by Seth Simon Davis
17 February 2026
Pitt is launching a new academic Hub for AI and Data Science Leadership (HAIL). GAINS interviews the managing director, Kendra Oliver.
Briefly introduce yourself and say your role at HAIL.
I'm the managing director of HAIL. I have a PhD in pharmacology and also a UX design degree, which is an interesting combination, but I think it really suits thinking about the future of AI. I have a lot of interest in art, science, and communication.
What HAIL is doing, as a hub for AI and data science leadership, is thinking about bringing everybody up to speed with what’s happening with AI and making it applicable for all. HAIL was actually formed from Responsible Data Science at Pitt. And so we have this really core focus on responsible data science and AI, which is now grown into what we're calling HAIL—the Hub for AI and Data Science Leadership. Part of what responsible data science and responsible AI is, is really a human-centered, usability-type implementation for AI and designing AI systems.
How is HAIL bringing everyone up to speed?
We actually published an article over the summer about digital leadership where we talk about confidence, accountability, and agency as the three key attributes we see leaders having. Agency over AI and emerging digital tools and data so that it can really shape the outcomes of how that AI is being used. The confidence to responsibly explore and also recover from any potential issues that emerge. And so that means that people can innovate by combining both artificial intelligence and human insights in a way that really is preventing any harm. And then accountability, not blaming some black box algorithm for harms and then just leaving it at that, but really taking charge of the problem, trying to figure out solutions and basically take that and make it have a positive impact on organizations and society.
How recently did you publish the article?
Yeah, so we actually published this over the summer and it was through over two years of conversations with our advisory board. We have this incredible group of industry professionals that cover a variety of industries and they've given us this really deep insight into what people are looking for, bringing on new hires and expectations. Or the wish list that they may have for new hires as they're coming into the workforce. And so through our conversations with them, through talking about what Pitt's doing in terms of adapting to AI, we've been able to identify these attributes as the key characteristics that they're looking for.
And then we get deeper into skills. And there's definitely this sense for technical skills and having those kinds of abilities. But I think what we're finding more is that the soft skills are extremely important, critical thinking, collaboration, creativity. Those are the skills that really set people apart, make them excel in work environments. And that's really across industry.
Was HAIL around two years ago?
So this is part of that RDS to HAIL transition. Responsible Data Science at Pitt started about two and a half years ago. And that's really laying the foundation for what we're doing at HAIL. It's part of why we've kept data science in our title, even though it's buried in there, data science is the foundation. Additionally, responsibility is a core pillar of what we’re doing at HAIL. And so that's resonated now into what our goals and mission is through HAIL.
What concretely is entailed in RDS’s transition to HAIL?
As part of this, we really have this unique opportunity to take the last two and a half years of work that we've been doing for RDS at Pitt and reimagine that thinking more specifically around AI. I’ll briefly talk about our vision, mission, and goals for HAIL, which again, we've learned a lot over what we've already done for RDS at Pitt.
Our vision with HAIL is a world where teams align human, statistical, and computational knowledge with the shared principles of communities to be able to deliver very practical, very context-aware solutions that are relevant across a variety of industries. We're hoping to do that through enabling trustworthy AI as well as data science solutions. Thinking very practically with real world decision making. Internally, we see that it's absolutely necessary to break down silos between schools and departments in order to build impactful partnerships that expand opportunities for all of Pitt's learners, staff, and faculty. And through that, I think we're going to build and help support everyone to become digital leaders. So this isn't just in CS, this isn't just in SCI. This is really across the university.
Right, so part of the transition from RDS to HALE is that, one, it's specifically around AI, whereas Responsible Data Science is about data science more generally. HALE sees AI as being this thing that has this huge opportunity to form new leaders because it's what everyone is looking at these days.
What are some ways that HAIL is hoping to break down silos between schools and departments?
We have three main goals with HAIL. One is cultivating and connecting the ecosystem and scaling innovation, which is again really tied into that network piece. We're also establishing and sharing strategic guidance for AI and data science across the academic mission. And then, as I mentioned, we really do think about products too and how this is actually implemented. But going back to cultivating and connecting the ecosystem, one of the ways that we're doing this first with a project is our roll-AI-dex. We’re using it as a way to get a sense of, and connect, everyone currently working on AI projects. And so this is looking across labs and research groups. It's looking across organizations. It's collecting products, things that people have made, and networking this as a searchable, interactable graph that people can see what's happening at Pitt.
