How many surveillance cameras do you pass when you walk down the street? Most of us don’t know and prefer not to think about it. We know that public and private entities, from social media sites like Facebook, to law enforcement agencies, are using facial recognition software. In most cases, we haven’t actively consented to this surveillance, and we don’t know what will be done with information – but it also seems like there’s not much we can do about it.
Enter artist Leo Selvaggio, who is interested in “increasing the amount of public discourse about surveillance and how it affects our behavior in public space.” Selvaggio has launched a venture called URME Surveillance, whose focus is “protecting the public from surveillance and creating a safe space to explore our digital identities.”
URME is doing this is in an unusual, and admittedly kind of unnerving way. The site provides masks, in the likeness of Selvaggio’s face, that you can wear in public to protect your own mug from ending up on file. These “Personal Surveillance Identity Prosthetics” are sold at cost – Selvaggio isn’t in it for the profits. There’s a $200 resin prosthetic, a set of 2D paper masks for large groups (protestors?), and a downloadable PDF paper mask that fits together like a 3D puzzle, giving the mask more dimension than the flat, 2D version.
“Our world is becoming increasingly surveilled. For example, Chicago has over 25,000 cameras networked to a single facial recognition hub,” explains the URME website. “We don’t believe you should be tracked just because you want to walk outside and you shouldn’t have to hide either. Instead, use one of our products to present an alternative identity when in public.”
Is this product a genuine solution to non-consensual surveillance? Or is it simply an artist’s attempt to make a statement? The 3D resin mask is fairly realistic, but with the wearer’s eyes peeking out of the mask’s holes, it’s creepy, to say the least.
While the mask may thwart surveillance cameras, it will probably attract attention from other people nearby – so perhaps anonymity isn’t the goal.
It’s more about making sure that your face doesn’t end up in a databank; or at the very least, inspiring conversation about the topic of public surveillance. Potential customers should also be advised that many states and cities have laws against wearing masks in public.
Regardless of the ultimate intention, the fact that Selvaggio is willing to sacrifice his own likeness to Big Brother means that he takes the issue seriously. Cameras linked to facial recognition software will identify and track Selvaggio, regardless of who is under the mask. URME has actually tested the product using Facebook’s “sophisticated” facial recognition software.
Selvaggio even acknowledges that people could use the mask to commit crimes, which could land him in hot water. However, he has “come to the conclusion that it is worth the risk if it creates public discourse around surveillance practices and how it affects us all.”
4 ways startups prove their investment in upcoming technology trends
(TECH NEWS) Want to see into the future? Just take a look at what technology the tech field is exploring and investing in today — that’s the stuff that will make up the world of tomorrow.
Big companies scout like for small ones that have proven ideas and prototypes, rather than take the initial risk on themselves. So startups have to stay ahead of technology by their very nature, in order to be stand-out candidates when selling their ideas to investors.
Innovation Leader, in partnership with KPMG LLP, recently conducted a study that sheds light onto the bleeding edge of tech: The technologies that the biggest companies are most interested in building right now.
The study asked its respondents to group 16 technologies into four categorical buckets, which Innovation Leader CEO Scott Kirsner refers to as “commitment level.”
The highest commitment level, “in-market or accelerating investment,” basically means that technology is already mainstream. For optimum tech-clairvoyance, keep your eyes on the technologies which land in the middle of the ranking.
“Investing or piloting” represents the second-highest commitment level – that means they have offerings that are approaching market-readiness.
The standout in this category is Advanced Analytics. That’s a pretty vague title, but it generally refers to the automated interpretation and prediction on data sets, and has overlap with Machine learning.
Wearables, on the other hand, are self explanatory. From smart watches to location trackers for children, these devices often pick up on input from the body, such heart rate.
The “Internet of Things” is finding new and improved ways to embed sensor and network capabilities into objects within the home, the workplace, and the world at large. (Hopefully that doesn’t mean anyone’s out there trying to reinvent Juicero, though.)
Collaboration tools and cloud computing also land on this list. That’s no shock, given the continuous pandemic.
The next tier is “learning and exploring”— that represents lower commitment, but a high level of curiosity. These technologies will take a longer time to become common, but only because they have an abundance of unexplored potential.
Blockchain was the highest ranked under this category. Not surprising, considering it’s the OG of making people go “wait, what?”
Augmented & virtual reality has been hyped up particularly hard recently and is in high demand (again, due to the pandemic forcing us to seek new ways to interact without human contact.)
And notably, AI & machine learning appears on rankings for both second and third commitment levels, indicating it’s possibly in transition between these categories.
The lowest level is “not exploring or investing,” which represents little to no interest.
