Affiliation:
1. Computer Science, New York University Abu Dhabi , Abu Dhabi 129188 , United Arab Emirates
2. School of Informatics, The University of Edinburgh , Edinburgh EH8 9YL , UK
Abstract
Abstract
Recent breakthroughs in machine learning and big data analysis are allowing our online activities to be scrutinized at an unprecedented scale, and our private information to be inferred without our consent or knowledge. Here, we focus on algorithms designed to infer the opinions of Twitter users toward a growing number of topics, and consider the possibility of modifying the profiles of these users in the hope of hiding their opinions from such algorithms. We ran a survey to understand the extent of this privacy threat, and found evidence suggesting that a significant proportion of Twitter users wish to avoid revealing at least some of their opinions about social, political, and religious issues. Moreover, our participants were unable to reliably identify the Twitter activities that reveal one’s opinion to such algorithms. Given these findings, we consider the possibility of fighting AI with AI, i.e., instead of relying on human intuition, people may have a better chance at hiding their opinion if they modify their Twitter profiles following advice from an automated assistant. We propose a heuristic that identifies which Twitter accounts the users should follow or mention in their tweets, and show that such a heuristic can effectively hide the user’s opinions. Altogether, our study highlights the risk associated with developing machine learning algorithms that analyze people’s profiles, and demonstrates the potential to develop countermeasures that preserve the basic right of choosing which of our opinions to share with the world.
Funder
New York University Abu Dhabi
Narodowe Centrum Nauki
Publisher
Oxford University Press (OUP)
Reference57 articles.
1. You are who you know: inferring user profiles in online social networks;Mislove;Proceedings of the 3rd ACM International Conference on Web Search and Data Mining,2010
2. Computer-based personality judgments are more accurate than those made by humans;Youyou;Proc Natl Acad Sci,2015
3. Private traits and attributes are predictable from digital records of human behavior;Kosinski;Proc Natl Acad Sci,2013
4. How Trump consultants exploited the Facebook data of millions;Rosenberg;The New York Times,2018
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