Dr. danah boyd is a Partner Researcher at Microsoft Research, the founder/president of Data & Society, a Distinguished Visiting Professor at Georgetown University, and a Visiting Professor at New York University.
What is new about how teenagers communicate through services such as Facebook, Twitter, and Insta... more What is new about how teenagers communicate through services such as Facebook, Twitter, and Instagram? Do social media affect the quality of teens’ lives? In this eye-opening book, youth culture and technology expert danah boyd uncovers some of the major myths regarding teens' use of social media. She explores tropes about identity, privacy, safety, danger, and bullying. Ultimately, boyd argues that society fails young people when paternalism and protectionism hinder teenagers’ ability to become informed, thoughtful, and engaged citizens through their online interactions. Yet despite an environment of rampant fear-mongering, boyd finds that teens often find ways to engage and to develop a sense of identity.
Boyd’s conclusions are essential reading not only for parents, teachers, and others who work with teens but also for anyone interested in the impact of emerging technologies on society, culture, and commerce in years to come. Offering insights gleaned from more than a decade of original fieldwork interviewing teenagers across the United States, boyd concludes reassuringly that the kids are all right. At the same time, she acknowledges that coming to terms with life in a networked era is not easy or obvious. In a technologically mediated world, life is bound to be complicated.
In this paper, we interrogate three technical moments in the history of the US Census to argue th... more In this paper, we interrogate three technical moments in the history of the US Census to argue that the legitimacy of data infrastructure is not a function of data quality, accuracy, or usability. Rather, legitimacy depends on a range of social, political, and historical factors.
ACM Conference on Fairness, Accountability, and Transparency, 2019
A key goal of the fair-ML community is to develop machine-learning based systems that, once intro... more A key goal of the fair-ML community is to develop machine-learning based systems that, once introduced into a social context, can achieve social and legal outcomes such as fairness, justice, and due process. Bedrock concepts in computer science-such as abstraction and modular design-are used to define notions of fairness and discrimination, to produce fairness-aware learning algorithms, and to intervene at different stages of a decision-making pipeline to produce "fair" outcomes. In this paper, however, we contend that these concepts render technical interventions ineffective, inaccurate, and sometimes dangerously misguided when they enter the societal context that surrounds decision-making systems. We outline this mismatch with five "traps" that fair-ML work can fall into even as it attempts to be more context-aware in comparison to traditional data science. We draw on studies of sociotechnical systems in Science and Technology Studies to explain why such traps occur and how to avoid them. Finally, we suggest ways in which technical designers can mitigate the traps through a refocusing of design in terms of process rather than solutions, and by drawing abstraction boundaries to include social actors rather than purely technical ones. CCS CONCEPTS • Applied computing → Law, social and behavioral sciences; • Computing methodologies → Machine learning;
Data voids are a security vulnerability that must be systematically, intentionally, and thoughtfu... more Data voids are a security vulnerability that must be systematically, intentionally, and thoughtfully managed. Data voids are often difficult to detect. Most can be harmless until something happens that causes lots of people to search for the same term, such as a breaking news event, or a reporter using an unfamiliar phrase. In some cases, manipulators work quickly to produce conspiratorial content to fill a void, whereas other data voids, such as those from outdated terms, are filled slowly over time. Data voids are compounded by the fraught pathways of search-adjacent recommendation systems such as auto-play, auto-fill, and trending topics; each of which are vulnerable to manipulation.
“Big Data” and “artificial intelligence” have captured the public imagination and are profoundly ... more “Big Data” and “artificial intelligence” have captured the public imagination and are profoundly shaping social, economic, and political spheres. Through an interrogation of the histories, perceptions, and practices that shape these technologies, we problematize the myths that animate the supposed “magic” of these systems. In the face of an increasingly widespread blind faith in data-driven technologies, we argue for grounding machine learning-based practices and untethering them from hype and fear cycles. One path forward is to develop a rich methodological framework for addressing the strengths and weaknesses of doing data analysis. Through provocatively reimagining machine learning as computational ethnography, we invite practitioners to prioritize methodological reflection and recognize that all knowledge work is situated practice.
Algorithms and data-driven technologies are increasingly being embraced by a variety of different... more Algorithms and data-driven technologies are increasingly being embraced by a variety of different sectors and institutions. This paper examines how algorithms and data-driven technologies, enacted by an organization like Facebook, can induce similarity across an industry. Using theories from organizational sociology and neoinstitutionalism, this paper traces the bureaucratic roots of Big Data and algorithms to examine the institutional dependencies that emerge and are mediated through data-driven and algorithmic logics. This type of analysis sheds light on how organizational contexts are embedded into algorithms, which can then become embedded within other organizational and individual practices. By investigating technical practices as organizational and bureaucratic, discussions about accountability and decision-making can be reframed.
