In an editorial for Slate published Monday, renowned security researcher Bruce Schneier warned that AI models may enable a new era of mass spying, allowing companies and governments to automate the process of analyzing and summarizing large volumes of conversation data, fundamentally lowering barriers to spying activities that currently require human labor.
In the piece, Schneier notes that the existing landscape of electronic surveillance has already transformed the modern era, becoming the business model of the Internet, where our digital footprints are constantly tracked and analyzed for commercial reasons. Spying, by contrast, can take that kind of economically inspired monitoring to a completely new level:
“Spying and surveillance are different but related things,” Schneier writes. “If I hired a private detective to spy on you, that detective could hide a bug in your home or car, tap your phone, and listen to what you said. At the end, I would get a report of all the conversations you had and the contents of those conversations. If I hired that same private detective to put you under surveillance, I would get a different report: where you went, whom you talked to, what you purchased, what you did.”
Schneier says that current spying methods, like phone tapping or physical surveillance, are labor-intensive, but the advent of AI significantly reduces this constraint. Generative AI systems are increasingly adept at summarizing lengthy conversations and sifting through massive datasets to organize and extract relevant information. This capability, he argues, will not only make spying more accessible but also more comprehensive.
“This spying is not limited to conversations on our phones or computers,” Schneier writes. “Just as cameras everywhere fueled mass surveillance, microphones everywhere will fuel mass spying. Siri and Alexa and ‘Hey, Google’ are already always listening; the conversations just aren’t being saved yet.”
From action to intent
We’ve recently seen a movement from companies like Google and Microsoft to feed what users create through AI models for the purposes of assistance and analysis. Microsoft is also building AI copilots into Windows, which require remote cloud processing to work. That means private user data goes to a remote server where it is analyzed outside of user control. Even if run locally, sufficiently advanced AI models will likely “understand” the contents of your device, including image content.
