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Researchers Sue US Government Over Anti Hacking Law

by Bill

A law that was put in place to make hacking illegal decades ago may be preventing researchers from preventing algorithmic discrimination, and the researchers are fighting back. The law is known as the Computer Fraud and Abuse Act and it makes it illegal for anyone to scrape websites for data that is already available to the public or to sign up for a free user account to do so.

Researchers who focus on this type of discrimination, which is thought to be especially prevalent on job search sites and real estate sites, could get arrested and charged through this act, because they need to test these websites to see if discrimination is present in their algorithms. While most charges for violating a site’s terms of service bring on civil charges which usually have a financial penalty, this act is one of the few that could bring criminal charges, meaning jail time. On your first offense, you can get up to a year in prison, and a second offense will land you up to ten years in the clink.

Because of this, the researchers have filed a lawsuit against the US Department of Justice, because in their eyes, creating the fake profiles they need to use in order to ascertain the level of discrimination on certain websites falls under the free speech act of the first amendment. One of the researchers, Christopher Sandvig, says that “Being able to run socially beneficial studies like ours is at the heart of academic freedom.”

However, in the past, this law has been helpful in finding ways to prosecute online bullies who created fake online social media accounts in order to bully people, which often leads to hardship and even suicide. While this law could be positive in certain cases, it’s clear that researchers need to be able to access website in a way that will allow them to observe what is happening and prevent discrimination. It’s yet another round in the enduring debate about data security, privacy and our increasingly powerful ability to analyze massive data sets in ever decreasing amounts of time.

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