For Better or Worse, Algorithms Help Control Local Communities

Written by Beryl Lipton

What is the chance you, or your neighbor, will commit a crime? Should the government change a child’s bus route? Add more police to a neighborhood or take some away?

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.

Every day government decisions from bus routes to policing used to be based on limited information and human judgment. Governments now use the ability to collect and analyze hundreds of data points everyday to automate many of their decisions.

Does handing government decisions over to algorithms save time and money? Can algorithms be fairer or less biased than human decision making? Do they make us safer? Automation and artificial intelligence could improve the notorious inefficiencies of government, and it could exacerbate existing errors in the data being used to power it.

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.

They’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.

MuckRock and the Rutgers Institute for Information Policy & Law (RIIPL) have compiled a collection of algorithms used in communities across the country to automate government decision-making.

Go right to the database.

The partners have also compiled policies and other guiding documents local governments use to make room for the future use of algorithms. Find those as a project on DocumentCloud.

View policies on smart cities and technologies

These collections are a living resource and attempt to communally collect records and known instances of automated decision making in government.

How to use these resources

By collecting these records and knowledge in one place, we can save hundreds of hours in redundant work and effort, allow others to build on the research that’s already been done and encourage new investigations and calls for basic algorithmic accountability.

Database Fields_MuckRock

Each entry is specific to a particular implementation or pilot program we’ve learned about, either through our own reporting, previous reporting, or feedback from MuckRock users.

The partners, MuckRock and RRIIPL, are trying to capture as many of the following data points as possible.

Release by MuckRock:
Have a suggestion or know of an algorithmic development near you? Send it to or submit it via the form below.


See also:

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