World Economic Forum Global Risk Report identifies cyberattacks and data theft as significant economic risks

The Global Risk Report 2017 from the World Economic Forum cites threats to global economic wellbeing ranging from natural disasters and large scale involuntary migration to — this year — risks arising from a “growing cyberdependency.” Specific risks the report calls out in this category are cyberattacks, data fraud and theft, critical infrastructure breakdown, and “adverse consequences of technology advances.” Among economic risks that are most likely to happen, the WEF report called out data theft or fraud as one of the top five most likely risks, and listed cyberattacks as number six.

In the report, there is a discussion of machine learning and AI as emerging technologies with some degree of risk. Regarding privacy, the report stated that: “AI systems are also being used in surveillance and monitoring – analysing video and sound to spot crime, help with anti-terrorism and report unusual activity. How much they will come to reduce overall privacy is a real concern.” The public dialogue around AI and machine learning is still in its inception, and the current dialogue is hampered to some degree by varying definitions of AI and machine learning. That being said, that machine learning and AI have found their way into this year’s WEF risk report is notable in and of itself and highlights the importance of ongoing, robust public dialogue.

Image from World Economic Forum Global Risks Report 2017, available at http://www3.weforum.org/docs/GRR17_Report_web.pdf

Posted January 27, 2017 in Cybercrime, Cybersecurity, Data Breach, Digital Privacy, Future of Privacy, Machine Learning

New Report: Risky Analysis: Assessing and Improving AI Governance Tools

We are pleased to announce the publication of a new WPF report, “Risky Analysis: Assessing and Improving AI Governance Tools.” This report sets out a definition of AI governance tools, documents why and how these tools are critically important for trustworthy AI, and where these tools are around the world. The report also documents problems in some AI governance tools themselves, and suggests pathways to improve AI governance tools and create an evaluative environment to measure their effectiveness. AI systems should not be deployed without simultaneously evaluating the potential adverse impacts of such systems and mitigating their risks, and most of the world agrees about the need to take precautions against the threats posed. The specific tools and techniques that exist to evaluate and measure AI systems for their inclusiveness, fairness, explainability, privacy, safety and other trustworthiness issues — called in the report collectively AI governance tools – can improve such issues. While some AI governance tools provide reassurance to the public and to regulators, the tools too often lack meaningful oversight and quality assessments. Incomplete or ineffective AI governance tools can create a false sense of confidence, cause unintended problems, and generally undermine the promise of AI systems. The report contains rich background details, use cases, potential solutions to the problems discussed in the report, and a global index of AI Governance Tools.
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Report: From the Filing Cabinet to the Cloud: Updating the Privacy Act of 1974

This comprehensive report and proposed bill text is focused on the Privacy Act of 1974, an important and early Federal privacy law that applies to the government sector and some contractors. The Privacy Act was written for the 1970s information era -- an era that was characterized by the use of mainframe computers and filing cabinets. Today's digital information era looks much different than the '70s: smart phones are smarter than the old mainframes, and documents are now routinely digitized and stored and perhaps even analyzed in the cloud, among many other changes. The report focuses on why the Privacy Act needs an update that will bring it into this century, and how that could look and work. This work was written by Robert Gellman, and informed by a two-year multi-stakeholder process.