…The Challenges of Transparency in the Digital Age (Workshop)

Session 1

Algorithmic Accountability and Transparency: A View from Computational Journalism

Keynote presentation:
Nick Diakopoulos, University of Maryland

Algorithms are coming to adjudicate decisions in nearly all facets of the public and private sectors. But despite the potential for efficiency gains, algorithms fed by big data can also amplify structural discrimination or produce errors that deny services to individuals — the close monitoring of such systems is paramount. Algorithmic accountability reporting is a new form of computational journalism that is emerging to apply the core journalistic functions of watchdogging and investigative reporting to algorithms. In this talk I will discuss how algorithmic accountability reporting is used by journalists as a method for articulating the power structures, biases, and influences that computational artifacts play in society. I'll trace various legal, technical, and regulatory challenges that remain, offering new openings for the development of tools and approaches. Finally, I will discuss the mandate for transparency of algorithms and proffer for discussion an initial transparency standard that delineates the dimensions of algorithms that might be productively disclosed while acknowledging mediating concerns. 

About the speaker:
Nicholas Diakopoulos is an Assistant Professor at the University of Maryland, College Park Philip Merrill College of Journalism with courtesy appointments in the College of Information Studies and Department of Computer Science. He is Director of the Computational Journalism Lab at UMD, a member of the Human-Computer Interaction Lab (HCIL) at UMD, a Tow Fellow at Columbia University School of Journalism, and Associate Professor II at the University of Bergen Department of Information Science and Media Studies. His research is in computational and data journalism with emphases on algorithmic accountability and social computing in the news. He received his Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech where he co-founded the program in Computational Journalism. Before UMD he worked as a researcher at Columbia University, Rutgers University, and CUNY studying the intersections of computing, information science, and journalism.

Lunch

Session 2

Breakout sessions:

Participants will collaboratively investigate the use of algorithms at various levels of UK government by running targeted search queries on governmental sites. Potential leads will be fleshed out with a set of well-defined metadata that help orient and situate the algorithm in terms of how it's used and how it may matter to the public. The appropriateness of applying various methods for undertaking investigation of the found algorithms will be discussed. 

Session 3

Fake News, Algorithmic Accountability and the Data Journalism in the Post-Truth Era

Speakers: Liliana Bounegru and Jonathan Gray

In the wake of concerns about the role of “fake news” in relation to the US elections, Liliana Bounegru and Jonathan Gray present a new project which aims to catalyse collaborations between leading digital media researchers, data journalists and civil society groups in order to map and respond to the issue and phenomenon of fake news in US and European politics. “A Field Guide to Fake News” will look at how digital methods, data, tools, techniques and research approaches can be utilised in the service of increasing public understanding of the politics, production, circulation and responses to fake news online. In particular it will look at how digital traces from the web and online platforms can be re-purposed in the service of public interest research, investigations, data stories and data journalism projects. Starting with deceptively straightforward questions, the guide follows fake news and misinformation phenomenon online across the web and online platforms – aiming to enrich the character of reporting and public debate around the infrastructures and algorithms that mediate collective life in the post-truth era.

Liliana Bounegru is a researcher specialising in data journalism and digital methods. She is affiliated with several universities in Europe and the US, including the universities of Amsterdam, Groningen and Ghent, Sciences Po, and Columbia University. She is also a data journalism advisor for the European Journalism Centre where she previously founded and led the Data Driven Journalism initiative and co-edited the Data Journalism Handbook. She tweets at @bb_liliana, and more about her can be found at lilianabounegru.org.
 

Jonathan Gray is Prize Fellow at the Institute for Policy Research, University of Bath. His current research focuses on the politics of open data and public information. He is also Research Associate at the Digital Methods Initiative, University of Amsterdam; Research Associate at the médialab at Sciences Po; Tow Fellow at the Tow Center for Digital Journalism, Columbia University. In addition to his academic work, Jonathan has a professional background in the civil society sector, public policy and data journalism. He is Senior Advisor at the global civil society organisation Open Knowledge International where he has founded and co-founded numerous initiatives, including the Data Journalism Handbook, Europe’s Energy, Open Data for Tax Justice, OpenSpending, Open Trials, The Public Domain Review and Where Does My Money Go?. You can follow him on Twitter at @jwyg and find out more about him at jonathangray.org