce nice tools and apps, and hopefully soon we are going to have some pilots on these apps. Yeah. So, these are two things. Yeah. So maybe Mila, you can highlight the two other things…
MILA GASCÓ-HERNÁNDEZ:
Experimental and engagement.
HANY ELGALA:
Experimental and engagement, yeah.
MILA GASCÓ-HERNÁNDEZ:
So, for…Let's start with engagement because Hany has left me the experiment part, but that's actually what he likes the most.
[Laughter}
HANY ELGALA:
Okay, I will take over there.
MILA GASCÓ-HERNÁNDEZ:
So, engagement clearly engagement is about engaging with the community. Usually, this engagement is taking place through events, and we can talk about different types of events. Two important events that we had last year was participation in the Showcase. We brought all of our community together. We had a very interesting agenda for the day, and people interacted, and people presented their work, and we raised visibility about what can be done in the field of AI. We also have more traditional events, if you will, where we have a speaker, and there is a presentation, and then a discussion about a topic. Usually, these events, which are open to the community are done in collaboration with the research center, with the AI and Society Research Center through a kind of virtual unity, if you will, that we call the consortium. So, the consortium holds activities that are shared between the AI and Society College and the AI and Society Research Center, and we have done several of these activities and several of these presentations throughout the year, as I said, open to the community. We also have other types of events. We had a social last year where we brought the community, but also the university as a whole. to celebrate our achievements throughout the year. So, engagement with you know or through different types of events. When we talk about engagement, we also talk about engagement with our other higher education institutions. We have… we are in the middle of or starting the second year of a project of a big grant funded by SUNY, that we called Leveraging AI, and we are collaborating with SUNY Oneonta, SUNY Cobleskill, and Hudson Valley Community College. And through that engagement, that interaction, that collaboration, we have been able to teach three AI academies throughout the summer. We have also been able to establish a faculty exchange program where faculty from the different campuses have been collaborating on designing and setting up new programs about AI, and we are very soon going to celebrate our first challenge about AI, also in collaboration with these three other campuses.
HANY ELGALA:
The final pillar of the college is experiment. Definitely, we would like to have as many members of the community engaged. So, we have a space we call it AI maker space where we had we have for example, configured 10 workstations with different configurations. All of them are like GPU-enabled. GPU is the like the hardware AI processor, if you will. Different configuration where they can experiment with models locally. I need to mention that also for the community, on-prem here, we have also access to NVIDIA GPUs and AI use Spyre from IBM. But this specific space is where the community members can have local access to the model and tinker with the model, like develop projects that have maybe some peripherals connected to the workstations, wear a virtual reality headset, and they can develop something where the model is running on the machine itself, so they have more flexibility. So, this is like one activity that we do with within the experiment pillar of the of the college.
MARY HUNT:
And Mila, you mentioned Claude before that you use Claude in your work sometimes. So, I thought it would be fun to ask Claude if he had or she or it had a chance to ask you folks a question. What would that one question be?
[Laughter]
MARY HUNT:
So, here's Claude's question: What does AI literacy and/or preparation actually look like across the various disciplines, for example, humanities student, an English student, history or fine arts? How is it different versus what a STEM student's experience might be like? And how do you avoid a one-size-fits-all curriculum? Claude snuck in two questions there.
[Laughter]
MARY HUNT:
Whoever would like to take that.
MILA GASCÓ-HERNÁNDEZ:
Mm-hmm. So, what we are doing, and I will bring back the AI academy, not only because we have taught it in the past, but because we are finally going to offer an AI academy this year for our UAlbany faculty. The AI academies that we taught in the summer were taught in SUNY Oneonta, Cobleskill, and Hudson Valley Community College, but we didn't have the opportunity to include our faculty, and our faculty requested to have one of our own. So, we're going to have.
HANY ELGALA:
So, this is exclusive announcement.
