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[…] explaining approaches to data protection. Unlike traditional software, in machine learning systems privacy or security harms do not necessarily require direct access to underlying data or source code. The white paper presents a layered approach to data protection in machine learning, including recommending techniques such as noise injection, inserting intermediaries between training data and […]

[…] of video manipulation, but those processes were generally expensive, time-consuming, and imperfect. That is no longer the case.  Professional tools are increasingly effective and affordable, and open-source code that even relative amateurs can use will soon be available to produce believable digital video forgeries.  Already impressive, these new tools are improving quickly. It may […]

[…] which FPF released last October. Most of what has been implemented is machine learning – algorithms that can evaluate their own output and make adjustments to their code without human involvement. Machine learning is used in image recognition, facial recognition, sensory inputs for autonomous vehicles, and many other tasks. I like the definition of […]

[…] into the global elderly and disab ility assistive -devices market , which was valued at $14 billion in 2015 and is expected to surpass $26 billion by 2024 .22 There are also opportunities to reach new customers without disabilities , as many IoT products and services designed for people with disabilities rise to mainstream […]

[…] media users with political ads remains an ongoing issue today.”  Although GDPR does capture the activity of political actors in Europe, guidance in the form of a Code of Conduct for political advertisers would be welcome, according to a new opinion from the European Data Protection Supervisor. How can we support more legitimate research […]

[…] a “black box” that is inevitably plagued by bias and potential injustice. While recognizing that algorithms are man-made artifacts, written and edited by humans in order to code decision-making processes, the article argues that a distinction should be drawn between “policy-neutral algorithms,” which lack an active editorial hand, and “policy-directed algorithms,” which are intentionally framed […]

[…] a “black box” that is inevitably plagued by bias and potential injustice. While recognizing that algorithms are man-made artifacts, written and edited by humans in order to code decision-making processes, the article argues that a distinction should be drawn between “policy-neutral algorithms,” which lack an active editorial hand, and “policy-directed algorithms,” which are intentionally framed […]