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Social and Behavioral Sciences Commons™
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Articles 1 - 10 of 10
Full-Text Articles in Social and Behavioral Sciences
Understanding Intelligent Systems, Tamara Kneese
Understanding Intelligent Systems, Tamara Kneese
Media Studies
Science fiction has long imagined a workforce reshaped by robots, but the increasingly common instantiation of intelligent systems in business is much more mundane. Beyond the utopian and dystopian hype of increased efficiencies and job displacement, how do we understand what disruptions intelligent systems will have on the workforce?
Understanding Fair Labor Practices In A Networked Age, Tamara Kneese
Understanding Fair Labor Practices In A Networked Age, Tamara Kneese
Media Studies
Unionization emerged as a way of protecting labor rights when society shifted from an agricultural ecosystem to one shaped by manufacturing and industrial labor. New networked work complicates the organizing mechanisms that are inherent to unionization. How then do we protect laborers from abuse, poor work conditions, and discrimination?
Technologically Mediated Artisanal Production, Tamara Kneese
Technologically Mediated Artisanal Production, Tamara Kneese
Media Studies
From 3D printing to maker culture, there’s a rise of technical practices that resist large industrial and corporate modes of production, similar to what is occurring in artisanal food and agriculture. While DIY practices are not new, the widespread availability and cheap cost of such tools has the potential to disrupt certain aspects of manufacturing. How do we better understand what is unfolding?
Workplace Surveillance, Tamara Kneese
Workplace Surveillance, Tamara Kneese
Media Studies
Employers have long devised techniques and used new technologies to surveil employees in order to increase efficiency, decrease theft, and otherwise assert power and control over subordinates. New and cheaper networked technologies make surveillance easier to implement, but what are the ramifications of widespread workplace surveillance?
Networked Employment Discrimination, Tamara Kneese
Networked Employment Discrimination, Tamara Kneese
Media Studies
Employers often struggle to assess qualified applicants, particularly in contexts where they receive hundreds of applications for job openings. In an effort to increase efficiency and improve the process, many have begun employing new tools to sift through these applications, looking for signals that a candidate is “the best fit.” Some companies use tools that offer algorithmic assessments of workforce data to identify the variables that lead to stronger employee performance, or to high employee attrition rates, while others turn to third party ranking services to identify the top applicants in a labor pool. Still others eschew automated systems, but …
Qr Codes For The Dead, Tamara Kneese
Qr Codes For The Dead, Tamara Kneese
Media Studies
Graveyards are becoming smart spaces, but will today's technology last for eternity?
Death Stares, Tamara Kneese
Death Stares, Tamara Kneese
Media Studies
Reports of a general “death taboo” have been greatly exaggerated. But there remains a disconnect between the shiny and seemingly disembodied memorials on social media platforms and the presence of the corpse.
Inequalities And Asymmetries, Tamara Kneese
Inequalities And Asymmetries, Tamara Kneese
Media Studies
The availability of data is not evenly distributed. Some organizations, agencies, and sectors are better equipped to gather, use, and analyze data than others. If data is transformative, what are the consequences of defense and security agencies having greater capacity to leverage data than, say, education or social services? Financial wherewithal, technical capacity, and political determinants all affect where data is employed. As data and analytics emerge, who benefits and who doesn't, both at the individual level and the institutional level? What about the asymmetries between those who provide the data and those who collect it? How does uneven data …
Inferences & Connections, Tamara Kneese
Inferences & Connections, Tamara Kneese
Media Studies
Data-oriented systems are inferring relationships between people based on genetic material, behavioral patterns (e.g., shared geography imputed by phone carriers), and performed associations (e.g., "friends" online or shared photographs). What responsibilities do entities who collect data that imputes connections have to those who are implicated by association? For example, as DNA and other biological materials are collected outside of medicine (e.g., at point of arrest, by informatics services like 23andme, for scientific inquiry), what rights do relatives (living, dead, and not-yet-born) have? In what contexts is it acceptable to act based on inferred associations and in which contexts is it …
Predicting Human Behavior, Tamara Kneese
Predicting Human Behavior, Tamara Kneese
Media Studies
Countless highly accurate predictions can be made from trace data, with varying degrees of personal or societal consequence (e.g., search engines predict hospital admission, gaming companies can predict compulsive gambling problems, government agencies predict criminal activity). Predicting human behavior can be both hugely beneficial and deeply problematic depending on the context. What kinds of predictive privacy harms are emerging? And what are the implications for systems of oversight and due process protections? For example, what are the implications for employment, health care and policing when predictive models are involved? How should varied organizations address what they can predict?