[Laughter]
MILA GASCÓ-HERNÁNDEZ:
Exactly. This is an exclusive announcement. So, we are building a curriculum that actually is of interest to any discipline, and that means that we are not going to go into the details. For example, we are not going to show how to code, or we are not going to show how to write in English using AI. That's you know specific courses that can still be taken, can still be offered, but that's not what we are trying to do in this academy. What we're trying to do is to raise awareness about AI in higher education and to give participants tools to integrate AI in their teaching, but also to support students that are using AI, so that use of AI is ethical, responsible, critical, as Hany was referring before. So, we are trying to build a curriculum that is going to be useful for everyone, regardless of the discipline, and that means that the curriculum is also going to include several discussions, and that was our experience during the summer. Several discussions about the concerns that faculty have when it comes to AI. They're not so concerned about the technical aspects of AI or how to use a specific tool for a specific class or a specific discipline. They are concerned about how AI is impacting higher education, and that's what they want to discuss, and that's what they need to think about and to get resources for it.
HANY ELGALA:
Yeah, if I may add, I think that… I will take it from the last point that Mila mentioned. We are not preparing students to use a specific tool or remember when we are talking about historically how AI is developing, where we are in terms of development, but also, we are not preparing them for a specific moment of the technology, because you cannot predict the future. So mainly like… and this is time where it's good to mention the microcredential structure and this is exactly how we approach like discipline by discipline and not like one size fits all yeah, but we start with like a common knowledge. You can call it like AI literacy, where you have understanding about what AI can do, what AI cannot do, and who can be impacted by AI, who is responsible, and all the privacy, security, trustworthy, and all these elements, how we bring them in the picture of AI. So, this is where the microcredential starts. We start with a one-credit hour course. It's UUNI 118, where these topics are covered within the allocated like time and the structure of the of the course, but the second course, which is… it’s a three-credit hour course; it provides more depth and also exposes to some like technical understanding of what's going on behind the scenes without the programming aspect. So, these two courses they form what we call an AI fundamental microcredit, a microcredential. It's a four-hour credit microcredential. However, there is a third course so as to complete the stack, and this one is a discipline specific. So, faculty members within the different schools and colleges and department they take over from after the 135 course and they introduce students to specific data sets, specific concerns within the community or the discipline, and all the nuances related to this discipline and how it is related to AI. So, it's a stacked approach. Start with a common knowledge to make everyone on the same page, and gradually, step by step, you increase the depth, still general depth, but the third course make it more discipline specific.
MILA GASCÓ-HERNÁNDEZ:
I would like to clarify that we are talking about two different programs with different audiences. When we talk about the AI Preparedness Academy, our audience is faculty. Microcredentials our audience are students, and in particular, undergraduate students. We have plans to make these microcredentials open to graduate students as well, even professionals outside of the university. But most of the microcredentials so far are at the undergraduate level.
MARY HUNT:
Well, I didn't want ChatGPT to feel left out, so I asked ChatGPT for one question…
[Laughter]
MARY HUNT:
… and Chat's question was AI is developing faster than our institutions and policies can often keep up. What responsibility do universities like UAlbany, have not just to advance AI, but to help determine how it should be used, who benefits from it, and what guardrails society needs.
MILA GASCÓ-HERNÁNDEZ:
Hmm.
MARY HUNT:
That's a tough one.
MILA GASCÓ-HERNÁNDEZ:
I think that they are… higher education institutions are a key stakeholder that needs to work with governments and other stakeholders in the regulation of AI in society. I come from public administration and policy, so my perspective is that AI needs to be regulated in different dimensions of society. I come from Europe, so I believe in regulations and the role of government, when there might be things that raise risks, so I do believe that higher education institutions, universities, need to contribute to this governance of AI by contributing their knowledge and their expertise in how this technology, but technology, generally speaking, needs to be limited, if you will. I don't want to say limited, and I know that Hany might not agree with this… needs to be controlled or needs to be…
HANY ELGALA:
Regulated?
