Modern Statistics and the Modern Newsroom

Explore the Relationship Between Journalism and Data During Free Public Lecture

Wednesday, November 17, at 3:00 p.m. ET.

Join Columbia Journalism School’s Mark Hansen as he discusses Modern Statistics and the Modern Newsroom Wednesday, November 17, at 3:00 p.m. ET.

In his own words:

“The adventure of being close to the stuff the world is made of …”

To steal a quote (very much out of context) from Anni Albers, this talk is about “the adventure of being close to the stuff the world is made of,” and, today, that “stuff” is abstractions by data processed through algorithms on its way to taking action in the world. Journalists working today are expected to report both on and with computation.

Data and algorithms constitute systems of power, and journalists have taken up the challenge of helping judge their fairness. How are people and situations represented in data? Do algorithmic systems treat everyone equally? Who was involved in the design of these systems? Were voices left out?

Jeffrey Rosenthal

The closer a journalist can come to understanding the nature of how and why data and algorithms are applied—in short, the fundamentals of statistical inference—the better they can inform the public about their effectiveness.

If we look back on 2020–2021, the biggest stories were statistical—from COVID-19 to the 2020 Census to climate change. Sometimes making sense of a situation for the public means detailed data analysis—computational work and a rigorous statistical framing.

I will discuss attempts to connect journalism and statistics—connections that bring much-needed formal technical training to journalism, deepening the profession’s capacity for finding and telling stories in a world awash in data and the artifacts of statistical work. These same connections introduce investigative and reporting skills to statistics, creating new forms of practice for the field and opening new career paths.

For nearly three decades, Mark Hansen has been working at the intersection of data, art, and technology. Currently the director of the Brown Institute at Columbia Journalism School, Hansen was previously a professor at the University of California at Los Angeles holding appointments in the department of statistics, department of design media arts, and department of electrical engineering.

Regarding journalism, Hansen has been a long-standing visiting researcher at The New York Times R&D Lab, a late-career intern at the Marshall Project, and a consultant with HBO Sports. In 2018, Hansen’s computational journalism course at Columbia Journalism School contributed the original reporting for The New York Times piece, “The Follower Factory,” which exposed the bot economy behind the sale of fake followers on Twitter. That article was cited by Twitter as the reason for its July 2018 “purge” of tens of millions of suspicious accounts and partially responsible for California’s bot law. It was also part of a package of stories from the Times that won the 2019 Polk Award for National Reporting and a finalist for a 2019 Pulitzer Prize for National Reporting.

Hansen holds a BS in applied math from the University of California at Davis and an MA and a PhD in statistics from the University of California at Berkeley. He has been awarded eight patents and published more than 60 papers about data science, statistics, and computer science.

Read Hansen’s CV and follow him on Twitter, @cocteau.

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