The Michigan Institute for Data and AI in Society (MIDAS) unveils the beginning of its new phase, nicknamed MIDAS 3.0, which will build on its previous success to pursue a new strategic goal: using focused “pillars” to achieve maximum impact, while continuing to support Data Science and AI research across the University broadly.
Data Science and AI methods are being adopted by an increasing number of research domains and researchers. MIDAS has built an inclusive research community and has a very large footprint across the university. It is now time to go to the next level by identifying a number of pillars where MIDAS as a campus-wide unit can help U-M solidify or establish its research leadership position. It will do so by promoting responsible research practices, supporting the adoption of new data types and methodologies, and facilitating convergence science. It is anticipated that the pillars will change over time: current pillars will be retired or shift focus, and new pillars established. Furthermore, these pillars are interconnected where possible, to maximize the synergies between them and leverage the interdisciplinary MIDAS community and the collaborative spirit U-M is known for.
While establishing pillars, MIDAS will continue to foster connections and collaborations in Data Science and AI for the entire University, maintain a large umbrella covering all relevant research areas, and support an inclusive community of researchers. Furthermore, MIDAS will continue to promote cutting edge methodological work in Data Science and AI as the essential foundation.
Responsible Research Pillar: Enhancing Scientific and Societal Impact. MIDAS has invested significant effort to enable reproducible Data Science and to promote data equity and fairness, and rallied the enthusiasm of researchers across campus. For instance, we lead the national institute Framework for Integrative Data Equity Systems (FIDES). We will intensify our efforts in this area from exploring foundational principles to developing methodology and tools for the larger research community. We will work with researchers from across the relevant domains, including those covered under the other three pillars, to integrate these methodologies and tools to enhance the scientific impact of Data Science and AI research. Furthermore, we will apply these methodologies and tools to research projects that primarily aim to inform policy and promote social good, thus translating research rigor into greater societal impact.
Data Pillar: Measuring and Improving Society. Societal transformations have complicated traditional survey methods for data collection, while a plethora of new data sources have become available that may create novel opportunities to measure human behaviors and the human social condition. U-M is known for its prominence in social science research, and MIDAS has been a close collaborator with social scientists and survey researchers. For example, MIDAS has been working with ICPSR on how social science data sets are ingested. MIDAS will collaborate with campus units to develop and use Data Science and AI methods to enable new opportunities to better understand society through new data interfaces such as sensors and digital traces (including social media and other digital transactions).
Analytics Pillar: Transforming Health Interventions. U-M’s biomedical and healthcare research is among the strongest in the nation. With the NIH and other leading agencies providing strong backing, even demand, for the adoption of Data Science and AI methods, there is an urgency for MIDAS to promote the transformation of health interventions through the use of cutting edge methods, such as sequential decision-making and integrative modeling of complex systems to enable insights from multiple types of data. MIDAS has already provided intensive support to many medical and health research teams, who have produced significant external research funding and major research outputs, including a nascent Center for Data-Driven Drug Development and Treatment Assessment. We will also work on health equity, which is closely tied with the Responsible Research pillar.
Emerging Pillar: Cultivating New Strengths. We will support team activities in strategic research areas that have the potential to grow into pillars. The focus will be on areas that are, or are expected to be, national priorities and / or U-M strengths, and can be significantly boosted with Data Science and AI. Our past success in bringing together methodologists and researchers from multiple domains provides a strong foundation for us to support convergence science.