How the Chinese Government Fabricates Social Media Posts

Speaker: Jennifer Pan
Date recorded: Feb 22, 2017
Jennifer Pan on how the Chinese government fabricates social media posts for strategic distraction, not engaged argument.

Jennifer Pan: The Chinese government has long been suspected of hiring as many as 2,000,000 people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called “50c party” posts vociferously argue for the government’s side in political and policy debates. Jennifer’s research shows that this is also true of the vast majority of posts openly accused on social media of being 50c. Yet, almost no systematic empirical evidence exists for this claim, or, more importantly, for the Chinese regime’s strategic objective in pursuing this activity.

In the first large scale empirical analysis of this operation, Jennifer’s research reveals how to identify the secretive authors of these posts, the posts written by them, and their content. She and her team estimate that the government fabricates and posts about 448 million social media comments a year. In contrast to prior claims, her research shows that the Chinese regime’s strategy is to avoid arguing with skeptics of the party and the government, and to not even discuss controversial issues. Her work infers that the goal of this massive secretive operation is instead to regularly distract the public and change the subject, as most of the these posts involve cheerleading for China, the revolutionary history of the Communist Party, or other symbols of the regime. She will discuss how these results fit with what is known about the Chinese censorship program, and suggest how they may change our broader theoretical understanding of “common knowledge” and information control in authoritarian regimes.

Jennifer Pan is an Assistant Professor of Communication, Assistant Professor, by courtesy, of Political Science and of Sociology at Stanford University. Her research focuses on the politics of authoritarian (non-democratic) countries in the digital age. How autocrats constrain collective action through online censorship, propaganda, and responsiveness. How information proliferation influences the ability of authoritarian regimes to collect reliable information. How public preferences are arranged and formed. She combines experimental and computational methods with large-scale datasets on political activity in China and other authoritarian regimes to examine these questions. Her work has appeared in peer-reviewed journals such as the American Political Science Review, American Journal of Political Science, and Science. She received her Ph.D. from Harvard University’s Department of Government in 2015. She graduated from Princeton University, summa cum laude, in 2004, and until 2009, she was a consultant at McKinsey & Company based in New York and Beijing.

Data Science from Wall Street to Startups to Academic Biomedicine

Speaker: Jeff Hammerbacher
Date recorded: Feb 16, 2017
Jeff Hammerbacher discusses academic biomedicine research at Hammer Lab, and how his prior experience in data science at Bear Stearns, Facebook, and Cloudera motivate his work.

Jeff Hammerbacher gives an overview of his work at Hammer Lab where he and his colleagues use data science to understand and improve the immune response to cancer. He also discusses the design of Hammer Lab, particularly focusing on ways that the lab is directly informed and motivated by his prior work experience at Bear Stearns, Facebook, and Cloudera.

Jeff is an Assistant Professor at the Medical University of South Carolina and the Icahn School of Medicine at Mount Sinai, a founder and the Chief Scientist of Cloudera, an angel investor with his wife Halle Tecco at Techammer, and a board member of CIOX Health and Sage Bionetworks. Jeff was an Entrepreneur in Residence at Accel Partners immediately prior to founding Cloudera. Before Accel, he conceived, built, and led the Data team at Facebook. Before joining Facebook, Jeff was a quantitative analyst on Wall Street. Jeff earned his Bachelor’s Degree in Mathematics from Harvard University.

Privacy in the Era of Personal Genomics

Speaker: The Biotech Futures Talk + Lab Series
Date recorded: Jan 19, 2017
A conversation exploring the promises, challenges, and perils as genomics becomes a common part of everyday life.

Jason Bobe, Sophie Zaaijer, Heather Dewey-Hagborg, Daniel Grushkin – Genomics, the collection and interpretation of DNA sequences, has long promised to change the way doctors practice medicine, scientists research disease and the environment, and ultimately the way we understand ourselves. In the past, reading DNA was slow, laborious, and expensive. Reading the first human genome cost $3 billion and took 13 years to complete in 2003. Today, that same genome could be read for roughly $1,000 in a few hours. And a gene sequencer, once a lumbering machine, can now fit into the palm of a hand.

In less than a decade, the practice of genomics has become ubiquitous, and the data sets enormous. Its wide adoption comes barbed with ethical challenges, tensions between scientific progress and individual privacy, and a heritage based in racial discrimination.

Panelists: Jason Bobe, Sophie Zaaijer
Moderator: Heather Dewey-Hagborg
Introduced by: Daniel Grushkin
Presented by: Genspace and Data & Society

ABOUT THE SERIES

The Biotech Futures Talk + Lab Series explores the implications of and ways in which biology is becoming a data science. Each talk is paired with a 3-4 hour lab workshop at Genspace for Data & Society and Genspace community members to demonstrate how these themes become realized in the lab. Lab details to follow.

