[csaa-forum] Media at Sydney Seminar, Mediain the Age of the Datalogical: 8 August

Jonathon Hutchinson jonathon.hutchinson at sydney.edu.au
Tue Aug 1 14:19:18 ACST 2017

Dear colleagues with apologies for cross-posting.

The Media at Sydney, in collaboration with Leeds University, are pleased to host its next seminar, In Data We Trust: Media in the Age of the Datalogical.

Tuesday 8 August 1pm - 4pm (Free lunch at 1pm)
Venue: Woolley Common Room, Level 4 John Woolley Room (A20)
To register, please go to https://www.eventbrite.com.au/e/in-data-we-trust-media-in-the-age-of-the-datalogical-tickets-36597322577

The seminar is hosted by Dr Jonathon Hutchinson (University of Sydney) and Dr Heather Ford (University of Leeds). Our 6 expert panelists include:

  1.  Dr Penny O’Donnell, University of Sydney
  2.  Dr David Nolan, Melbourne University
  3.  Professor Nick Enfield, University of Sydney
  4.  Dr Fiona Martin, University of Sydney
  5.  Professor Heather Horst, University of Sydney
  6.  Dr Jason Ensor, Western Sydney University

Several key global events, especially within the political arena, have centered public interest on the role that data plays within contemporary society. Commercial media outlets obsess over data analytics in the face of falling revenues; global digital intermediaries are delivering content using algorithms that are obscure to human oversight; and social media platforms are becoming media powerhouses outside of regulation. Some public commentators recognise this as a process of ‘un-democratization’ as data and algorithms are impacting on society’s ability to make informed decisions. While this may be a reactive stance towards our latest technological turn, it is undoubtable that we are, to at least some extent, delegating our decision-making power to automatic systems and that this will have an impact on social and political life.

Such questions present unique opportunities for humanities and social science researchers. In a post ‘algorithmic turn’ era, humanities scholars have built and mobilized a suite of tools and methods for understanding social life online. Now, new challenges arise in the face of algorithmic cultures. Algorithmic cultures are those in which everyday life is increasingly mediated by rules and procedures of software that is either private, accessible only to the companies that deploy them, or based on principles of machine learning, where computers are delegated with the decision-making based on input data that is increasingly independent of human oversight. In the midst of this challenge  scholars need to continue to build new approaches that draw on disciplinary expertise from multiple quarters.

One emerging approach within computational computer science that is attracting attention, for example, is the combination of ethnography with digital media methods, but interpretive methodological work is being pursued by researchers in a variety of fields: from media studies to cultural studies, history to cognitive and behavioral science. In Data We Trust is a seminar designed to explore the contemporary issues surrounding the implications of datafication, and how best to research it. What are the sites in which data logics and techniques crystallize? Should the starting point be to study the algorithm and then follow the socio-technical relations that result from it? Or should we start from the people and practices that ultimately determine data’s usefulness? Discussing a variety of approaches that are currently being used to study cultures and societies that are heavily mediated by data systems, this workshop aims to encourage discussions about methods for consolidating approaches.
DR JONATHON HUTCHINSON | Lecturer in Online and Social Media
Department of Media and Communications | Faculty of Arts and Social Sciences
Room N233, John Woolley Building A20 | The University of Sydney | NSW | 2006
T +61 2 9351 2821  | F +61 2 9351 2434
E jonathon.hutchinson at sydney.edu.au<mailto:grant.bollmer at sydney.edu.au>  | W jonathonhutchinson.com<http://sydney.edu.au/arts/digital_cultures/>

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