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Why We Need to Audit Algorithms

Algorithmic decision-making and artificial intelligence (AI) hold enormous potential and are likely to be economic blockbusters, but we worry that the hype has led many people to overlook the serious problems of introducing algorithms into business and society. Indeed, we see many succumbing to what Microsoft’s Kate Crawford calls “data fundamentalism” — the notion that massive datasets are repositories that yield reliable and objective truths, if only we can extract them using machine learning tools.

A more nuanced view is needed. It is by now abundantly clear that, left unchecked, AI algorithms embedded in digital and social technologies can encode societal biases, accelerate the spread of rumors and disinformation, amplify echo chambers of public opinion, hijack our attention, and even impair our mental wellbeing.

Full article: Why We Need to Audit Algorithms

Cambridge Analytica Knew How You’d Vote If You Wore Wrangler

The whistle-blower behind the Cambridge Analytica revelations said the now-defunct data research firm used the fashion preferences of Facebook Inc. users to help develop the algorithms needed to target them with political messaging.

Sharing examples of the anonymized data for the first time, originally collected and used by Cambridge Analytica, Christopher Wylie said people who displayed an interest in Abercrombie & Fitch tended on average to be less cautious and more liberal, and individuals who liked Wrangler were usually more conservative and more keen on “orderliness.”

Full article: Cambridge Analytica Knew How You’d Vote If You Wore Wrangler – Bloomberg

Algorithms can reduce discrimination, but only with proper data

If self-learning algorithms discriminate, it is not because there is an error in the algorithm, but because the data used to train the algorithm are “biased.”

It is only when you know which data subjects belong to vulnerable groups that bias in the data can be made transparent and algorithms trained properly. The taboo against collecting such data should, therefore, be broken, as this is the only way to eliminate future discrimination.

Full article: Algorithms can reduce discrimination, but only with proper data

Facebook to let French regulators investigate on moderation processes

Facebook and the French government are going to cooperate to look at Facebook’s efforts when it comes to moderation. At the start of 2019, French regulators will launch an informal investigation on algorithm-powered and human moderation. Facebook is willing to cooperate and give unprecedented access to its internal processes.

Full article: Facebook to let French regulators investigate on moderation processes

Child abuse algorithms: from science fiction to cost-cutting reality

In an age of austerity, and a climate of fear about child abuse, perhaps it is unsurprising that social workers have turned to new technology for help.

Local authorities are beginning to ask whether big data could help to identify vulnerable children. Could a computer program flag a problem family, identify a potential victim and prevent another Baby P or Victoria Climbié?

Source: Child abuse algorithms: from science fiction to cost-cutting reality | Society | The Guardian

Health Insurers Tap Data Brokers To Help Predict Costs

Without scrutiny, insurers and data brokers are predicting your health costs based on public data about things like race, marital status, your TV consumption and even if you buy plus-size clothing. The companies are tracking your race, education level, TV habits, marital status, net worth. They’re collecting what you post on social media, whether you’re behind on your bills, what you order online. Then they feed this information into complicated computer algorithms that spit out predictions about how much your health care could cost them.

Source: Health Insurers Tap Data Brokers To Help Predict Costs : Shots – Health News : NPR

Algorithms and artificial intelligence: CNIL’s report on the ethical issues

Numerous initiatives on the governance of artificial intelligence are currently being undertaken. In this context, this report aims at giving an overview of the main ethical matters which are raised, and to increase the collective awareness on these issues in civil society.

Source: Algorithms and artificial intelligence: CNIL’s report on the ethical issues

Facial recognition system had 7 percent hit rate at 2017 Champions League Final

NEC system trialled at UEFA Champions League Final by South Wales Police produced almost 2,300 false positives.

South Wales Police said the high number of false positives at the Cardiff final was due to poor quality images supplied by UEFA, Interpol, and other agencies; an old NEC algorithm; and it being the first major deployment.

Source: Facial recognition system had 7 percent hit rate at 2017 Champions League Final | ZDNet

Questions We Need To Be Asking Before Deciding an Algorithm is the Answer

Across the globe, algorithms are quietly but increasingly being relied upon to make important decisions that impact our lives.

This includes determining the number of hours of in-home medical care patients will receive, whether a child is so at risk that child protective services should investigate, if a teacher adds value to a classroom or should be fired , and whether or not someone should continue receiving welfare benefits.

Source: Math Can’t Solve Everything: Questions We Need To Be Asking Before Deciding an Algorithm is the Answer

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