LACOL • Hamilton College
2021 Play & Innovation
Bryan Alexander is an award–winning, internationally known futurist, researcher, writer, speaker, consultant, and teacher, working in the field of higher education’s future.
He completed his English language and literature PhD at the University of Michigan in 1997, with a dissertation on doppelgangers in Romantic-era fiction and poetry.
Then Bryan taught literature, writing, multimedia, and information technology studies at Centenary College of Louisiana. There he also pioneered multi-campus interdisciplinary classes, while organizing an information literacy initiative.
Reimagining the Future(s) of Learning: Play in Speculative Spaces (https://youtu.be/p7HsnoEiCa8)
Tuesday, June 22, 1:30 p.m.
Dr. Heather Pleasants is a faculty development and senior assessment specialist at the University of Texas at Austin, where she works with faculty interested in making experiential learning a part of their courses. She is also an educational researcher and consultant who specializes in providing needs assessment, program evaluation, and external evaluation of funded initiatives—particularly those that address issues of diversity, equity, and inclusion. Dr. Pleasants received her PhD in Educational Psychology (2000) with a specialization in Language, Literacy, and Learning from Michigan State University. She is a regular contributor to the work of the Digital Pedagogy Lab, and her most recent publication is Digital Storytelling in Higher Education: International Perspectives (2017).
Data Feminism (https://youtu.be/zSZgh_y41CI)
Wednesday, June 23, 1:30 p.m.
As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their unequal effects on both individuals and groups have become increasingly difficult for data scientists--and others who rely on data in their work--to ignore. But it is precisely this power that makes it worth asking: "Data science by whom? Data science for whom? Data science with whose interests in mind? These are some of the questions that emerge from what we call data feminism, a way of thinking about data science and its communication that is informed by the past several decades of intersectional feminist activism and critical thought. Illustrating data feminism in action, this talk will show how challenges to the male/female binary can help to challenge other hierarchical (and empirically wrong) classification systems; it will explain how an understanding of emotion can expand our ideas about effective data visualization; how the concept of invisible labor can expose the significant human efforts required by our automated systems; and why the data never, ever “speak for themselves.” How can we operationalize intersectional feminist thinking in order to imagine more ethical and equitable data practices? This talk will focus in particular on examples of play, innovation and emancipatory pedagogy in data science.
Catherine D’Ignazio is a scholar, artist/designer and hacker mama who focuses on feminist technology, data literacy and civic engagement. She has run reproductive justice hackathons, designed global news recommendation systems, created talking and tweeting water quality sculptures, and led walking data visualizations to envision the future of sea level rise. With Rahul Bhargava, she built the platform Databasic.io, a suite of tools and activities to introduce newcomers to data science. Her 2020 book from MIT Press, Data Feminism, co-authored with Lauren Klein, charts a course for more ethical and empowering data science practices. Her research at the intersection of technology, design & social justice has been published in the Journal of Peer Production, the Journal of Community Informatics, and the proceedings of Human Factors in Computing Systems (ACM SIGCHI). Her art and design projects have won awards from the Tanne Foundation, Turbulence.org and the Knight Foundation and exhibited at the Venice Biennial and the ICA Boston. D’Ignazio is an Assistant Professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT. She is also Director of the Data + Feminism Lab which uses data and computational methods to work towards gender and racial equity, particularly in relation to space and place.