Friday Squid Blogging: Climate Change Could be Good for Squid

Basically, they thrive in a high CO2 environment, because it doesn't bother them and makes their prey weaker.

As usual, you can also use this squid post to talk about the security stories in the news that I haven't covered.

Read my blog posting guidelines here.

Posted on June 14, 2019 at 4:41 PM27 Comments

Upcoming Speaking Engagements

This is a current list of where and when I am scheduled to speak:

The list is maintained on this page.

Posted on June 14, 2019 at 1:30 PM2 Comments

Computers and Video Surveillance

It used to be that surveillance cameras were passive. Maybe they just recorded, and no one looked at the video unless they needed to. Maybe a bored guard watched a dozen different screens, scanning for something interesting. In either case, the video was only stored for a few days because storage was expensive.

Increasingly, none of that is true. Recent developments in video analytics -- fueled by artificial intelligence techniques like machine learning -- enable computers to watch and understand surveillance videos with human-like discernment. Identification technologies make it easier to automatically figure out who is in the videos. And finally, the cameras themselves have become cheaper, more ubiquitous, and much better; cameras mounted on drones can effectively watch an entire city. Computers can watch all the video without human issues like distraction, fatigue, training, or needing to be paid. The result is a level of surveillance that was impossible just a few years ago.

An ACLU report published Thursday called "the Dawn of Robot Surveillance" says AI-aided video surveillance "won't just record us, but will also make judgments about us based on their understanding of our actions, emotions, skin color, clothing, voice, and more. These automated 'video analytics' technologies threaten to fundamentally change the nature of surveillance."

Let's take the technologies one at a time. First: video analytics. Computers are getting better at recognizing what's going on in a video. Detecting when a person or vehicle enters a forbidden area is easy. Modern systems can alarm when someone is walking in the wrong direction -- going in through an exit-only corridor, for example. They can count people or cars. They can detect when luggage is left unattended, or when previously unattended luggage is picked up and removed. They can detect when someone is loitering in an area, is lying down, or is running. Increasingly, they can detect particular actions by people. Amazon's cashier-less stores rely on video analytics to figure out when someone picks an item off a shelf and doesn't put it back.

More than identifying actions, video analytics allow computers to understand what's going on in a video: They can flag people based on their clothing or behavior, identify people's emotions through body language and behavior, and find people who are acting "unusual" based on everyone else around them. Those same Amazon in-store cameras can analyze customer sentiment. Other systems can describe what's happening in a video scene.

Computers can also identify people. AIs are getting better at identifying people in those videos. Facial recognition technology is improving all the time, made easier by the enormous stockpile of tagged photographs we give to Facebook and other social media sites, and the photos governments collect in the process of issuing ID cards and drivers licenses. The technology already exists to automatically identify everyone a camera "sees" in real time. Even without video identification, we can be identified by the unique information continuously broadcasted by the smartphones we carry with us everywhere, or by our laptops or Bluetooth-connected devices. Police have been tracking phones for years, and this practice can now be combined with video analytics.

Once a monitoring system identifies people, their data can be combined with other data, either collected or purchased: from cell phone records, GPS surveillance history, purchasing data, and so on. Social media companies like Facebook have spent years learning about our personalities and beliefs by what we post, comment on, and "like." This is "data inference," and when combined with video it offers a powerful window into people's behaviors and motivations.

Camera resolution is also improving. Gigapixel cameras as so good that they can capture individual faces and identify license places in photos taken miles away. "Wide-area surveillance" cameras can be mounted on airplanes and drones, and can operate continuously. On the ground, cameras can be hidden in street lights and other regular objects. In space, satellite cameras have also dramatically improved.

Data storage has become incredibly cheap, and cloud storage makes it all so easy. Video data can easily be saved for years, allowing computers to conduct all of this surveillance backwards in time.

In democratic countries, such surveillance is marketed as crime prevention -- or counterterrorism. In countries like China, it is blatantly used to suppress political activity and for social control. In all instances, it's being implemented without a lot of public debate by law-enforcement agencies and by corporations in public spaces they control.