PANELISTS:

JASON BOBE

Jason Bobe is Associate Professor and Director of the Sharing Lab at Icahn Institute at Mount Sinai. For the past 10 years, Jason has been at the forefront of innovative data sharing practices in health research. His work on the Personal Genome Project at Harvard, and now three other countries, pioneered new approaches for creating well-consented public data, cell lines and other open resources. These efforts led to important changes in the governance of identifiable health data and also led to the development of valuable new products, such as NIST’s standardized human genome reference materials (e.g. NIST RM 8392), now used for calibrating clinical laboratory equipment worldwide.

More recently, he co-founded Open Humans, a platform that facilitates participant-centered data sharing between individuals and the health research community. At the Sharing Lab, he attempts to produce health research studies that people actually want to join and works on improving our understanding of how to make great, impactful studies capable of engaging the general public and achieving social good. He is alsothe leader of the Resilience Project, an effort leveraging open science approaches to identify and learn how some people are able avoid disease despite having serious risk factors. Last year, he was selected to be in the inaugural class of Mozilla Open Science Fellows. He is also co-founder of two nonprofits: Open Humans Foundation and DIYbio.org.

SOPHIE ZAAIJER

Dr. Sophie Zaaijer is a Postdoctoral Researcher in the Erlich’s lab at the New York Genome Center and Columbia University. Sophie is from the Netherlands, where she did her undergraduate in Music (viola) and Food Technology. For her Masters, she studied Medical Biotechnology at Wageningen University and went to Harvard Medical School to finish her thesis work in Monica Colaiacovo’s lab. She next went on to do a PhD in Molecular Biology and Genetics in Julie Cooper’s lab at Cancer Research UK, London (now the Crick Institute) and at the National Institutes of Health, Bethesda. Sophie focuses on genome technology and the growing impact of genomics on our daily lives.

MODERATOR:

HEATHER DEWEY-HAGBORG

Heather Dewey-Hagborg is a transdisciplinary artist and educator who is interested in art as research and critical practice. Her controversial biopolitical art practice includes Stranger Visions in which she created portrait sculptures from analyses of genetic material (hair, cigarette butts, chewed up gum) collected in public places.

Heather has shown work internationally at events and venues including the World Economic Forum, Shenzhen Urbanism and Architecture Biennale, the New Museum, and PS1 MOMA. Her work has been widely discussed in the media, from the New York Times and the BBC to TED and Wired.
She is an Assistant Professor of Art and Technology Studies at the School of the Art Institute of Chicago and a 2016 Creative Capital award grantee in the area of Emerging Fields.

INTRODUCTION:

DANIEL GRUSHKIN

Daniel Grushkin is founder of the Biodesign Challenge, an international university competition that asks students to envision future applications of biotech. He is co-founder and Cultural Programs Director of Genspace, a nonprofit community laboratory dedicated to promoting citizen science and access to biotechnology. Fast Company ranked Genspace fourth among the top 10 most innovative education companies in the world.

Daniel is a Fellow at Data & Society. From 2013-2014, he was a fellow at the Woodrow Wilson International Center for Scholars where he researched synthetic biology. He was an Emerging Leader in Biosecurity at the UPMC Center of Health Security in 2014. As a journalist, he has reported on the intersection of biotechnology, culture, and business for publications including Bloomberg Businessweek, Fast Company, Scientific American and Popular Science.

Living and Learning in the Digital Age

Speaker: Sonia Livingstone
Date recorded: Nov 1, 2016
Where and why do digital media – and digital media learning – fit into the lives of young teenagers living in complex urban societies?

Sonia Livingstone on where and why do digital media – and digital media learning – fit into the lives of young teenagers living in complex urban societies? Do they help build valued connections, or enhance opportunities to create, learn and participate? Or do they lead to hyper-connection, surveillance and loss of privacy for young people? Reflecting on a year’s ethnography (free to read at http://connectedyouth.nyupress.org/) with a class of 13 year olds, exploring their sites of living and learning online and offline, Sonia argues that their understandable desire for ‘positive disconnections’ means crucial opportunities to learn are being missed. These might be overcome with a more child-centered or even child-rights approach to the digital age.

The Messy Realities of Digital Schooling

Speaker: Neil Selwyn
Date recorded: Apr 7, 2016
Highlighting ways in which schools’ actual uses of technology often contradict presumptions of ‘connected learning’ and ‘digital education.’

In this Databite, Neil Selwyn works through some emerging headline findings from a new three year study of digital technology use in Australian high schools. In particular Neil highlights the ways in which schools’ actual uses of technology often contradict presumptions of ‘connected learning’, ‘digital education’ and the like. Instead Neil considers…

• how and why recent innovations such as maker culture, personalised learning and data-driven education are subsumed within more restrictive institutional ‘logics’;
• the tensions of ‘bring your own device’ and other permissive digital learning practices
• how alternative and resistant forms of technology use by students tend to mitigate *against* educational engagement and/or learning gains;
• the ways in which digital technologies enhance (rather than disrupt) existing forms of advantage and privilege amongst groups of students;
• how the distributed nature of technology leadership and innovation throughout schools tends to restrict widespread institutional change and reform;
• the ambiguous role that digital technologies play in teachers’ work and the labor of teaching;
• the often surprising ways that technology seems to take hold throughout schools – echoing broader imperatives of accountability, surveillance and control.

