Mar 23, 2017
from 11:30 AM to 03:30 PM
|Where||S1 Alison Richard Building, West Road Cambridge|
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How can public interest journalism hold algorithms to account?
The challenges of transparency in the digital age
Please register online in advance as spaces are limited: book here
11.30 am – 3.30pm
The increasing use of algorithms throughout the public and private sectors to inform decisions about access to services, allocation of resources, consumer credit and even criminal sentencing poses many challenges. While the adoption of Big-Data driven systems has been praised by some as a potential means to reduce inefficiencies, journalists and researchers have uncovered evidence that reliance on algorithms can amplify, rather than reduce structural bias on grounds of race, gender and social class.
This workshop will investigate what role journalism can play in uncovering and unpacking algorithms and explore the skills, resources and methods required to hold algorithms and their owners to account.
Session 1 - 11.30 – 1pm
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.
1.30 – 2.30pm
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.
2.30 – 3.30pm
Roundtable discussion with Jonathan Gray, Liliana Bounegru and Nick Diakopoulos