This is bad, because ubiquitous surveillance will drastically change our relationship to society. We've never lived in this sort of world, even those of us who have lived through previous totalitarian regimes. The effects will be felt in many different areas. False positives­ -- when the surveillance system gets it wrong­ -- will lead to harassment and worse. Discrimination will become automated. Those who fall outside norms will be marginalized. And most importantly, the inability to live anonymously will have an enormous chilling effect on speech and behavior, which in turn will hobble society's ability to experiment and change. A recent ACLU report discusses these harms in more depth. While it's possible that some of this surveillance is worth the trade-offs, we as society need to deliberately and intelligently make decisions about it.

Some jurisdictions are starting to notice. Last month, San Francisco became the first city to ban facial recognition technology by police and other government agencies. A similar ban is being considered in Somerville, MA, and Oakland, CA. These are exceptions, and limited to the more liberal areas of the country.

We often believe that technological change is inevitable, and that there's nothing we can do to stop it -- or even to steer it. That's simply not true. We're led to believe this because we don't often see it, understand it, or have a say in how or when it is deployed. The problem is that technologies of cameras, resolution, machine learning, and artificial intelligence are complex and specialized.

Laws like what was just passed in San Francisco won't stop the development of these technologies, but they're not intended to. They're intended as pauses, so our policy making can catch up with technology. As a general rule, the US government tends to ignore technologies as they're being developed and deployed, so as not to stifle innovation. But as the rate of technological change increases, so does the unanticipated effects on our lives. Just as we've been surprised by the threats to democracy caused by surveillance capitalism, AI-enabled video surveillance will have similar surprising effects. Maybe a pause in our headlong deployment of these technologies will allow us the time to discuss what kind of society we want to live in, and then enact rules to bring that kind of society about.

This essay previously appeared on Vice Motherboard.

Posted on June 14, 2019 at 12:04 PM10 Comments

Video Surveillance by Computer

The ACLU's Jay Stanley has just published a fantastic report: "The Dawn of Robot Surveillance" (blog post here) Basically, it lays out a future of ubiquitous video cameras watched by increasingly sophisticated video analytics software, and discusses the potential harms to society.

I'm not going to excerpt a piece, because you really need to read the whole thing.

Posted on June 14, 2019 at 6:28 AM9 Comments

Rock-Paper-Scissors Robot

How in the world did I not know about this for three years?

Researchers at the University of Tokyo have developed a robot that always wins at rock-paper-scissors. It watches the human player's hand, figures out which finger position the human is about to deploy, and reacts quickly enough to always win.

EDITED TO ADD (6/13): Seems like this is even older -- from 2013.

Posted on June 12, 2019 at 6:22 AM19 Comments

Workshop on the Economics of Information Security

Last week, I hosted the eighteenth Workshop on the Economics of Information Security at Harvard. Ross Anderson liveblogged the talks.

Posted on June 11, 2019 at 6:17 AM4 Comments

Friday Squid Blogging: Possible New Squid Species

NOAA video.

As usual, you can also use this squid post to talk about the security stories in the news that I haven't covered.

Read my blog posting guidelines here.

Posted on June 7, 2019 at 4:18 PM96 Comments

iOS Shortcut for Recording the Police

"Hey Siri; I'm getting pulled over" can be a shortcut:

Once the shortcut is installed and configured, you just have to say, for example, "Hey Siri, I'm getting pulled over." Then the program pauses music you may be playing, turns down the brightness on the iPhone, and turns on "do not disturb" mode.

It also sends a quick text to a predetermined contact to tell them you've been pulled over, and it starts recording using the iPhone's front-facing camera. Once you've stopped recording, it can text or email the video to a different predetermined contact and save it to Dropbox.

Posted on June 7, 2019 at 6:24 AM30 Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.

Schneier on Security is a personal website. Opinions expressed are not necessarily those of IBM Resilient.