Fighting Deepfakes When Detection Fails. Brookings Institution. Alex Engler. November 14, 2019
Deepfakes intended to spread misinformation are already a threat to online discourse, and there is every reason to believe this problem will become more significant in the future. So far, most ongoing research and mitigation efforts have focused on automated deepfake detection, which will aid deepfake discovery for the next few years. However, worse than cybersecurity’s perpetual cat-and-mouse game, automated deepfake detection is likely to become impossible in the relatively near future, as the approaches that generate fake digital content improve considerably. In addition to supporting the near-term creation and responsible dissemination of deepfake detection technology, policymakers should invest in discovering and developing longer-term solutions. Policymakers should take actions that:
- Support ongoing deepfake detection efforts with continued funding through DARPA’s MediFor program, as well as adding new grants to support collaboration between detection efforts and training journalists and fact-checkers to use these tools.
- Create an additional stream of funding awards for the development of new tools, such as reverse video search or blockchain-based verification systems, that may better persist in the face of undetectable deepfakes.
- Encourage the release of large social media datasets for social science researchers to study and explore solutions to viral misinformation and disinformation campaigns. [Note: contains copyrighted material].
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The Emerging Risk of Virtual Societal Warfare: Social Manipulation in a Changing Information Environment. RAND Corporation. Michael J. Mazarr et al. October 9, 2019.
The evolution of advanced information environments is rapidly creating a new category of possible cyberaggression that involves efforts to manipulate or disrupt the information foundations of the effective functioning of economic and social systems. RAND researchers are calling this growing threat virtual societal warfare in an analysis of its characteristics and implications for the future.
To understand the risk of virtual societal warfare, the authors surveyed evidence in a range of categories to sketch out some initial contours of how these techniques might evolve in the future. They grounded the assessment in (1) detailed research on trends in the changing character of the information environment in the United States and other advanced democracies; (2) the insights of social science research on attitudes and beliefs; and (3) developments in relevant emerging technologies that bear on the practices of hostile social manipulation and its more elaborate and dangerous cousin, virtual societal warfare. The authors then provide three scenarios for how social manipulation could affect advanced societies over the next decade. [Note: contains copyrighted material].
[PDF format, 215 pages].
Generation AI Establishing Global Standards for Children and AI. World Economic Forum. September 11, 2019.
On 6-7 May 2019, the World Economic Forum Centre for the
Fourth Industrial Revolution and its partners UNICEF and the Canadian Institute
for Advanced Research (CIFAR) hosted a workshop in San Francisco on the joint
“Generation AI” initiative. This workshop identified deliverables in two key
areas: 1) public policy guidelines that direct countries on creating new laws focused
on children and 2) a corporate governance charter that guides companies
leveraging AI to design their products and services with children in mind. [Note: contains copyrighted material].
[PDF format, 18 pages].
Artificial Intelligence Primer: What is Needed to Maximize AI’s Economic, Social, and Trade Opportunities. Brookings Institution. Joshua P. Meltzer. May 13, 2019
Artificial intelligence (AI) has the potential to transform
economic growth, commerce, and trade, affecting the types of jobs that are
available and skills that are needed. The United States, China, Japan, Germany,
the United Kingdom, France, and others have recognized the opportunity and are
supporting AI research and development as well as preparing their workforce.
For AI to develop also requires an enabling environment that
includes new regulation in areas such as AI ethics and data access and revisiting
existing laws and regulation in areas such as privacy and intellectual property
(IP) rights to ensure that they work for AI. In addition, AI development
requires an international agenda to avoid unnecessary regulatory heterogeneity
that creates barriers to data access and use and impedes the global diffusion
of AI products. [Note: contains copyrighted material].
[PDF format, 26 pages].
Automation and Artificial Intelligence: How Machines are Affecting People and Places. Brookings Institution. Mark Muro, Robert Maxim, and Jacob Whiton. January 24, 2019
At first, technologists issued dystopian alarms about the power of automation and artificial intelligence (AI) to destroy jobs. Then came a correction, with a wave of reassurances. Now, the discourse appears to be arriving at a more complicated understanding, suggesting that automation will bring neither apocalypse nor utopia, but instead both benefits and stress alike. Such is the ambiguous and sometimes disembodied nature of the “future of work” discussion.
Hence the analysis presented here. Intended to bring often-inscrutable trends down to earth, the following report develops both backward and forward-looking analyses of the impacts of automation over the years 1980 to 2016 and 2016 to 2030 to assess past and upcoming trends as they affect both people and communities in the United States. [Note: contains copyrighted material].
[PDF format, 108 pages].
Artificial Intelligence Applications to Support Teachers and Teaching: A Review of Promising Applications, Challenges, and Risks. Rand Corporation. Robert F. Murphy. January 24, 2019
Recent applications of artificial intelligence (AI) have been successful in performing complex tasks in health care, financial markets, manufacturing, and transportation logistics, but the influence of AI applications in the education sphere has been limited. However, that may be changing. In this paper, the author discusses several ways that AI applications can be used to support the work of K–12 teachers and the practice of teaching by augmenting teacher capacity rather than replacing teachers. Three promising applications are intelligent tutoring systems, automated essay scoring, and early warning systems. The author also discusses some of the key technical challenges that need to be addressed in order to realize the full potential of AI applications for educational purposes. The paper should be of interest to education journalists, publishers, product developers, researchers, and district and school administrators. [Note: contains copyrighted material].
[PDF format, 20 pages].
What is Machine Learning? Brookings Institution. Chris Meserole. October 4, 2018
Machine learning is now so popular that it has effectively become synonymous with artificial intelligence itself. As a result, it’s not possible to tease out the implications of AI without understanding how machine learning works. [Note: contains copyrighted material].
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