In a media ecosystem besieged with misinformation and polarizing rhetoric, what the news media ch... more In a media ecosystem besieged with misinformation and polarizing rhetoric, what the news media chooses not to cover can be as significant as what they do cover. In this article, we examine the historical production of silence in journalism to better understand the role amplification plays in the editorial and content moderation practices of current news media and social media platforms. Through the lens of strategic silence (i.e., the use of editorial discretion for the public good), we examine two U.S.-based case studies where media coverage produces public harms if not handled strategically: White violence and suicide. We analyze the history of journalistic choices to illustrate how professional and ethical codes for best practices played a key role in producing a more responsible field of journalism. As news media turned to online distribution, much has changed for better and worse. Platform companies now curate news media alongside user generated content; these corporations are largely responsible for content moderation on an enormous scale. The transformation of gatekeepers has led an evolution in disinformation and misinformation, where the creation and distribution of false and hateful content, as well as the mistrust of social institutions, have become significant public issues. Yet it is not just the lack of editorial standards and ethical codes within and across platforms that pose a challenge for stabilizing media ecosystems; the manipulation of search engines and recommendation algorithms also compromises the ability for lay publics to ascertain the veracity of claims to truth. Drawing on the history of strategic silence, we argue for a new editorial approach—“strategic amplification”—which requires both news media organizations and platform companies to develop and employ best practices for ensuring responsibility and accountability when producing news content and the algorithmic systems that help spread it.
In July 2018, the U.S. Census Bureau issued a Federal Register notice asking census data users to... more In July 2018, the U.S. Census Bureau issued a Federal Register notice asking census data users to provide information about what data they used, at what level of geography, and how these use cases might affect different populations. This request for feedback did not announce to those users—local governments, social scientists, and the public at large—that its purpose was to facilitate a massive change in how data about the nation would be produced. A month later, the bureau’s chief scientist, John Abowd, announced on a government blog the need to “modernize” the system used for disclosure avoidance by turning to “formal privacy” methods. Such an approach would allow the government to renew its guarantee of the confidentiality of data. The description of this innovation did not convey the trade-off that would be discussed later, a trade-off that underpinned the Federal Register notice, a trade-off that pitted accuracy against confidentiality, and then pitted both against the desire for conventional statistical tables with numbers that appeared to resemble counts. Unaware of the broader context, the solicitation for feedback confounded data users and community advocates. Which data mattered? All of it, they answered. They needed all of the data, and it had to be accurate. As the reason for this question became clearer, data users grew upset, sides formed, coalitions coalesced, a controversy bloomed.
Published in 2014, the Facebook “emotional contagion” study prompted widespread discussions about... more Published in 2014, the Facebook “emotional contagion” study prompted widespread discussions about the ethics of manipulating social media content. By and large, researchers focused on the lack of corporate institutional review boards and informed consent procedures, missing the crux of what upset people about both the study and Facebook’s underlying practices. This essay examines the reactions that unfolded, arguing the public’s growing discomfort with “big data” fueled the anger. To address these concerns, we need to start imagining a socio-technical approach to ethics that does not differentiate between corporate and research practices.
While much attention is given to young people’s online privacy practices on sites like Facebook, ... more While much attention is given to young people’s online privacy practices on sites like Facebook, current theories of privacy fail to account for the ways in which social media alter practices of information-sharing and visibility. Traditional models of privacy are individualistic, but the realities of privacy reflect the location of individuals in contexts and networks. The affordances of social technologies, which enable people to share information about others, further preclude individual control over privacy. Despite this, social media technologies primarily follow technical models of privacy that presume individual information control. We argue that the dynamics of sites like Facebook have forced teens to alter their conceptions of privacy to account for the networked nature of social media. Drawing on their practices and experiences, we offer a model of networked privacy to explain how privacy is achieved in networked publics.
