Presentations CWI's Lectures on Privacy and Security 2018

Please find below more information about the presentations which were held on 15 November 2018:

Mark Rotenberg
Toward an International Policy Framework for Artificial Intelligence
Governments around the world are grappling with the policy implications of Artificial Intelligence. There is broad agreement that AI is bringing about rapid transformation, but still there is no coherent policy response. In this talk, Marc Rotenberg explores the contours of the AI debate, focusing in particular on recent developments in the US, Europe, and East Asia.  Rotenberg also looks at the increasingly important role of scientific societies and professional organizations that have joined the AI discussion. Rotenberg recommends an international framework, drawing on similar frameworks developed by the OECD, to promote AI innovation while safeguarding fundamental rights. He emphasizes, in particular, transparency and accountability as the twin pillars of an AI policy framework.

Jan Camenisch
Cryptography for Privacy
With the increasing use of digital media for our daily tasks, our privacy is eroding at a fast pace. Recent developments such as public blockchains are even accelerating this pace. In this talk we will argue that this is not only a privacy issue but as well a security problem. We show that lots of existing technologies would protect our data well if only they were used. We will give a couple of examples of such technologies and explain them. Finally we will discuss research and other challenges that still need to be overcome to realize a more secure and privacy-preserving digital world.

Adam Smith
Rigorous Foundations for Statistical Data Privacy
Consider an agency holding a large database of sensitive personal information -- medical records, census survey answers, web search records, or genetic data, for example. The agency would like to discover and publicly release global characteristics of the data while protecting the privacy of individuals' records.
I will begin by discussing what makes this problem difficult, illustrating some challenges via recent attacks. I will present differential privacy, a rigorous definition of privacy in statistical databases that is now widely studied, and increasingly used to analyze and design deployed systems. Time permitting, I will survey differential privacy's applications so far, its connections to other areas of science, and opportunities for further research.

Ed Felten
Issues in AI and Privacy

This lecture will consider how the arrival of artificial intelligence, and specifically advanced machine learning methods, might affect technical and policy considerations of privacy. AI makes access to personal data more empowering in some respects, while at the same time potentially reducing the leverage provided by increasing data access.  AI will also probably change the market structures surrounding data collection and access, with further complex implications for privacy.
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