The talk provides plenty of scope to consider how technology use in schools might be ‘otherwise’, and alternate agendas to be pursued by educators, policymakers, technology developers and other stakeholders in the ed-tech space.

Student Privacy and Big Data

Speaker: Elana Zeide
Date recorded: Jan 21, 2016
The current student privacy regulatory regime does not address the issues raised by modern information technology and data-driven decision-making in education.

Elana Zeide on Student Privacy and Big Data. With the rise of online learning environments, student records are no longer just basic academic and administrative information, but include data and metadata generated from student interaction with digital platforms as well as unexpected sources like student ID badges and social media. Applying big data analytics to this wealth of information has the potential to revolutionize education, but also risks unintended consequences that affect the core values of the education system as well as civil rights and liberties.

The current student privacy regulatory regime does not address the issues raised by modern information technology and data-driven decision-making in education. This presentation highlights key issues of the student privacy debate, proposed reforms, and emerging legal and ethical issues, as well as implications of data-driven education environments and decision-making that extend far beyond school settings.

An AI Pattern Language: Accounting for Human Factors & Human Frames

Speaker: Madeleine Clare Elish
Date recorded: Jan 25, 2017
How are practitioners grappling with the social impacts of AI systems? An AI Pattern Language presents a taxonomy of social challenges that emerged from interviews with a range practitioners working in the intelligent systems and AI industry.

Madeleine Clare Elish presents “An AI Pattern Language,” coauthored with Tim Hwang. The publication is the culmination of two years of research and conversations with a range of industry practitioners working in intelligent systems and artificial intelligence. The work was supported by the John D. and Catherine T. MacArthur Foundation. You can purchase your own copy or download the PDF at autonomy.datasociety.net.

Predictive Policing: Bias In, Bias Out

Speaker: Kristian Lum
Date recorded: Nov 17, 2016
Machine learning algorithms are designed to learn and reproduce patterns in data, but if biased data is used to train these predictive models, the models will reproduce and in some cases amplify those same biases.

Kristian Lum will elaborate on the concept of “bias in, bias out” in machine learning with a simple, non-technical example. She will then demonstrate how applying machine learning to police records can result in the over-policing of historically over-policed communities. Using a case study from Oakland, CA, she will show one specific case of how predictive policing not only perpetuates the biases that were previously encoded in the police data, but – under some circumstances – actually amplifies those biases.

Social Dilemmas Around New Media

Speaker: Ilana Gershon
Date recorded: Mar 17, 2016
We all have moments in which someone’s use of new media baffles us, and we have to ask a friend how to respond. It often isn’t just the content of the message, it is also using that particular medium in that way which leaves us scratching our heads.

Ilana Gershon discusses how we all have moments in which someone’s use of new media baffles us, and we have to ask a friend how to respond. It often isn’t just the content of the message, it is also using that particular medium in that way which leaves us scratching our heads. In this talk, I discuss what anthropological concepts can help us understand our confusion. I will turn to LinkedIn as my case study and analyze the dilemmas people face when using LinkedIn as they look for a job. This will be my starting point to discuss how the newness of new media generates social dilemmas, especially for the people these days who are looking for a job.

Self-regulation in Sensor Society

Speaker: Natasha Schüll
Date recorded: Mar 31, 2016
In the story of self-tracking technology and its increasing automation, a certain ambivalence over the terms of contemporary selfhood comes to the fore.

Natasha Schüll – From the NSA scandal to Facebook’s controversial “mood experiment,” the past decade has seen heated debate over the ways that governments and corporations collect data on citizens and consumers, the ends to which they use it, and the threat this poses to civil liberties. Yet even as this discussion over surveillant monitoring unfolds, the public has embraced practices and products of self-tracking, applying sensor-laden patches, wristbands, and pendants to their own bodies.

Drawing on ethnographic fieldwork, this talk explores how mainstream self-tracking technologies – in their design, marketing, and use – increasingly part ways with the ethos of intensive self-attention found within the Quantified Self (QS) community, serving as digital compasses to guide consumers through the confounding, tempting, and sometimes toxic landscape of everyday choice making and lifestyle management (for instance, by regulating the micro-rhythms of their bites, steps, sips, and breaths). By offering them a way to fulfill the cultural demand for self-management while delegating the often tedious, sometimes existentially taxing labor involved in meeting that demand, such devices at once exemplify and short-circuit ideals of individual agency and responsibility.

In the story of self-tracking technology and its increasing automation, a certain ambivalence over the terms of contemporary selfhood comes to the fore. Are there any connections to be drawn between this ambivalence and broader debates over governmental and corporate surveillance, data privacy, and the possibility for resistance?