Algorithmic Control: Automated Decisionmaking in America’s Cities
Governing bodies throughout the United States are turning to automated decision making systems in an attempt to make their operations more efficient, their services more equitable, and their economies more robust. These technologies, though, aren’t free from the biases and bad calculations that also plague human decision making, and they’ll need their own accountability measures and guarantees of transparency to protect the populace against institutionalizing poor choices.
MuckRock and the Rutgers Institute for Information Policy & Law (RIIPL) are collaborating on a new reporting and research project about local government use of big data, artificial intelligence, and algorithms.
According to Rutgers Law Professor Ellen P. Goodman, who will be partnering on the project, “Algorithms are playing an ever larger part in who goes to jail, who gets dibs on the best education, how we move through cities, and every other part of public life – we need to know more about them.”
Through interviews with leading experts and public records requests filed across the country, MuckRock Projects Editor/Senior Reporter Beryl Lipton will investigate city contracts, requests for proposals, and in-house development of these systems of governance to build an open, searchable database of how these technologies are in use.
We’ll be looking at the data going into these algorithms, the models they use, the outcomes they produce, and the policies dictating how these tools are being integrated into our current systems.
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The largest city in the country seemed ready to create a framework to follow. But the final NYC Automated Decision Systems Task Force report, released last month, concluded that quick answers wouldn’t be available for addressing questions of fairness and accountability, even when trying to define ADS itself.
An interim report released earlier this month by the National Security Commission on Artificial Intelligence says the U.S. will lose important advantages in defense, human resources, and the economy if it doesn’t cooperate with industry and academia to prioritize progress in AI research and development.
“It’s PredPol, and it’s going to reduce crime”: Agencies take algorithmic effectiveness on faith, with few checks in place
Law enforcement agencies nationwide are using predictive policing software, yet almost none of their users, past or present, have clear measures for how effective or accurate they are.