Considering Mass Surveillance

Cops Wanted to Keep Mass Surveillance App Secret; Privacy Advocates Refused

By Ars Technica, September 9, 2022  in CACM

Much is known about how the federal government leverages location data by serving warrants to major tech companies like Google or Facebook to investigate crime in America. However, much less is known about how location data influences state and local law enforcement investigations. It turns out that's because many local police agencies intentionally avoid mentioning the under-the-radar tech they use—sometimes without warrants—to monitor private citizens.

As one Maryland-based sergeant wrote in a department email, touting the benefit of "no court paperwork" before purchasing the software, "The success lies in the secrecy."

This week, an investigation from the Electronic Frontier Foundation and Associated Press—supported by the Pulitzer Center for Crisis Reporting—has made public what could be considered local police's best-kept secret. Their reporting revealed the potentially extreme extent of data surveillance of ordinary people being tracked and made vulnerable just for moving about small-town America....

It took the Electronic Frontier Foundation months and more than 100 public records requests to gather thousands of pages of evidence to compile a clear picture that shows how local law enforcement increasingly mines location data.... 

From Ars Technica  

EU and Copyrights

Had not heard of this particular topic. Of interest.

In the Electronic Frontier Foundation (EFF)  Been around a long time, a good follow.

The Final Version of the EU's Copyright Directive Is the Worst One Yet   By Cory Doctorow

Despite ringing denunciations from small EU tech businesses, giant EU entertainment companies, artists' groups, technical experts, and human rights experts, and the largest body of concerned citizens in EU history, the EU has concluded its "trilogues" on the new Copyright Directive, striking a deal that—amazingly—is worse than any in the Directive's sordid history.
Goodbye, protections for artists and scientists

The Copyright Directive was always a grab bag of updates to EU copyright rules—which are long overdue for an overhaul, given that it's been 18 years since the last set of rules were ratified. Some of its clauses gave artists and scientists much-needed protections: artists were to be protected from the worst ripoffs by entertainment companies, and scientists could use copyrighted works as raw material for various kinds of data analysis and scholarship.... "

How to Read a Privacy Policy

Thoughtful piece worth reading ...

How to read a privacy policy   By Ashley Carman    @ashleyrcarman  in TheVerge

We haven’t been able to avoid privacy policies in our post-GDPR world, but figuring out what these legal documents are trying to tell us isn’t easy. They’re typically filled with legalese and boring chatter about data and how it’s handled. I get why no one wants to spend time reading them.

So to save us all some effort, I called a couple lawyers — Nate Cardozo from the Electronic Frontier Foundation and Joseph Jerome from the Center for Democracy and Technology — to learn how they read and process tons of policies. They’ve given me a few tips on how we can essentially skim through a privacy policy while still learning something about how our data is handled. ..... " 

Tracking, Measuring AI Research

Very good effort.  Much more detail at the link.  Putting it on my alert list. From the EFF: Electronic Frontier Foundation,  which I have little watched lately.   Plus also see Algorithmia.

Measuring the Progress of AI Research

This pilot project collects problems and metrics/datasets from the AI research literature, and tracks progress on them.

You can use this Notebook to see how things are progressing in specific subfields or AI/ML as a whole, as a place to report new results you've obtained, as a place to look for problems that might benefit from having new datasets/metrics designed for them, or as a source to build on for data science projects.

At EFF, we're ultimately most interested in how this data can influence our understanding of the likely implications of AI. To begin with, we're focused on gathering it.

Original authors: Peter Eckersley and Yomna Nasser at EFF. Contact: ai-metrics@eff.org.

With contributions from: Gennie Gebhart and Owain Evans .... "