There's really so much creative and impactful work that's happening at Pitt, but we found that it’s within its individual silo. And we're hoping that just by creating this roll-AI-dex, people will be able to see the breadth and connect across existing silos in a way that they haven't before.
Is Roll-AI-Dex online anywhere?
We are getting it started. Emily Durning is a new administrative research assistant that HAIL hired as part of this year. She's currently designing it. There are a few blog posts about this on our website if you're interested in learning more. And of course, because as you're scanning and just word of mouth finding these AI groups, we also have an intake form. So if we've missed something or if you know of something that you want to share, you can use this intake form as a way to get connected with our network.
Besides Roll-AI-Dex, are there any projects that HAIL is working on right now that you’re excited about?
So many projects. It's anywhere from policy around how to use AI to specific use-case needs. They're still formulating some of the titles of these groups, but there is a gen AI frameworks faculty group that has been meeting to talk about gen AI use within higher education as well as K-12 and developing some AI literacy frameworks.
One of our partnerships that I'm very excited about is our Carnegie Heroes Fund Commission partnership. They are an incredible organization that started in 1910 and have this really rich historic data about heroism and altruism. And so we're helping both to digitize that work as well as make it searchable and accessible to researchers who are interested in studying altruism and heroism. They've been incredible partners. That's one project that I love to highlight.
Another one that we have, as part of RDS at Pitt, is the RDS Scholars Program, which is for undergraduates to have an opportunity to explore what responsible data science is and how it's applied across different contexts. This year, that program is led by Nora Matern, who’s in SCI.
Nora was able to actually run a workshop with these students about creating their own personal Gen AI frameworks, which reflect their personal values on how and when they should use AI. If it should be used, when it should be used, and more importantly, when it should not be used, right?
And so I think that's been a really fun, new opportunity that we've had pop up. She's actually working right now on a blog post describing that. And I think that's something where maybe we all should take a moment and think about our frameworks for using AI and when it's appropriate.
In the K-12 space, we have incredible partners in the Data Jam, which is a program that I think has been running for over 10 years by Judy Cameron. And it's really about asking answerable research questions and understanding data science. Understanding how you make comparisons. But again, they have this incredible wealth of information on students. These are usually high school students, some community college students, but mostly high school students that have given proposals and then responses to those proposals. So for instance, if they're asking questions that aren't specific or answerable, using statistics, these responses give feedback and suggestions for how to update their proposal. And so using that information, we've actually created version one of a chat bot that students can use to modify their proposals in a way that hopefully gets them to that ideal state, testable questions faster. And it's been really interesting to try and develop that chatbot in a way that isn't giving answers, that it's really focused on helping and supporting the students in their learning. The idea is that they would use it.
I’m really excited to share that we have a new leadership structure. Justin Kitzes, from Biological Sciences, is going to serve as Associate Director for Research. We also have Nora Matern starting as Associate Director for Responsible Data and AI Practice. And again, she also leads the RDS Scholars Program
How is HAIL serving the needs of Pitt’s students?
Part of serving Pitt students comes back to supporting faculty who are actively teaching. One of the things that we're really interested in is meeting faculty where they are in terms of their personal views on AI and when and when not to use it, when it's appropriate for their teaching. But also providing resources for them to think about how to leverage it in their teaching. Another project that I'll mention that I think does this really well is our concrete curriculum, which is a set of data sets that have contextual information that can help one expose learners to real world situations in a “choose your own adventure” sense. It's a resource for faculty to use, so they're not starting from scratch. As part of that, I think we need to do more on training faculty how to use AI in their teaching, which is something that we're excited to do with a lot of other partners as well.
Let me really quickly mention LSET and the University Center for Teaching and Learning are two of those really key partners in pedagogical approaches.
The concrete curriculum is something that we actually had initial funding through an RK Mellon grant to develop. And again, it's all about context around data sets so that students can learn how to think with and beyond data.
Was this before or after RDS became HAIL?
This was something that had started when we were already at Pitt, but it's one of the key projects that we're gonna be pushing forward as HAIL.
Any closing remarks?
Thank you so much for the opportunity. We're really excited to work with all types of people across the university and beyond the university. We really, again, are focused on practical uses and making sure that AI matches human needs, human values, and human principles.