Discrimination and racial disparities persist at every stage of the U.S. criminal justice system,... more Discrimination and racial disparities persist at every stage of the U.S. criminal justice system,from policing to trials to sentencing. The United States incarcerates a higher percentage of its population than any of its peer countries, with 2.2 million people behind bars. The criminal justice system disproportionately harms communities of color: while they make up 30 percent of the U.S. population, they represent 60 percent of the incarcerated population. There has been some discussion of how “big data” can be used to remedy inequalities in the criminal justice system; civil rights advocates recognize potential benefits but remained fundamentally concerned that data-oriented approaches are being designed and applied in ways that also disproportionately harms those who are already marginalized by criminal justice processes.Like any other powerful tool of governance, data mining can empower or disempower groups. The values that go into an algorithm, and the metrics it optimizes for, are baked into its design. Data could be used to identify discrimination in current practices, or to predict where certain combinations of data points are likely to lead to an erroneous conviction. When algorithms are designed to improve how law enforcement regimes are deployed, the question that data analytics raises is, which efficiencies are we optimizing for? Who are the stakeholders, and where do they stand to gain or lose? How do these applications intersect with core civil rights concerns? Where can we use big data techniques to improve the structural conditions criminal justice system that lead to disparate impacts on marginalized communities? How do we measure that impact, and the factors that lead to it?
What is new about how teenagers communicate through services such as Facebook, Twitter, and Insta... more What is new about how teenagers communicate through services such as Facebook, Twitter, and Instagram? Do social media affect the quality of teens’ lives? In this eye-opening book, youth culture and technology expert danah boyd uncovers some of the major myths regarding teens' use of social media. She explores tropes about identity, privacy, safety, danger, and bullying. Ultimately, boyd argues that society fails young people when paternalism and protectionism hinder teenagers’ ability to become informed, thoughtful, and engaged citizens through their online interactions. Yet despite an environment of rampant fear-mongering, boyd finds that teens often find ways to engage and to develop a sense of identity.
Boyd’s conclusions are essential reading not only for parents, teachers, and others who work with teens but also for anyone interested in the impact of emerging technologies on society, culture, and commerce in years to come. Offering insights gleaned from more than a decade of original fieldwork interviewing teenagers across the United States, boyd concludes reassuringly that the kids are all right. At the same time, she acknowledges that coming to terms with life in a networked era is not easy or obvious. In a technologically mediated world, life is bound to be complicated.
In this paper, we interrogate three technical moments in the history of the US Census to argue th... more In this paper, we interrogate three technical moments in the history of the US Census to argue that the legitimacy of data infrastructure is not a function of data quality, accuracy, or usability. Rather, legitimacy depends on a range of social, political, and historical factors.
ACM Conference on Fairness, Accountability, and Transparency, 2019
A key goal of the fair-ML community is to develop machine-learning based systems that, once intro... more A key goal of the fair-ML community is to develop machine-learning based systems that, once introduced into a social context, can achieve social and legal outcomes such as fairness, justice, and due process. Bedrock concepts in computer science-such as abstraction and modular design-are used to define notions of fairness and discrimination, to produce fairness-aware learning algorithms, and to intervene at different stages of a decision-making pipeline to produce "fair" outcomes. In this paper, however, we contend that these concepts render technical interventions ineffective, inaccurate, and sometimes dangerously misguided when they enter the societal context that surrounds decision-making systems. We outline this mismatch with five "traps" that fair-ML work can fall into even as it attempts to be more context-aware in comparison to traditional data science. We draw on studies of sociotechnical systems in Science and Technology Studies to explain why such traps occur and how to avoid them. Finally, we suggest ways in which technical designers can mitigate the traps through a refocusing of design in terms of process rather than solutions, and by drawing abstraction boundaries to include social actors rather than purely technical ones. CCS CONCEPTS • Applied computing → Law, social and behavioral sciences; • Computing methodologies → Machine learning;
Data voids are a security vulnerability that must be systematically, intentionally, and thoughtfu... more Data voids are a security vulnerability that must be systematically, intentionally, and thoughtfully managed. Data voids are often difficult to detect. Most can be harmless until something happens that causes lots of people to search for the same term, such as a breaking news event, or a reporter using an unfamiliar phrase. In some cases, manipulators work quickly to produce conspiratorial content to fill a void, whereas other data voids, such as those from outdated terms, are filled slowly over time. Data voids are compounded by the fraught pathways of search-adjacent recommendation systems such as auto-play, auto-fill, and trending topics; each of which are vulnerable to manipulation.
“Big Data” and “artificial intelligence” have captured the public imagination and are profoundly ... more “Big Data” and “artificial intelligence” have captured the public imagination and are profoundly shaping social, economic, and political spheres. Through an interrogation of the histories, perceptions, and practices that shape these technologies, we problematize the myths that animate the supposed “magic” of these systems. In the face of an increasingly widespread blind faith in data-driven technologies, we argue for grounding machine learning-based practices and untethering them from hype and fear cycles. One path forward is to develop a rich methodological framework for addressing the strengths and weaknesses of doing data analysis. Through provocatively reimagining machine learning as computational ethnography, we invite practitioners to prioritize methodological reflection and recognize that all knowledge work is situated practice.
