Algorithm accountability

I came across an article “If Algorithms know all, how much should humans help?” which states that: 

“Big companies and start-ups are beginning to use the technology in decisions like medical diagnosis, crime prevention and loan approvals. The application of data science to such fields raises questions of when close human supervision of an algorithm’s results is needed.” The article referred to a branch of academic study known as algorithmic accountability. The author states that public interest and civil rights organizations are scrutinizing the implications of data science, both the pitfalls and the potential and warns that

“…there is a serious challenge, given the complexity and opacity of data science. Will a technology that promises large benefits on average sufficiently protect the individual from a mysterious and wayward decision that might have a lasting effect on a person’s life?”

I googled ‘algorithm accountability’ to see what it was all about and came across these interesting articles, reports and videos.

This report Civil Rights, Big Data, and Our Algorithmic Future A September 2014 report on social justice and technology by Robinson + Yu.

“Big data can and should bring greater safety, economic opportunity, and convenience to all people. At their best, new data-driven tools can strengthen the values of equal opportunity and equal justice. They can shed light on inequality and discrimination, and bring more clarity and objectivity to the important decisions that shape people’s lives.

But we also see some risks. For example, inaccuracies in databases can cause serious civil rights harms. The E-Verify program, the voluntary, government-run system that employers can use to check whether new employees are work-eligible, has been plagued by an error rate that is 20 times higher for foreign-born workers than for those born in the United States. E-Verify has been under development since it was first authorized in 1996, uses data only from one fairly homogenous source—the government—and is frequently audited. Yet after nearly 20 years, persistent errors remain. This experience provides an important lesson for existing commercial systems, which are fairly new and untested, use data from widely different sources, and operate with no transparency.”

Algorithmic Accountability: On the Investigation of Black Boxes “We’re now operating in a world where automated algorithms make impactful decisions that can and do amplify the power of business and government. I’ve argued in this paper that we need to do better in deciphering the contours of that power. As algorithms come to regulate society and perhaps even implement law directly,47we should proceed with caution and think carefully about how we choose to regulate them back.”


Camilla Wood

UK based Legal Aid Lawyer

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