[Laughter]
MILA GASCÓ-HERNÁNDEZ:
Yeah, regulated. I will use that. Yeah, how it has to be regulated, taking into account what the university knows and the use that students, faculty, staff make of this tool. In the end, what is risky when using AI in higher education contexts, that's the contribution that these higher education institutions can make to the governance of AI. And so, for me, universities are one stakeholder more in the regulation of AI. Now, I also want to say that this is not new. We talk about AI now, but many years ago, when other technologies were in place, there were groups, there were associations in higher education that they were also thinking about. Critically thinking about how technology could change higher education at that specific moment. What is changing is the technology and the capabilities of the technology, and therefore there might be more to be regulated. But this kind of thinking, these reflection processes, are not new for society, for government, for higher education. We have always wondered the same things when technology has been perceived as risky, threatening to the things that we do. So, there are many conversations about technology. AI is now reliving those conversations, but we can still, you know, learn from what we discussed in the past and what we said we were going to do in the past,
MARY HUNT:
Are there any regulations currently on AI? Are they local? Are they state? Are they federal? Or what's the status of regulating AI?
HANY ELGALA:
I think there are several efforts on several levels. Like as Mila was saying, Europe definitely is leading with regulations, and they categorize the risk of the application, and they have also regulation on the data, how the data can be used and stored, and stuff like that. There are also regulations on a state level, but in general, like it's not like a unified regulation, or there is consensus when it comes to like international regulation where the majority of the nations or the institutes are following, so it depends where you are, which state you are in, which country you are in. You are going to follow a certain regulation, and maybe like totally different if it exists even because in some places there are no regulations whatsoever, so it's still… and this is the nature of the dynamics, yeah. Because if you put regulation, it's good to put regulation like because it takes time, but at the same time it's a dilemma because the capabilities of the models and the apps keep improving so the regulations, they have to keep improving as well so it's yeah there are regulations but I cannot refer to other than Europe which are like trying to deploy it in different phases, like yeah. I mean, in the U.S. you can feel the tone is changing the last couple of weeks or couple of months. Whether it's coming from CEOs of big companies and like you mentioned ChatGPT, like let let's because ChatGPT asked this question. Okay, so OpenAI CEO was recently mentioned that OpenAI volunteered to somehow pause or somehow limit the activities or somehow control the pace of the activities. So, this is self-regulation, self-governance. I'm not sure whether this is actually effective or somehow, it's serious or just like PR for the for the company. But yeah, other than like some initiatives, there is no like regulation in specifically in the U.S.
MARY HUNT:
Do you see a day when it might be, or it might have to be? The thing about AI is, it's already in everything we do. It's not a technology that people, oh, I’m going to go out and buy that now or I'm going to try that out now. It's already in our lives, you know.
MILA GASCÓ-HERNÁNDEZ:
I do think that there should be regulation. I do not know if we will see it internationally or in the U.S. One classic dilemma that we've always taught about when we teach technology, particularly technology in government, is that regulation hinders innovation, and depending on the context, the role and the priority that innovation has is going to change. Again, if we go back to Europe, why is there an AI Act that all the countries that belong to the European Union need to implement in their countries? Because innovation matters. Of course, innovation always matters, but fundamental rights matter more. In the U.S. I don't want to say that fundamental rights matter more, But AI data, innovation are seen are perceived as economic assets that have an impact from an economic point of view, and that that's why the U.S. is seen as the capitalist paradigm, right? Because the economy matters more than anything else. So, context and history, in the end, determines how we think about different things, determines how we think about technology, determines how we think about AI, and that makes me believe that it will be difficult in the U.S. to have a unified regulation. Now we see differences in states. There are states that are not regulating. There are states which are closer to European Union perspectives that are regulating AI. The same with local governments. We have local governments like New York City that are regulating AI. Even if there is a state regulation, they are also regulating AI at the local level, and there are many other local governments which are not. So, contextually speaking, we are going to see many differences. Of course, if countries cannot agree internally on having a unified regulation, it is impossible that they agree, you know, at the international level to get anything. In one of my classes, I use this vignette where there are different animals. Each animal is representing a country, and they are all saying we need to collaborate to regulate AI. And then underneath, you know, like the different circles. That indicates someone is thinking. Each of them exactly is saying, but we have, or I have to be the first one to implement and you know create it. So, I think that tells you a little bit the difficulties of doing something at the international level.
