Month: August 2016
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Routing Detours: Can We Avoid Nation-State Surveillance?
Since 2013, Brazil has taken significant steps to build out their networking infrastructure to thwart nation-state mass surveillance. For example, the country is deploying a 3,500-mile fiber cable from Fortaleza, Brazil to Portugal; they’ve switched their government email system from Microsoft Outlook to a state-built system called Expresso; and they now have the largest IXP…
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Differential Privacy is Vulnerable to Correlated Data — Introducing Dependent Differential Privacy
[This post is joint work with Princeton graduate student Changchang Liu and IBM researcher Supriyo Chakraborty. See our paper for full details. — Prateek Mittal ] The tussle between data utility and data privacy Information sharing is important for realizing the vision of a data-driven customization of our environment. Data that were earlier locked up…
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Language necessarily contains human biases, and so will machines trained on language corpora
I have a new draft paper with Aylin Caliskan-Islam and Joanna Bryson titled Semantics derived automatically from language corpora necessarily contain human biases. We show empirically that natural language necessarily contains human biases, and the paradigm of training machine learning on language corpora means that AI will inevitably imbibe these biases as well. Specifically, we look at…
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Security against Election Hacking – Part 2: Cyberoffense is not the best cyberdefense!
State and county election officials across the country employ thousands of computers in election administration, most of them are connected (from time to time) to the internet (or exchange data cartridges with machines that are connected). In my previous post I explained how we must audit elections independently of the computers, so we can trust the…
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Security against Election Hacking – Part 1: Software Independence
There’s been a lot of discussion of whether the November 2016 U.S. election can be hacked. Should the U.S. Government designate all the states’ and counties’ election computers as “critical cyber infrastructure” and prioritize the “cyberdefense” of these systems? Will it make any difference to activate those buzzwords with less than 3 months until the…
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The workshop on Data and Algorithmic Transparency
From online advertising to Uber to predictive policing, algorithmic systems powered by personal data affect more and more of our lives. As our society begins to grapple with the consequences of this shift, empirical investigation of these systems has proved vital to understand the potential for discrimination, privacy breaches, and vulnerability to manipulation. This emerging…
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A response to the National Association of Secretaries of State
Election administration in the United States is largely managed state-by-state, with a small amount of Federal involvement. This generally means that each state’s chief election official is that state’s Secretary of State. Their umbrella organization, the National Association of Secretaries of State, consequently has a lot of involvement in voting issues, and recently issued a…
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Supplement for Revealing Algorithmic Rankers (Table 1)
Table 1: A ranking of Computer Science departments per csrankings.org, with additional attributes from the NRC assessment dataset. Here, the average count computes the geometric mean of the adjusted number of publications in each area by institution, faculty is the number of faculty in the department, pubs is the average number of publications per faculty…
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Revealing Algorithmic Rankers
By Julia Stoyanovich (Assistant Professor of Computer Science, Drexel University) and Ellen P. Goodman (Professor, Rutgers Law School) ProPublica’s story on “machine bias” in an algorithm used for sentencing defendants amplified calls to make algorithms more transparent and accountable. It has never been more clear that algorithms are political (Gillespie) and embody contested choices (Crawford),…