The review looks at the use of algorithmic decision-making in four sectors (policing, local government, financial services and recruitment) and makes cross-cutting recommendations.
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Unless you literally wear a mask all the time, it is almost impossible to completely avoid cameras and face recognition technology. Not only is this a privacy concern, but it also presents a potential liability for companies that need to protect personal data. D-ID, a startup currently taking part in Y Combinator, wants to solve […]
This report has 20 recommendations on the culture of responsibility, and the promotion of data, algorithm and AI literacy through public participation.
The big companies developing them show no interest in fixing the problem. Source: Biased Algorithms Are Everywhere, and No One Seems to Care – MIT Technology Review
Council of Europe´s Committee of Ministers issued a set of guidelines calling on governments to ensure that they do not breach human rights through their own use, development or procurement of algorithmic systems. In addition, as regulators, they should establish effective and predictable legislative, regulatory and supervisory frameworks that prevent, detect, prohibit and remedy human […]
his report provides details about the recognition process, notes where demographic effects could occur, details specific performance metrics and analyses, gives empirical results, and recommends research into the mitigation of performance deficiencies.
Algorithms pervade our lives today, from music recommendations to credit scores to now, bail and sentencing decisions. But there is little oversight and transparency regarding how they work. Nowhere is this lack of oversight more stark than in the criminal justice system. Without proper safeguards, these tools risk eroding the rule of law and diminishing […]
One of the standard critiques of using algorithms for decision-making about people, and especially for consequential decisions about access to housing, credit, education, and so on, is that the algorithms don’t provide an “explanation” for their results or the results aren’t “interpretable.” This is a serious issue, but discussions of it are often frustrating. Source: […]