September 9, 2019
In London? See our work on Adversarial Machine Learning at the Science Museum
Research exploring adversarial machine learning, or the ability to fool machine learning systems, is on display at the Science Museum in London as part of “Driverless: Who is in Control?” This free exhibit includes a modified stop sign developed by a team of researchers to fool driverless cars into misidentifying it and asks “can self-driving cars see the world as well as you can?”
MoreAugust 21, 2019
Co-Director Ryan Calo on Adversarial Machine Learning and the Law
OneZero by Medium
"Using adversarial machine learning, researchers can trick machines — potentially with fatal consequences. But the legal system hasn’t caught up."
ArticleMarch 22, 2019
Lab Co-Director Ryan Calo Discusses Data and Privacy
Geekwire and KUOW
Lab Co-Director Ryan Calo discusses data and privacy on a panel hosted by KUOW and Geekwire with Marketplace Tech's Molly Wood.
ArticleMarch 20, 2019
Toward Inclusive Tech Policy Design: A Method for Underrepresented Voices to Strengthen Tech Policy Documents
New research published in Ethics of Information Technology introduces the Diverse Voices method and reports on two case studies demonstrating its use: one with a white paper on augmented reality technology, and the other with a strategy document on automated driving vehicle technologies.
MoreMarch 19, 2019
Highlights from Our Fifth Year
The Tech Policy Lab at the University of Washington has become an indispensable source for tech policy research, education, and local, national, and international thought leadership. The Lab has worked directly with policymakers, published research and guides on emerging technologies, and provided opportunities for the public to learn from experts.
MoreFebruary 13, 2019
Co-Director Batya Friedman inducted into the CHI Academy
UW iSchool
"Three University of Washington professors, including two from the Information School, have been inducted into the CHI Academy – recognized as the highest honor in the field of human-computer interaction."
ArticleFebruary 5, 2019
Data Statements for NLP: Toward Mitigating System Bias and Enabling Better Science
New Research
In research published in Transactions of the Association for Computational Linguistics, experts in information science and computational linguistics propose data statements as a design solution and professional practice for natural language processing technologists to help mitigate issues related to exclusion and bias.
MoreJanuary 9, 2019
Join the New Diverse Voices Mailing List!
We’ve started a new mailing list for our Diverse Voices project, DiverseVoices@uw.edu. Through this mailing list you will be able to connect with others interested in the Diverse Voices method, ask questions, and receive information on additional resources. To join the mailing list, go to https://mailman11.u.washington.edu/mailman/listinfo/diversevoices. Through the mailing list, you will have access to: • Q&A. We […]
MoreOctober 16, 2018
New Research on Adversarial Machine Learning
Last fall, a team of researchers with the Lab’s Ivan Evtimov, Earlence Fernandes, and Co-Director Yoshi Kohno shared research on ArXiv showing that malicious alterations to real world objects could cause devices to “misread” the image. Specifically, the team tricked an object classifier, like those present in self-driving cars, into misidentifying a stop sign as a […]
MoreOctober 10, 2018
Co-Director Batya Friedman Joins Panel at NAE Annual Meeting on Security and Privacy
On October 1st, 2018, Tech Policy Lab Faculty Co-Director Batya Friedman discussed privacy and security in the 21st century as part of a panel at the 2018 National Academy of Engineering (NAE) annual meeting.
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