The facts on 'fake news'

Location
Alan Walters Building (R29)
Category
Lectures Talks and Workshops, Research, Social Sciences
Dates
Monday 6th November 2017 (18:00-20:00)
Download the date to your calendar (.ics file)
Contact

For more information on this event, please contact Dr Siddhartha Bandyopadhyay.

Register for this event

The University of Birmingham are delighted to present this event, part of the Economic and Social Research Council Festival of Social Science 2017.

Our current world is data rich yet the excess of available information makes the task of filtering news quite challenging. We will illustrate the power of scientific methods to rule out common errors. The power of alternate news to drown out reasoned discourse had made us realise the need to develop rules of thumb for public understanding of using data in a way that informs us about policy issues in a meaningful way.

This is important as sound policy requires that the public understand how numbers can be used and abused and without an ability to filter news, voters cannot choose from various options in a meaningful way. The idea of ‘curation; i.e. ability to select information in a meaningful way is now understood in business but this is a skill that the citizenry at large needs to understand if it has to have a meaningful voice in democratic decision making.

We shall present and illustrate some rules of thumb, to help filter from multifarious information channels to derive useful information to decide on how to judge competing claims. This is particularly important in an era where there is too much data available and lobby groups vigorously pass off their biased views as ‘news’.

ESRC Festival 2017The topic promotes an understanding of how data in social sciences can be used by the public to make informed choices.

The talks will use examples to first show how data can be used to misinform, and then show how it can be used to inform us on policy issues.

Siddhartha Bandyopadhyay, Colin Rowat and Kamilya Suleymenova will give an overview of how data can misinform and derive simple rules to make sense of data with examples from current policy debates such as Brexit.