Quantum computing is the standout selection for this category of technology. But there’s reason to believe that it, too, is just waiting for the right breakthroughs to happen.
Internet of Things and deep learning: How your devices are getting smarter
(TECH NEWS) The latest neural network from Massachusetts Institute of Technology shows a great bound forward for deep learning and the “Internet of Things.”
The deep learning that modifies your social media and gives you Google search results is coming to your thermostat.
Researchers at the Massachusetts Institute of Technology (MIT) have developed a deep learning system of neural networks that can be used in the “Internet of Things” (IoT). Named MCUNet, the system designs small neural networks that allow for previously unseen speed and accuracy for deep learning on IoT devices. Benefits of the system include energy savings and improved data security for devices.
Created in the early 1980s, the IoT is essentially a large group of everyday household objects that have become increasingly connected through the internet. They include smart fridges, wearable heart monitors, thermostats, and other “smart” devices. These gadgets run on microcontrollers, or computer chips with no processing system, that have very little processing power and memory. This has traditionally made it hard for deep learning to occur on IoT devices.
“How do we deploy neural nets directly on these tiny devices? It’s a new research area that’s getting very hot,” said Song Han, Assistant Professor of Computer Science at MIT who is a part of the project, “Companies like Google and ARM are all working in this direction.”
In order to achieve deep learning for IoT connected machines, Han’s group designed two specific components. The first is TinyEngine, an inference engine that directs resource management similar to an operating system would. The other is Tiny NAS, a neural architecture search algorithm. For those not well-versed in such technical terms, think of these things like a mini Windows 10 and machine learning for that smart fridge you own.
The results of these new components are promising. According to Han, MCUNet could become the new industry standard, stating that “It has huge potential.” He envisions the system has one that could help smartwatches not just monitor heartbeat and blood pressure but help analyze and explain to users what that means. It could also lead to making IoT devices far more secure than they are currently.
“A key advantage is preserving privacy,” says Han. “You don’t need to transmit the data to the cloud.”
It will still be a while until we see smart devices with deep learning capabilities, but it is all but inevitable at this point—the future we’ve all heard about is definitely on the horizon.
Google is giving back some privacy control? (You read that right)
(TECH NEWS) In a bizarre twist, Google is giving you the option to opt out of data collection – for real this time.
It’s strange to hear “Google” and “privacy” in the same sentence without “concerns” following along, yet here we are. In a twist that’s definitely not related to various controversies involving the tech company, Google is giving back some control over data sharing—even if it isn’t much.
Starting soon, you will be able to opt out of Google’s data-reliant “smart” features (Smart Compose and Smart Reply) across the G-Suite of pertinent products: Gmail, Chat, and Meet. Opting out would, in this case, prevent Google from using your data to formulate responses based on your previous activity; it would also turn off the “smart” features.
One might observe that users have had the option to turn off “smart” features before, but doing so didn’t disable Google’s data collection—just the features themselves. For Google to include the option to opt out of data collection completely is relatively unprecedented—and perhaps exactly what people have been clamoring for on the heels of recent lawsuits against the tech giant.
In addition to being able to close off “smart” features, Google will also allow you to opt out of data collection for things like the Google Assistant, Google Maps, and other Google-related services that lean into your Gmail Inbox, Meet, and Chat activity. Since Google knowing what your favorite restaurant is or when to recommend tickets to you can be unnerving, this is a welcome change of pace.
Keep in mind that opting out of data collection for “smart” features will automatically disable other “smart” options from Google, including those Assistant reminders and customized Maps. At the time of this writing, Google has made it clear that you can’t opt out of one and keep the other—while you can go back and toggle on data collection again, you won’t be able to use these features without Google analyzing your Meet, Chat, and Gmail contents and behavior.
It will be interesting to see what the short-term ramifications of this decision are. If Google stops collecting data for a small period of time at your request and then you turn back on the “smart” features that use said data, will the predictive text and suggestions suffer? Only time will tell. For now, keep an eye out for this updated privacy option—it should be rolling out in the next few weeks.
Business Finance2 weeks ago
7 ways spending habits have changed since COVID-19
Opinion Editorials2 weeks ago
4 simple tips to ease friction with your boss while working remotely
Opinion Editorials1 week ago
Improve UX design by tracking your users’ eye movements
Tech News2 weeks ago
Deepfakes of musicians raise all kinds of moral quandaries
Business News1 week ago
Movie theaters explore renting out their space to survive COVID
Business News1 week ago
Driverless delivery startup raises half a billion dollars to transport local goods
Tech News1 week ago
First wireless, now headphoneless headphones? Enter, Soundbeamer
Tech News1 week ago
Microsoft engineer *almost* gets away with $10 million