Algorithms and data-driven technologies are increasingly being embraced by a variety of different... more Algorithms and data-driven technologies are increasingly being embraced by a variety of different sectors and institutions. This paper examines how algorithms and data-driven technologies, enacted by an organization like Facebook, can induce similarity across an industry. Using theories from organizational sociology and neoinstitutionalism, this paper traces the bureaucratic roots of Big Data and algorithms to examine the institutional dependencies that emerge and are mediated through data-driven and algorithmic logics. This type of analysis sheds light on how organizational contexts are embedded into algorithms, which can then become embedded within other organizational and individual practices. By investigating technical practices as organizational and bureaucratic, discussions about accountability and decision-making can be reframed.
In a media ecosystem besieged with misinformation and polarizing rhetoric, what the news media ch... more In a media ecosystem besieged with misinformation and polarizing rhetoric, what the news media chooses not to cover can be as significant as what they do cover. In this article, we examine the historical production of silence in journalism to better understand the role amplification plays in the editorial and content moderation practices of current news media and social media platforms. Through the lens of strategic silence (i.e., the use of editorial discretion for the public good), we examine two U.S.-based case studies where media coverage produces public harms if not handled strategically: White violence and suicide. We analyze the history of journalistic choices to illustrate how professional and ethical codes for best practices played a key role in producing a more responsible field of journalism. As news media turned to online distribution, much has changed for better and worse. Platform companies now curate news media alongside user generated content; these corporations are largely responsible for content moderation on an enormous scale. The transformation of gatekeepers has led an evolution in disinformation and misinformation, where the creation and distribution of false and hateful content, as well as the mistrust of social institutions, have become significant public issues. Yet it is not just the lack of editorial standards and ethical codes within and across platforms that pose a challenge for stabilizing media ecosystems; the manipulation of search engines and recommendation algorithms also compromises the ability for lay publics to ascertain the veracity of claims to truth. Drawing on the history of strategic silence, we argue for a new editorial approach—“strategic amplification”—which requires both news media organizations and platform companies to develop and employ best practices for ensuring responsibility and accountability when producing news content and the algorithmic systems that help spread it.
In July 2018, the U.S. Census Bureau issued a Federal Register notice asking census data users to... more In July 2018, the U.S. Census Bureau issued a Federal Register notice asking census data users to provide information about what data they used, at what level of geography, and how these use cases might affect different populations. This request for feedback did not announce to those users—local governments, social scientists, and the public at large—that its purpose was to facilitate a massive change in how data about the nation would be produced. A month later, the bureau’s chief scientist, John Abowd, announced on a government blog the need to “modernize” the system used for disclosure avoidance by turning to “formal privacy” methods. Such an approach would allow the government to renew its guarantee of the confidentiality of data. The description of this innovation did not convey the trade-off that would be discussed later, a trade-off that underpinned the Federal Register notice, a trade-off that pitted accuracy against confidentiality, and then pitted both against the desire for conventional statistical tables with numbers that appeared to resemble counts. Unaware of the broader context, the solicitation for feedback confounded data users and community advocates. Which data mattered? All of it, they answered. They needed all of the data, and it had to be accurate. As the reason for this question became clearer, data users grew upset, sides formed, coalitions coalesced, a controversy bloomed.
Published in 2014, the Facebook “emotional contagion” study prompted widespread discussions about... more Published in 2014, the Facebook “emotional contagion” study prompted widespread discussions about the ethics of manipulating social media content. By and large, researchers focused on the lack of corporate institutional review boards and informed consent procedures, missing the crux of what upset people about both the study and Facebook’s underlying practices. This essay examines the reactions that unfolded, arguing the public’s growing discomfort with “big data” fueled the anger. To address these concerns, we need to start imagining a socio-technical approach to ethics that does not differentiate between corporate and research practices.
While much attention is given to young people’s online privacy practices on sites like Facebook, ... more While much attention is given to young people’s online privacy practices on sites like Facebook, current theories of privacy fail to account for the ways in which social media alter practices of information-sharing and visibility. Traditional models of privacy are individualistic, but the realities of privacy reflect the location of individuals in contexts and networks. The affordances of social technologies, which enable people to share information about others, further preclude individual control over privacy. Despite this, social media technologies primarily follow technical models of privacy that presume individual information control. We argue that the dynamics of sites like Facebook have forced teens to alter their conceptions of privacy to account for the networked nature of social media. Drawing on their practices and experiences, we offer a model of networked privacy to explain how privacy is achieved in networked publics.
