Fact or Fiction: Learning How to Challenge DEI Data
January 27, 2022 - 9:00am to 11:30am (PST)
Presenters: Jevin West & Carl Bergstrom
Data and statistics have been used by organizations to justify (or not) their Diversity, Equity & Inclusion (DEI) efforts, including such practices as recruiting, hiring and promotions. For years, organizations have crafted a “Business Case for diversity and inclusion” to justify programs and efforts to increase women and people of color. Yet, here we are years later and there is still much work to be done.
This session will examine the tools for questioning data, with examples from the kind of data traditionally used for DEI. Has it made a difference? We won’t be able to answer that question for an individual organization or for industries more broadly, but we will explore some of the basic principles of data inspection and how data can both inform and misinform. This will include lessons on spotting BS in data graphics, identifying when selection bias could be leading to erroneous conclusions, and calling out problems of causation versus correlations. Participants will leave this session with the tools necessary to question data claims within their industry and their own organization.
By the end of this session, participants will be able to:
Spot misinformation related to DEI data.
Refute misinformation related to DEI data.
Recognize data graphic errors and how to fix them.
Identify flawed data arguments as a result of selection bias.
Distinguish between claims of causation versus correlation.
Carl Bergstrom is a professor of biology at the University of Washington and a faculty member at the UW Center for an Informed Public.
Trained in evolutionary biology, mathematical population genetics, and epidemiology, Carl is perhaps best known for crossing field boundaries and integrating ideas across the span of the natural and social sciences. The unifying theme that runs through all of Carl’s work is the concept of information.
Within biology, he studies problems such as how communication evolves, how animals deal with deception, and how the process of evolution by natural selection creates the information that is encoded in genomes. In the philosophy and sociology of science, he studies how the incentives created by scientific institutions shape scholars’ research strategies and, in turn, our scientific understanding of the world.
In physics and network science, he explores how to extract the relevant information from massive networks comprising tens of millions of nodes, and how information flows through networks of this scale. Within informatics, he studies how citations and other traces of scholarly activity can be used to better navigate the overwhelming volume of scholarly literature. Within epidemiology, he studies the interaction between evolutionary and epidemiological processes in the emergence of infectious disease, the role of disease surveillance including rapid testing, and the effects of disinformation on public health.
Carl is the author the college textbook, Evolution (W.W. Norton). Recently, Carl has teamed up with Jevin West on a series of projects focused around teaching quantitative reasoning and information literacy. Together they have developed a high-profile educational website (http://callingbull.org), course materials used at over 100 colleges and universities, and the popular book Calling Bullshit: The Art of Skepticism in a Data-Driven World (Random House).
Jevin West is an Associate Professor in the Information School at the University of Washington. He is the inaugural Director of the Center for an Informed Public at UW aimed at resisting strategic misinformation, promoting an informed society and strengthening democratic discourse.
He is also the co-founder of the DataLab at UW, a Data Science Fellow at the eScience Institute, and Affiliate Faculty for the Center for Statistics & Social Sciences
His research and teaching focus on the impact of technology on science and society, with a focus on slowing the spread of misinformation. He is also the co-author of the new book, Calling Bullshit: The Art of Skepticism in a Data-Driven World, which helps non-experts question numbers, data, and statistics without an advanced degree in data science.
Meet the Presenters: