CANCELLED: Max Clermont: Data for Black Lives
Due to circumstances beyond our control, THIS EVENT HAS BEEN CANCELLED.
Aynne Kokas: From Grindr to Cybersovereignty
The Chinese government has become increasingly involved in global standards-making events such as the annual Internet Governance Forum and China’s Wuzhen Internet Summit (aka the World Internet Conference) that leverage China’s national standing in international standards-building events to shape global the future of global Internet governance. At the same time, Chinese regulators are also exporting standards not through national, or international governance frameworks, but through the community standards of individual platforms. This talk examines how the Chinese government is expanding its regulatory control over global consumer platforms through the expansion of Chinese-owned consumer platforms.
ESC POD: Faculty Mixer
A mixer for Michigan faculty interested in ESC to be held at "Hathaway’s Hideaway," a 1901 ward meeting hall redecorated with bar and restaurant furnishings from establishments that are significant in the history of Ann Arbor.
Megan Finn: We Are All Well
When an earthquake happens in California today, residents may turn to Twitter for government bulletins and the latest news, check Facebook for updates from friends and family, look to the United States Geological Survey (USGS) for online maps that show the quake's epicenter, and hope to count on help from the Federal Emergency Management Agency (FEMA). This information order articulates a particular epistemic experience of earthquake...
Rayid Ghani: Machine Learning for Social Good
Rayid Ghani was Chief Scientist of 2012 Obama Campaign. He is presently Distinguished Career Professor in Machine Learning at Carnegie Mellon University.
Tina Eliassi-Rad: Just Machine Learning
In this talk, I will discuss current tasks, experiences, and performance measures as they pertain to fairness in machine learning. The most popular task thus far has been risk assessment. Most human decision-makers seem to use risk estimates for efficiency purposes and not to make fairer decisions. The task of risk assessment seems to enable efficiency instead of fairness. I will present an alternative task definition whose goal is to provide more context to the human decision-maker. I will discuss our null model for fairness and demonstrate how to use deviations from this null model to measure favoritism and prejudice in data.
Chris Calabrese: Show Your Face?
Facial recognition technology is sweeping into our public and private lives. The government is deploying it at the border and throughout law enforcement investigations. Technology companies are building it into their social networks. Employers are using it to monitor movements and productivity. As the technology becomes increasingly powerful, accurate, and versatile, it’s raising more and more privacy and civil liberties concerns, especially for marginalized or vulnerable populations. Christopher Calabrese, Vice President for Policy at the Center for Democracy & Technology will discuss the pros and cons of facial recognition technology, how it is changing many aspects of our lives, and how policymakers should address it.
“Anonymous Autonomous” Work in Progress Community Demo
A free public exhibition at the Duderstadt Gallery2281 Bonisteel Boulevard, Ann Arbor, MI 48109 ARTIST Katherine Behar, Michigan ESC Artist-in-Residence; Associate Professor of Art at Baruch College DESCRIPTION Anonymous Autonomous is a robotic art installation being developed by Katherine Behar, Artist in Residence at the University of Michigan, together with a team of U-M students. […]
Julia Stoyanovich: Follow the Data!
Data science technology promises to improve people's lives, accelerate scientific discovery and innovation, and bring about positive societal change. Yet, if not used responsibly, this same technology can reinforce inequity, limit accountability, and infringe on the privacy of individuals. In my talk I will discuss recent technical work in scope of the "Data, Responsibly" project. The goal of this project is to establish a foundational new role for database technology, in which managing data in accordance with ethical and moral norms, and legal and policy considerations becomes a core system requirement.
Julia Stoyanovich: TransFAT
Data science technology promises to improve people's lives, accelerate scientific discovery and innovation, and bring about positive societal change. Yet, if not used responsibly, this same technology can reinforce inequity, limit accountability, and infringe on the privacy of individuals. In my talk I will give an overview of the "Data, Responsibly" project that aims to operationalize ethics and legal compliance in data science systems. In particular, I will speak about my involvement in efforts to regulate the use of data science and AI in New York City, and about the imperative to establish a broad and inclusive educational agenda around responsible data science.