Discrimination and racial disparities persist at every stage of the U.S. criminal justice system,... more Discrimination and racial disparities persist at every stage of the U.S. criminal justice system,from policing to trials to sentencing. The United States incarcerates a higher percentage of its population than any of its peer countries, with 2.2 million people behind bars. The criminal justice system disproportionately harms communities of color: while they make up 30 percent of the U.S. population, they represent 60 percent of the incarcerated population. There has been some discussion of how “big data” can be used to remedy inequalities in the criminal justice system; civil rights advocates recognize potential benefits but remained fundamentally concerned that data-oriented approaches are being designed and applied in ways that also disproportionately harms those who are already marginalized by criminal justice processes.Like any other powerful tool of governance, data mining can empower or disempower groups. The values that go into an algorithm, and the metrics it optimizes for, are baked into its design. Data could be used to identify discrimination in current practices, or to predict where certain combinations of data points are likely to lead to an erroneous conviction. When algorithms are designed to improve how law enforcement regimes are deployed, the question that data analytics raises is, which efficiencies are we optimizing for? Who are the stakeholders, and where do they stand to gain or lose? How do these applications intersect with core civil rights concerns? Where can we use big data techniques to improve the structural conditions criminal justice system that lead to disparate impacts on marginalized communities? How do we measure that impact, and the factors that lead to it?
Facebook, like many communication services and social media sites, uses its Terms of Service (ToS... more Facebook, like many communication services and social media sites, uses its Terms of Service (ToS) to forbid children under the age of 13 from creating an account. Such prohibitions are not uncommon in response to the Children’s Online Privacy Protection Act (COPPA), which seeks to empower parents by requiring commercial Web site operators to obtain parental consent before collecting data from children under 13. Given economic costs, social concerns, and technical issues, most general–purpose sites opt to restrict underage access through their ToS. Yet in spite of such restrictions, research suggests that millions of underage users circumvent this rule and sign up for accounts on Facebook. Given strong evidence of parental concern about children’s online activity, this raises questions of whether or not parents understand ToS restrictions for children, how they view children’s practices of circumventing age restrictions, and how they feel about children’s access being regulated. In this paper, we provide survey data that show that many parents know that their underage children are on Facebook in violation of the site’s restrictions and that they are often complicit in helping their children join the site. Our data suggest that, by creating a context in which companies choose to restrict access to children, COPPA inadvertently undermines parents’ ability to make choices and protect their children’s data. Our data have significant implications for policy–makers, particularly in light of ongoing discussions surrounding COPPA and other age–based privacy laws.
National, epidemiological data that provide lifetime rates of psychological, physical, and sexual... more National, epidemiological data that provide lifetime rates of psychological, physical, and sexual adolescent data abuse (ADA) perpetration and victimization within the same sample of youth are lacking. To address this gap, data from 1058 randomly selected U.S. youth, 14-21 years old, surveyed online in 2011 and/or 2012, were weighted to be nationally representative and analyzed. In addition to reporting prevalence rates, we also examined the overlap of the six types of ADA queried. Results suggested that ADA was commonly reported by both male and female youth. Half (51 %) of female youth and 43 % of male youth reported victimization of at least one of the three types of ADA. Half (50 %) of female youth and 35 % of male youth reported at least one type of ADA perpetration. More male youth reported sexual ADA perpetration than female youth. More female youth reported perpetration of psychological and physical ADA and more reported psychological victimization than male youth. Rates wer...
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Books by danah boyd
Boyd’s conclusions are essential reading not only for parents, teachers, and others who work with teens but also for anyone interested in the impact of emerging technologies on society, culture, and commerce in years to come. Offering insights gleaned from more than a decade of original fieldwork interviewing teenagers across the United States, boyd concludes reassuringly that the kids are all right. At the same time, she acknowledges that coming to terms with life in a networked era is not easy or obvious. In a technologically mediated world, life is bound to be complicated.
Papers by danah boyd
Boyd’s conclusions are essential reading not only for parents, teachers, and others who work with teens but also for anyone interested in the impact of emerging technologies on society, culture, and commerce in years to come. Offering insights gleaned from more than a decade of original fieldwork interviewing teenagers across the United States, boyd concludes reassuringly that the kids are all right. At the same time, she acknowledges that coming to terms with life in a networked era is not easy or obvious. In a technologically mediated world, life is bound to be complicated.