Race and gender have long sociopolitical histories of classification in technical infrastructures-from the passport to social media. Facial analysis technologies are particularly pertinent to understanding how identity is operationalized in new technical systems. What facial analysis technologies can do is determined by the data available to train and evaluate them with. In this study, we specifically focus on this data by examining how race and gender are defined and annotated in image databases used for facial analysis. We found that the majority of image databases rarely contain underlying source material for how those identities are defined. Further, when they are annotated with race and gender information, database authors rarely describe the process of annotation. Instead, classifications of race and gender are portrayed as insignificant, indisputable, and apolitical. We discuss the limitations of these approaches given the sociohistorical nature of race and gender. We posit that the lack of critical engagement with this nature renders databases opaque and less trustworthy. We conclude by encouraging database authors to address both the histories of classification inherently embedded into race and gender, as well as their positionality in embedding such classifications.
In this paper, we propose a new concept for understanding the role of algorithms in daily life: algorithmic authority. Algorithmic authority is the legitimate power of algorithms to direct human action and to impact which information is considered true. We use this concept to examine the culture of users of Bitcoin, a crypto-currency and payment platform. Through Bitcoin, we explore what it means to trust in algorithms. Our study utilizes interview and survey data. We found that Bitcoin users prefer algorithmic authority to the authority of conventional institutions, which they see as untrustworthy. However, we argue that Bitcoin users do not have blind faith in algorithms; rather, they acknowledge the need for mediating algorithmic authority with human judgment. We examine the tension between members of the Bitcoin community who would prefer to integrate Bitcoin with existing institutions and those who would prefer to resist integration.
Abstract-We present our experiences with an SMS-based system for providing transit information based solely on existing cellular and GPS networks. The aim is to permit the development of information services that do not rely on a central authority or complex web hosting. We developed and applied our system to the network of privately-run marshrutka buses in Bishkek, Kyrgyzstan. However, our goal is to more broadly address issues of ad-hoc shared transportation systems in the developing world. A custom designed GPS-GSM unit is placed on a vehicle, and users can query our server over SMS with their own non-GPSenabled cell phones. We report on the accuracy of our location naming approach and estimates of bus arrival times. In addition, we summarize interviews with bus drivers and bus riders relating their views of the system and outline directions for future work. Our system is a grassroots solution to the persistent lack of transport information in developing countries.
This panel will explore algorithmic authority as it manifests and plays out across multiple domains. Algorithmic authority refers to the power of algorithms to manage human action and influence what information is accessible to users. Algorithms increasingly have the ability to affect everyday life, work practices, and economic systems through automated decision-making and interpretation of "big data". Cases of algorithmic authority include algorithmically curating news and social media feeds, evaluating job performance, matching dates, and hiring and firing employees. This panel will bring together researchers of quantified self, healthcare, digital labor, social media, and the sharing economy to deepen the emerging discourses on the ethics, politics, and economics of algorithmic authority in multiple domains.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.