Minds and Machines
Pushing the frontiers of science and responsible innovation for public good in the age of intelligent tools
Intelligent tools are changing the world, our lives, and our work in expected and unexpected ways. They have led to advancements in our health, livelihood, and overall quality of life. At the same time, their misuse can have harmful individual and societal outcomes such as loss of privacy, algorithmic bias, group marginalization, and the propagation of misinformation. Today’s interconnected world requires intelligence in science and a new generation of decision-makers to simultaneously support growing needs and safeguard society from unintended consequences.
Minds and Machines is an interdisciplinary effort that will jointly push the frontiers of science and responsible innovation through intelligence to achieve the transformational advancements necessary for economic change and public good in a world with intelligent machines. It will build on Rutgers’s existing strengths in science, engineering, public policy, business, medicine, and the humanities to position us as a hub in emerging areas of digital technology done in partnership with industry and government agencies, and through engagement with the general public. A central part of our work will be educating the next generation of scientists, business, and civic leaders who will play a crucial role in mitigating threats and exploiting the social opportunities of a new era.
The convergence of data and computing has led to recent breakthroughs in AI and is beginning to radically change how we work, learn, share information, and navigate our environments. Research institutions that recognize the cross-disciplinary applications of data science and AI, and train their students to identify the unintended consequences resulting from these advancements, will be at the vanguard of changes that cut across established fields and create new opportunities for innovation and prosperity.
Minds and Machines is a visionary interdisciplinary effort to push the frontiers of science and achieve the transformational advancements necessary for economic innovation and public good in a world where machines are partners and not simply tools. By building on Rutgers’ strengths, this effort will make the university a hub for responsible innovation and a destination for public private partners looking for unique interdisciplinary solutions to complex problems.
The science: data science and AI
Data science is a low-risk, high-reward discipline.
- It is a solutions-driven tool that can help us solve research and business problems.
- We have already begun to develop widely accessible academic programs that introduce students from nontechnical disciplines to the fundamentals of data science.
- We have efforts under way that integrate into curricula results of successful cross-disciplinary collaborations between faculty in units across all four chancellor-led units.
Artificial intelligence is a moderate-risk, high-reward discipline.
- It will become increasingly possible to make smart predictions that improve our lives.
- It will create new opportunities to perform tasks that humans never thought possible.
- It will also create enormous cost savings, helping increase productivity.
- However, with the opportunities come potential threats from bias, unintended consequences, and invasion of privacy.
The program: education, collaboration, and infrastructure
Through Minds and Machines, Rutgers will create a vibrant synergistic community (physical and virtual) fostering collaborative research and integrative teaching across the New Brunswick, Newark, and Camden campuses and Rutgers Biomedical and Health Sciences. At the heart of the effort will be an institute that will amplify research projects currently underway and provide a structure to facilitate more cross-campus collaboration and expand external partnerships. It will rely on the university’s decades-long history of supporting successful multidisciplinary partnerships and allow for local expressions of this important work to take place within and across the chancellor-led units.
The new institute will give Rutgers national visibility by assembling thematic research teams from across organizational, spatial, and disciplinary boundaries to work together to develop and apply new knowledge to critical issues facing society. Thematic workshops and conferences will bring in national and international leaders to the university and promote further collaboration and engagement. Finally, the institute will train students to think both critically and technically about data and enrich their experience at Rutgers through new certificate and degree programs, capstone projects, and other special programming.
Big Ideas are driven by faculty, staff, and researchers across disciplines, divisions, and locations. Project champions represent the robust, expansive, and highly collaborative project teams whose work will bring these ideas to life.
Executive Dean, School of Arts and Sciences, Rutgers—New Brunswick
March is also a distinguished professor of mathematics whose research interests center on probability theory and its applications. He joined the faculty at The Ohio State University in 1988, where he served as chair of the mathematics department, associate director of the Mathematical Biosciences Institute, and dean of natural and mathematical sciences. From 2006 to 2010, he was director of the Division of Mathematical Sciences at the National Science Foundation. He joined Rutgers in 2014. From 2014 to 2016, March chaired the U.S. National Committee for Mathematics’ Board on International Scientific Organizations of the National Academies of Science, which is the formal U.S. representative to the International Mathematical Union. He serves on the Committee on Science Policy of the American Mathematical Society and the Society for Industrial and Applied Mathematics. In 2017, he was named a fellow of the American Association for the Advancement of Science, an honor bestowed for scientifically or socially distinguished efforts to advance human knowledge.