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George J. Tomko, Ph.D.

Abstract: SmartData is the evolution of Privacy by Design – PbD 2.0, which moves control from the organization and places it directly in the hands of the data subject, where it belongs. Instead of having a one-to-many oversight mechanism wherein one organization is responsible for protecting the privacy of many individuals, the goal is to evolve a one-to-one oversight mechanism whereby an individual would be responsible for one set of personal data – one’s own data.  In a world where personal information can increasingly be transmitted and used in multiple locations simultaneously, protecting privacy may only truly be accomplished if the information itself becomes ‘intelligent’ and capable of making appropriate decisions, relating to its release, on behalf of the data subject. In other words, the data must become “smart.” Accordingly, protecting privacy and security becomes a multi-domain task, where each domain must be seamlessly integrated into a functioning whole which we call SmartData.  However, using deep learning techniques alone becomes problematic in terms of seamlessly integrating many domains, current and future, into a functioning whole that can also learn online.

Instead, the proposed methodology for SmartData is based upon embodied software agents within a virtual world, learning models of the world within a framework of evolutionary computation and dynamical systems. Embodied cognition is a growing field of research that emphasizes the formative role that both an agent’s “body” and the environment will play in the development of cognitive processes, primarily through the role of evolved primary actions. The general theory posits that these processes develop when tightly-coupled systems emerge from real-time, goal-directed interactions between agents and their environments, in our case, in a simulated virtual environment. The goal of SmartData is to surpass current limited and brittle data protection methods by being able to respond to unforeseen situations (exceptions to the rules), adapt to these novel circumstances, and provide an accurate, nuanced and contextual representation of an individual’s privacy and data security preferences.

Bio: Adjunct Professor in Computer Science at Ryerson University and Expert-in-Residence at IPSI (Privacy, Security and Identity Institute) at the University of Toronto. Dr. Tomko invented the privacy-enhancing technology “Biometric Encryption,” as well as “Anonymous Database,” both of which were the subject of patents. Later he invented “SmartData,” and is presently working on developing SmartData Intelligent Agents. Dr. Tomko holds over a dozen patents in the areas of optical computing and biometric encryption. He received his Ph.D. in Neuroscience from the University of Toronto as well as undergraduate degrees in Engineering Physics, Electrical Engineering and an Executive MBA. He was Vice-President and General Manager of Chubb Security, after which he co-founded two technology companies where he served as President and CEO, one of which he took public on the Toronto Stock Exchange. He also served as Chairman of Photonics Research Ontario, an Ontario Centre of Excellence.  Dr. Tomko began his professional career as an officer in the Canadian Armed Forces (Navy branch) where he served on submarines and destroyers and also designed anti-missile electronic countermeasure systems.

Konstantinos N. (Kostas) Plataniotis

Abstract: The recent rise of artificial intelligence (AI) can be attributed to the success of deep neural networks (DNN) in tasks, such as image classification and natural language processing.  The availability of curated, large scale and diverse data sets, access to powerful computing infrastructure, and theoretical advances are the main driving factors behind the resurgence. Machine learning (ML), deep neural nets, smart analytics are all trending tools promising disruptive contributions capable of solving real-world problems. Thus, it is not surprising to see a sustained push from industry, policy makers, and government bodies towards accelerating developments in machine learning. The purpose of this presentation is to provide an environmental scan of the research landscape, introduce, in a tutorial style, aspects of the research machinery, and discuss intuition, utility and expectations.

Bio: Konstantinos N. (Kostas) Plataniotis is a Professor and the Bell Canada Chair in Multimedia with the Electrical and Computer Engineering Department, University of Toronto, Toronto, ON, Canada. He is the co-founder and inaugural Director-Research for the Identity, Privacy and Security Institute (IPSI), University of Toronto, and he served as the Director of the Knowledge Media Design Institute (KMDI), University of Toronto, from January 2010 to July 2012. His research interests are knowledge and digital media design, multimedia systems, biometrics, image and signal processing, communications systems, and machine learning. Dr. Plataniotis is a Registered Professional Engineer in the Province of Ontario, a Fellow of IEEE, a Fellow of the Engineering Institute of Canada. He was the IEEE Signal Processing Society Vice President for Membership (2014–2016) and he has served as the Editor-in-Chief of IEEE SIGNAL PROCESSING LETTERS, as Technical Co-Chair of the IEEE 2013 International Conference in Acoustics, Speech and Signal Processing, and as General Co-Chair for the 2017 IEEE GlobalSIP Conference. Dr. Plataniotis is the General Co-Chair for the 2018 International Conference on Image Processing (ICIP-18) and the General Co-Chair for the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021).