HANY ELGALA:
If I may add, I think coming with a unified regulation, there is a belief that it has to be, hopefully not the case, a major incident that is happening, whether it's related to cyber security attack, hopefully not biological weapons, then like all nations are going to get together. But, however, it's good to start early. Back to the to your question related to was this the proper timing for the university to start like working with AI? I think for humanity and the society it's good to start as early as possible, regardless how the technology is going to be changed. But there are, I mean, Mila highlighted several facts that are not like somehow contributing to this unification, and I will mention it specifically on a nation level, like there is, like not even on the nation level, within companies there is a like a race who gets first to better model and like the terms super intelligent and general intelligence so this race between companies and between nations also is contributing to not coming up with a unified regulation.
MARY HUNT:
Well, you have in in the AI and Society College, in addition to integrating AI education across the disciplines, you've made a commitment to emphasizing trustworthiness, equity, privacy, and accountability. Why was that important, and how do you do that?
MILA GASCÓ-HERNÁNDEZ:
We want to use AI in a way that maximizes the benefits and minimizes the risks. And there is already a lot of evidence. There is not so much about the benefits. We do know about potential benefits. We do not really know about real benefits, but there is a lot of evidence about potential risks, and so by emphasizing trustworthiness, privacy, responsibility, we are actually referring to those risks and acknowledging that a misuse of AI can result in those risks, and therefore, instead of leveraging and boosting the benefits, it might cause harm, and that's why these are not only the principles that we have. This is a set of examples of the principles that we want to pursue at the AI and Society College. But the idea behind this is we are recognizing that a misuse of AI is harming and it can bring risks, and we want to avoid these risks with our approach to AI.
HANY ELGALA:
You can consider that the technology is agnostic from the get-go. But the reason why the trustworthy and all these topics are very important because it's not about just developing a technical system. It is designed within a context where it's going to be deployed in the society and being used by us humans, yeah. So, all these aspects they have to be considered, and like Mila mentioned, why they are important and the way how we somehow work on these aspects is, I think, through our fellowship programs. So, if you see the list of our… actually now I'm advertising for the website, so you can go to our AI and Society College website and see the list of our fellows. You can see that the majority of them are coming from non-STEM disciplines, humanities, social science, the arts, and every single project is dealing with one of these aspects.
[Music fades in]
HANY ELGALA:
So this is how we approach this situation and how we support and empower faculty members who are experts in trying to focus on these aspects related to this technology.
[Music fades in]
ANNOUNCER/MARY HUNT:
And that's where we're going to pause. But we're definitely not finished. In part two of our conversation, I'll ask Mila and Hany more about the students' experience with AI and what it really means for all of us to live, learn and work alongside the increasingly powerful technology of artificial intelligence. I hope you'll join us.
Mila Gascó-Hernández and Hany Elgala are the associate directors of the AI and Society College at the University at Albany. Dr. Gascó-Hernandez is also the research director at the Center for Technology and Government and professor in the Department of Public Administration and Policy at the Rockefeller College of Public Affairs and Policy. Dr. Elgala is an associate professor in the Department of Electrical and Computer Engineering in the College of Nanotechnology, Science, and Engineering, and the director of the Signals and Networks Lab, SINE Lab, at the University at Albany.
For more information on Dr. Gascó-Hernández and Dr. Elgala and the AI and Society College, visit the resource page for this podcast online at the engagement dash ring dot Simplecast dot com.
The Engagement Ring is produced by the University at Albany's Office for Public Engagement. Special thanks to our recording engineer Scott Freedman of UAlbany's Digital Media Services. If you have questions or comments or want to share an idea for an upcoming podcast, email us at UAlbany O P E at Albany dot E D U.
[Music fades out]