From social implications of automation to manipulation of algorithmic systems, many of our research efforts track and inform broader conversations about how datadriven systems, automation, and machine intelligence impact people and society.
Who should be accountable? Accountable to whom? Understanding how powerful, technological systems can be governed is a core concern that shapes many of our research efforts.
Concern about what is ethical, just, and appropriate influences how our different research efforts approach trade-offs, conflicting values, and social implications. Notably, many initiatives focus on privacy, social justice, and equity and fairness.
The Media Manipulation initiative works to provide news organizations, civil society, platforms, and policymakers with insights into new forms of media manipulation to ensure a close and informed relationship between technical research and socio-political outcomes. This requires assessing strategic manipulation, imagining the possibilities for encoding fairness and accountability into technical systems, and conducting ethnographic research to describe and understand new social activity.
The Intelligence and Autonomy initiative develops grounded, qualitative research to inform the design, evaluation, and regulation of AI-driven systems.
Technology is disrupting, destabilizing, and transforming many aspects of the labor force. The Future of Labor initiative seeks to better understand emergent disruptions in the labor force as a result of data-centric technological development, with a special focus on structural inequalities.
"Precision medicine" is a growing field that aims to use multiple data sources to tailor medical care to individuals. The Fairness in Precision Medicine initiative aims to critically assess the potential for bias and discrimination in health data collection, sharing, and interpretation.
Libraries and Privacy is a suite of projects exploring the roles of libraries in supporting their communities with regard to data-centric technological development. Topics include privacy in libraries, facilitating safe research data sharing worldwide, and new roles for librarians as data scientists.
Machine learning raises novel challenges for ensuring non-discrimination, due process, and understandability in decision-making. This initiative uses computational approaches and quantitative and qualitative datasets to translate findings to policymakers, regulators, and advocates who seek to understand issues in data and AI ethics.
What is the value of data in education and learning? The Enabling Connected Learning (ECL) initiative assesses how existing and proposed policies affect connected learning initiatives, and where and when education-related
data can and should be used.
Data can provide real-time awareness about disaster, violence, or protest. Yet practitioners, researchers, and policymakers face unique challenges and opportunities when assessing technological benefit, risk, and harm. The Data, Human Rights, and Human Security initiative asks: How can these technologies be used responsibly to assist people in need, prevent abuse, and protect them from harm?
How young people are adapting to a changing media environment to access news they trust.danah boyd, Claire Fontaine, Karen Levy, Alice Marwick
The goal of this project is to better understand how privacy is understood in a networked society and the ways in which control is complicated by the networked nature of information. This project seeks to examine how a theory of networks can better elucidate social, cultural, and legal models of privacy and jurisprudence in a data-centric era.
Led by Amanda Lenhart and Michele Ybarra of the Center for Innovative Public Health Research, this Data & Society project conducted a nationally representative landline and mobile phone survey of 3,000 Americans ages 15 years and older to quantify the prevalence of online harassment, cyberstalking, and digital domestic violence. Recognizing that witnessing abuse can also have a negative impact, the researchers further investigated the extent to which people witness others’ abusive behavior online. The project provides a better understanding of how abuse is perpetrated and experienced through technology.Mary Madden
Making a fundamental contribution to understanding the everyday privacy- and security-related behaviors of low-SES adults.
On October 30, 2014, Data & Society, the Leadership Conference, and New America teamed up to host the first Data & Civil Rights Conference to identify and discuss opportunities and challenges presented by “big data” in the realm of civil rights. This conference focused on examining existing civil rights issues and asking how the availability of data and the practices surrounding data analytics may alter the landscape, both productively and problematically.
In collaboration with the National Science Foundation, the Council for Big Data, Ethics, and Society was started in 2014 to provide critical social and cultural perspectives on big data initiatives. The Council brings together researchers from diverse disciplines — from anthropology and philosophy to economics and law — to address issues such as security, privacy, equality, and access in order to help guard against the repetition of known mistakes and inadequate preparation. Through public commentary, events, white papers, and direct engagement with data analytics projects, the Council developed frameworks to help researchers, practitioners, and the public understand the social, ethical, legal, and policy issues that underpin the big data phenomenon.Noel Hidalgo
A program that combines didactic open data advocacy with local government use. This research explores how New York City's local communities can use civic data to improve local community outcomes.Ingrid Burrington, Surya Mattu
Educational tools that teach people the systems and infrastructure that make the Internet possible.Martha Poon
This research seeks to enrich public debate about consumer credit by investigating the lenders’ perspective. It explains why today’s markets are ravenous for data, and why it seems like data-driven technology is the only means to achieving fair access to credit.