Following a series of data breaches and privacy scandals, most notably the controversy surrounding Facebook’s engagement with political firm Cambridge Analytica, there has been increasing discussion over whether Congress should establish comprehensive legislation to protect American consumers’ online privacy. Achieving broad privacy legislation will be a challenge for legislators, given the rapid pace of innovation, but in the coming months, Congress may feel compelled to act. With the recent implications of the EU’s adoption of the General Data Protection Regulations (GDPR), public pressure may also encourage congressional action.

On July 26, the Center for Technology Innovation at Brookings will host a panel discussion to explore a comprehensive framework for U.S. privacy legislation. The discussion will address both the opportunities and challenges associated with such legislation during a period where big data analytics are fueling the new economy and online consumer data is being manipulated and mined for undemocratic purposes. What should be included in federal privacy legislation? Is either the GDPR or the California Consumer Privacy Act a good model?  What types of companies and business models should be covered by legislation? Should different types of companies in the internet ecosystem be regulated the same under a federal system? Which government entity should be responsible for enforcing online privacy guardrails?

After the session, panelists will take audience questions.

RSVP: July 27, 2018 to Cheyenne Blount / mailto:[email protected]/ 646.673.8338

With an increased focus on consumer privacy issues both in the United States and Europe, first-party data, such as a company’s customer database, is becoming a safer and easier asset to exploit. That said, there are still privacy issues to consider whenever consumer data is leveraged for marketing purposes. As regulations continue to evolve, streamlining processes for compliance that minimizes impact on customers has become more complicated, yet more important than ever.

For this program, our panel of speakers – comprised of data privacy legal experts and industry leaders who are already dealing with these rapidly changing developments – will address the following topics and issues:

• Privacy-compliant methods for leveraging first party data.
• Opportunities and challenges associated with various data sources and technology practices.
• Best practices for staying on top of regulatory, self-regulatory and legislative developments.
• What to do if/when a company receives an enforcement notice.

Speakers:
Gary Kibel, Digital Media, Technology & Privacy Partner, Davis & Gilbert LLP
Andy Dale, Esq., General Counsel, VP Global Privacy, SessionM
David Hale, Chief Privacy Officer, TD Ameritrade
Noga Rosenthal, Esq., Chief Privacy Officer, Epsilon

Registration and Networking: 5:30 – 6:15 p.m.
Seminar: 6:15 – 7:30 p.m.
Cocktail and Network Reception: 7:30 – 8:30 p.m.

Location:
Davis & Gilbert LLP
1740 Broadway, 19th Floor
(between 55th and 56th Streets)
New York City

We’re excited to announce the opening of the Partnership on AI’s new headquarters! Come visit our San Francisco office to meet our staff, our members, and to learn more about our current work and community. You can expect casual mingling with brief remarks from our leadership and board.

Drinks and small bites will be served. PAI Partners and friends welcome; RSVP required to attend.

Join VA Privacy Service and leading privacy experts on August 9, 2018 in the G.V. “Sonny” Montgomery Veterans Auditorium, Room 230, at 810 Vermont Ave in Washington, D.C. for exciting sessions on fostering privacy awareness across the individual, the agency and the broader community.

Experts will discuss individual responsibility in creating a culture of privacy, how Federal agencies are addressing privacy concerns, and opportunities for collaboration with external partners to ensure privacy and security on all fronts.

Attendees are eligible to receive Continuing Privacy Education credits. VA employees are also eligible to receive Talent Management System credits for attending.

Agenda:

8:15 a.m.– 8:30 a.m.

Arrive

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8:30 a.m.– 9:05 a.m.

Welcome, Opening Remarks, and Keynote Address

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9:05 a.m.–9:55 a.m.

Pillar I: The Individual

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9:55 a.m.–10:10 a.m.

Networking I

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10:10 a.m.–11:00 a.m.

Pillar II: The Agency

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11:00 a.m.–11:15 a.m.

Networking II

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11:15 a.m.–12:05 p.m.

Pillar III: The Broader Community

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12:05 p.m.–12:15 p.m.

Closing Session

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12:15 a.m.–12:30 a.m.

Networking III

Continuing Education credit:

Attendees are eligible to receive Continuing Privacy Education credits.

VA employees are also eligible to receive Talent Management System credits for attending.

The workshop will discuss security and privacy issues of broader significance as well as technical challenges. This workshop is not limited to CS people. We invite applications from Social Science, Mathematics, Economics and Engineering Departments also.