This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (shrink)

In this moment of rising nationalism worldwide, governments, civil society groups, transnational companies, and web users all complain of increasing regional fragmentation online. While prior work in this area has primarily focused on issues of government censorship and regulatory compliance, we use an inductive and qualitative approach to examine targeted blocking by corporate entities of entire regions motivated by concerns about fraud, abuse, and theft. Through participant-observation at relevant events and intensive interviews with experts, we document the quest by professionals (...) tasked with preserving online security to use new machine-learning based techniques to develop a “fairer” system to determine patterns of “good” and “bad” usage. However, we argue that without understanding the systematic social and political conditions that produce differential behaviors online, these systems may continue to embed unequal treatments, and troublingly may further disguise such discrimination behind more complex and less transparent automated assessment. In order to support this claim, we analyze how current forms of regional blocking incentivize users in blocked regions to behave in ways that are commonly flagged as problematic by dominant security and identification systems. To realize truly global, non-Eurocentric cybersecurity techniques would mean incorporating the ecosystems of service utilization developed by marginalized users rather than reasserting norms of an imagined user that casts aberrations as suspect. (shrink)

This article is an analysis of rumors about Internet scamming told by Internet café users in the West African capital city of Accra, Ghana. Rumors provided accounts of how the Internet can be effectively operated by young Ghanaians to realize ‘‘big gains’’ through foreign connections. Yet these accounts were contradicted by the less promising direct experiences users had at the computer interface. Rumors amplified evidence of wildly successful as well as especially harmful encounters with the Internet. Rather than simply transferring (...) information, through the telling of rumors, Internet users reclaimed a social stability that was disrupted by the presence of the Internet. These stories cast young Ghanaian Internet users as both good and effective in relation to the Internet. The study of accounts as they relate to the activities accounted for is an established area of interest in social theory. By considering how rumors function as accounts and how such interpretations of the technology are propagated among users, this analysis contributes to a broader understanding of user agency. (shrink)