Dr. Corey Jackson joined the iSchool as a Postdoctoral Scholar this fall and will stay on as a faculty member in Fall 2021. Dr. Jackson earned an M.S. in Library and Information Science at the Univeristy of Illinois Urbana-Champaign and a Ph.D. in Information Science and Technology at Syracuse University.
Could you please describe your area of focus?
My work is described as computer supported cooperative work (CSCW) and human-computer interaction (HCI). I study the tools and techniques that enable groups and individuals to collaborate via the Internet. Research in CSCW and HCI attempts to understand the social and technical dimensions surrounding working over the web. Our work’s ultimate goal is to design and build robust tools using human-centered design principles that enhance collaboration.
What main issue do you seek to solve in your work?
I study virtual citizen science projects. Citizen science involves collaboration between amateurs and professional scientists. Snapshot Wisconsin (http://snapshotwisconsin.org/) is one example of citizen science. Snapshot is a wildlife monitoring program that uses camera traps to capture photos of wildlife in the state. Photos are analyzed by a community of volunteers who note information about the photo, e.g., species type. Ecologists use the data to research wildlife occurrence. Citizen science projects face challenges, including ensuring high-quality data and understanding how best to educate amateurs. My research addresses these problems by investigating human interaction online and informing the design of software to enhance participants’ work.
What’s one thing you hope students who take a class with you will learn?
Beginning in Fall 2021, I teach “Data Science for Everyone.” This course seeks to attract students who don’t consider themselves programmers or statisticians. I want students to understand that data science is more than a technical discipline. Being knowledgeable of machine learning techniques is critical to data science, but so are considerations of the ethics and contexts in which the data are situated. The peril of ignoring the non-technical aspects of data science is that we make data science tools and decisions that aren’t for everyone. Some context reading: Algorithms of Oppression by Dr. Safiya Umoja Noble and Race After Technology by Dr. Ruha Benjamin.
What attracted you to UW-Madison?
I have an affinity for Big Ten schools (Go Illini!). I chose Wisconsin because I was impressed with the culture of the iSchool and its growth trajectory. The iSchool becoming a part of the new School of Computing, Data & Information Sciences (CDIS) was the icing on the cake. As we shift to include computational thinking as a core area of focus, I saw a unique opportunity to shape the iSchool’s curriculum and research. As we grapple with the problems that technology has brought about, we need a new generation of data and information professionals who are critically engaged in future tech development. I plan to make that a reality at the iSchool.
How does your work relate to the Wisconsin Idea?
The Wisconsin Idea is tightly woven into my ethos. As an undergrad student, I participated in faculty-led research projects. Research experiences allow me to apply what I learned in the classroom to real-world problems. Interactions with faculty were crucial to my intellectual development. I encourage students to get involved in research through the Undergrad Research Scholar (URS) program, the Center for Academic Excellence (CAE), or the McNair Scholars Program.