 When we built the learning platform, LearnGala.com, we did so as an open source, open access tool that could quickly enable people to make new kinds of content for the environmental and sustainability challenges we face in our time. Content that could be quickly bootstrapped into existing curricula where there aren't good enough learning tools like the ones we need to manage our systems differently and better for the future. Our theory of change was pretty simple. We felt that makers are very empowered and that any learner should not just be able to use content but also be empowered to try their hand at making content that reflects their community's concerns, their individual skills and perspectives, their historical knowledge and their sense of future tools that might be important to resolving current challenges. So that's the short answer to how we attract students to our PITUN work. We make it fun for them and empowering for them, not only to use content but to make it and to make it better in accordance with the ways that they learn best. There are other ways we've moved to attract students and one of them is to partner with existing problem-driven initiatives on our campus like the U of M internally funded Blue Skies Initiative. That initiative, pioneered by civil and environmental engineer Luke Baraskin, has created trust and collaboration between our campus and the Civic Water Utility in Ann Arbor, Michigan. As a result, it's made it possible for students to do something else they really love to do which is to work directly with practitioners in the sector they're interested in and find out if that sector is one that's of longer-term career interest to them and where they might make meaningful contributions. Turns out, that's also very useful because in the water sector in Michigan, we have many highly-mediatized problems like the water crises many of you have heard about in Flint, Michigan, or Benton Harbor. These crises are unevenly distributed, unfairly affecting communities of color and low-income communities, tribal communities. However, not only do those actual pipeline problems of contamination happen but the professional pipelines for a better water sector that is more inclusive, more equitably managed and more sophisticated in its use of data analytics, those challenges are a learning pipeline problem. And so students who get involved with us can feel that they're contributing to both. They're making water better and they're making learning better so that the future of this sector can be commensurate with the importance of the challenge of providing clean water for all as a primary public health proposition and indeed one of the human rights that we must protect as we move into the future. The Midwest Big Data Hub has helped us do that on a wider scale with a regional footprint and that's what we're going to scale up and explore further in this PIT project. So becoming a model for community-engaged public interest technology work is not as easy as it might sound. So many of the models we've inherited are broken. They're arrogant. They are disseminationist. They assume a science deficit in ways that involve the laboratory or the university as the seat of valid knowledge that must be disseminated to communities. Working against that is only now becoming something to which we have multiple kinds of answers. In our case, the student attraction that I discussed in that previous video is coupled with a series of conversations with partners like my co-principal investigator, Kyle Powis-White, who himself has pioneered approaches to things like the NSF program, Tribal College and University Partnerships, research experience for undergraduates in ways that begin to build out learning communities, even on campuses that have historically been underrepresented in tech fields and underfunded and underprovided with materials for tech solutions. Doing this is no main feat, even in preparing the proposal. I learned the hard way that to do this well, you need to take more time in building projects. You need to consult thoroughly, listen carefully, be willing to build more slowly, be willing to rebuild if what you've started to construct doesn't bring true to the communities you seek to interpolate or whom you've identified as vulnerable or targets of the problems you're trying to address. It needs to be we who try to address them through listening, through co-creation, through formative, iterative assessment of the learning tools we create and a willingness to recreate them over time as users give us feedback and guidance about how they work and for whom in a sector as volatile as the water sector in Michigan right now. That kind of community engagement is something that is sometimes frustrating, sometimes complex, but almost always an investment in the long-term benefits to the many, many different communities who need to move forward together in dialogue with one another in order for something like water quality to improve across a matrix like a city, a state, a region or indeed even our country and the world. I have worked on water quality with colleagues from Jinghua University in Beijing, China. I know for a fact that these concerns about community-based water quality rights are not only those of our own country, but that the solutions that have to emerge need to be deeply grounded in close listening and careful work with different kinds of minds who have different historical relationships to the problem. That's what we're going to try to model here in our fellows program. We'll train fellows in those skills, in addition to coding our Python and so on. We hope very much that it can be a beacon and we will be recording those things as learning modules as we go. In terms of the skills that students will attain through engagement with our PITU and project, well, learning to work in genuine dialogue with vulnerable communities is non-negligible as a skill. Project management in general is an important skill for students to begin to master early. But when working on something as volatile as the water crisis in very vulnerable communities, an even different dimension of project management comes into play, thinking about the temporality of the project to ensure that different kinds of participants feel they've had time to digest, consider and be in dialogue with one about the project is sort of vulnerable community project engagement 101. It's not easy. And it also implies attention to translational elements in what registers in what forms should a knowledge sharing effort occur and how can feedback about that knowledge effort best be invited and really seriously considered as the project moves forward. That means project framing as well as project management needs to be highly dynamic and sensitive to the ways in which problems are being defined and by whom with what the deliverables created by whom and for whom. This is huge. It's fundamental. Of course, there's also the question of students working across different disciplinary communities. And that also is a kind of communication challenge. Each student's different mandate might mix differently. The humanities, for example, the history and culture of a site and the communities affected in a site, even within a water distribution network or within a utility itself that utilities history, but they might also draw from social sciences. They might draw from biosciences. They might draw from critical infrastructure studies. All of these different triangulations matter immensely to the ways in which we frame the problems, the inscrutable puzzles about why water quality seems so much better in some neighborhoods than others, even within a single system. And what might be the explanations for that microbiologically, demographically, infrastructurally. I think we have in some ways the most perfect game. It's like a candy land board. It's like a system that one can explore and learn with across different fields of knowledge. And finally, much has been made of agile development in the software world in recent years. Clearly, the curricular and learning design world is also making that move and students will learn, both as coders and designers of learning tools, about how to engage in backwards design and iterative evaluation. How to think about iterative development in terms of feedback cycles and to get comfortable with those feedback cycles as a product eventually emerges and gets feedback from different kinds of users developing as it goes. As far as advancing the field of public interest technology itself, our PIT, UN Project Data Learning for Better Drinking Water in small utilities really does begin at that point where, sort of like craft brewing, we are thinking about craft tech. What kinds of particular innovations in learning tools, the features they use, the interactive features they come up with, the ways they link to an existing management system for civic utility. That process we like to call craft tech because it's locally grounded in problem-driven needs in our community. But I think we can also help the PIT field think further about how to integrate that fundamental place-based impulse with slightly wider kinds of users and applications. We're working, for example, with Blue Ponduit, which began as a student learning opportunity in our university campus, but is now a startup which links data analytics excellence with really existing water systems to help improve their performance. Further, we have the Midwest Big Data Hub, a federally funded repository for big data excellence that partners with many different sectors across the entire upper Midwest. How do we plan to integrate the very local relationships that are at the start of this? The modules that have to do with day-in, day-out flushing of the Ann Arbor water system and learning how to dig deeper in terms of data analytics about those practices through the work of doctoral student Matthew Bedran in combination with our platform manager Ed Weissmann and the faculty advisors for both the Water Improvement Project Blue Sky, and the Learning Improvement Project Gala, how do we scale that at a more regional level or even beyond at a national level? I think those kinds of questions of the interrelation of scales, localities and relationships that go into innovation might be extremely useful for PIT to think about in the context of our project. And we very much hope to blaze trails for the solution to those challenges that not only remains accountable to and useful for a local system, but potentially also modularly applicable and inspiring for other systems beyond our own. One thing is for sure, data analytics skills are not going to go away. In the space that we're working in our project, Data Learning for Better Drinking Water in Small Utilities, it's clear that drinking water utilities are going to need to do more with data and continually adapt to changing conditions within their systems and within their staff and their client base. But as Jonathan Knee points out in his really excellent book, The Platform Delusion, recently published, we need to be careful not to fetishize or be a triumphalist about things like big data and AI. There's danger in that. Certainly they will be relevant, but so will be the questions of how communities are involved and own or decide how data are used. So this kind of engagement is really important to model and as Knee points out, far too few platforms currently being built or expanded are really taking as a task the mending of rifts that large platforms with their race to scale have created within our societies. That's a space that we believe that PIT support helps us move into. How do we be a different kind of platform? We believe that learning materials are going to need to continually adapt and that creating useful learning materials about environment and sustainability challenges is going to keep meaning new and better ways of connecting professionals, researchers, learners and community leaders. That facilitative and collaborative goal is not only based in low barrier to use, delightful to use software but it's based in social process and project management. So students in PIT careers are going to need not only core technology skills but also network building skills and a critical sense of when not to network but to work together with existing partners to ensure that trust and accountability isn't lost in the race to scale. That means I think that our small experiment with PIT is extremely valuable support can be a step not just in public interest technology but perhaps for technology itself further and further away from that sexy original moment of move fast and break things and instead toward a new moment of move slowly forward together and make things. Thanks for your attention and I look very much forward to learning from the rest of the network.