Let’s start by discussing what this name change is not about. We did not get sold or acquired. We did not change markets. We are not running away from the facial recognition space.

What this name change is about is bringing our brand in line with our expanded vision and the markets we serve. Over the last seven years, we were focused on helping modern enterprises better protect themselves from known security threats by leveraging facial recognition and Visual AI technologies. The goal was to transform CCTV cameras into proactive security solutions. But, increasingly companies are looking to protect customers, guests, and employees from a variety of threats and provide a higher level of safety and security.

Physical Threats Go Hand-In-Hand with Cyber Attacks

Cybersecurity attacks are becoming more sophisticated every day, with attackers able to hack, eavesdrop, spoof, and socially engineer their way into valuable corporate and customer data. With the average breach costing $3.62 million in damage, it’s no wonder that global enterprises are scrambling to secure their networks and prevent attackers from gaining access to their digital assets. Add to this ransomware attacks which have already seen a 102% increase in the first half of 2021(compared to the beginning of last year, according to a report from cybersecurity firm Check Point Software).

While digital hacking incidents are on the rise, many IT professionals have lost focus on the tried-and-true method of attacking physical security. In targeted hits, attackers are targeting physical threat vectors in order to bypass digital controls, or even vice-versa. If you’re putting most (or all) of your eggs into the cyber basket, criminals will often resort to the old-fashioned break-and-enter and then attack the system from inside, completely bypassing traditional network security.

AnyVision is now Oosto.
Read the Press Release

How Can Oosto Make the World a Safer Place?

Well, it still starts with facial recognition which we use to identify known security threats from watchlists. We leverage ethical AI and video analytics to match people that are captured by cameras to persons of interest in real-time, even when they’re in crowds, not looking directly at the camera, or obscured by other people.

But, the possibilities are much greater especially if you’re trying to protect your customers, guests and employees from a myriad of threats. That’s why we will be investing in new technologies that help security professionals protect their premises, including:

• Object Recognition: The ability to detect vehicles, weapons, and even unattended luggage from live video footage.
• Body Recognition: Full body detectors which combine face and body poses help us track individuals as they traverse your property, even if they are walking away from a camera. This can even help identify when someone has fallen down and needs medical assistance.
• Aggression Detection: 3D reconstruction of human faces can start to tap into a person’s emotional state and can flag security if a person is under duress or potentially in medical jeopardy.
• Age Estimation: Advanced algorithms can start to automatically label a human face from video footage with an approximate age group (e.g., actual age, appearance age, perceived age, or estimated age). In retail use cases, this type of analytics can provide a better assessment of customer demographics.
• Touchless Access Control: Oosto will continue investing in touchless technologies that limit (or eliminate) the need to touch physical surfaces which can help spread germs and disease.

Why Oosto?

As we discovered, changing your company name is not for the faint of heart. We literally explored more than 300 names before settling on “Oosto.”  So, what does it mean?

Absolutely nothing!

It’s a name that doesn’t have any meaning in the English language. We liked it because it was short, fun to say, and easy to pronounce.  It’s a purely invented name, but it’s a name that will allow us to recreate a fresh, authentic brand and reinvent a category. Instead of just focusing on security use cases, Oosto is raising its gaze to protect the people that propel your business — customers, guests, and your own employees.

Commitment to Ethical AI & Recognition

Facial recognition has captured today’s headlines, raising many important questions about its accuracy and ethical use. These concerns have even led to blanket bans on use of the technology in several U.S. and European jurisdictions, without regard to the purpose or the benefits of specific applications.

There is a clear need for steps to build public trust without eliminating the crucial benefits the technology can provide. Oosto will lead the way in ethical recognition, but we can’t do this by ourselves  — it’s about educating the market, the press, and everyday consumers.

That’s why we’re teaming up with Carnegie Mellon University’s CyLab Biometric Research Center which will focus on early-stage research in object, body, and behavior recognition. This team is helping us explore new safety related use cases and ensure that the technology is used to better protect all of us from a growing and varied security threats from school shooters to touch-based transmissions.

“The realm of object, body, and behavioral recognition research has largely been untapped in a number of commercial markets,” said CMU’s Professor Marios Savvides. “Sadly, most security alerts happen too late to be actionable. We want to provide solutions that provide actionable intelligence in real-time whether that’s alerting medical staff when someone has fallen or identifying weapons on school grounds. I’m genuinely excited to jointly explore and invent AI-based solutions that help make this a safer planet.”

We will also partner with industry leaders, thought leaders and academic institutions to publish best practices in ethical facial recognition. This includes explaining how facial (and other types of) recognition work and how the algorithms were developed, providing levels of transparency that historically have been lacking.

But, it also is about imparting guidance on how these solutions should be deployed and used. It’s about providing clear notification to users before they encounter a camera’s visual field to capture biometric data and about disclosing any practices that link users’ biometric data to information from third parties or from publicly available sources.

With the introduction of every new technology, there is an inherent opportunity to gain or lose stakeholders’ trust. Unsurprisingly, most new technologies are met with mistrust (e.g., DNA testing, robotics, biometrics) — and much of this mistrust is well founded. Just witness the number of security hacks, inappropriate or illegal surveillance, misuse of personal data, spread of misinformation, algorithmic bias, and lack of transparency. Oosto is committed to harnessing the power of ethical AI for good and firmly believes that  the benefits can far exceed the costs  — if the technology is developed, deployed and used ethically.

The world is increasingly dangerous. We want to make it a safer place.

Welcome to the Oosto Revolution!

The post Mucho Gusto, Oosto! appeared first on Oosto.

Challenge 1

Knowing Who the Bad Actors Are

Preventing card counting, cheating, or hacking is hard. Being able to identify who attempted to or successfully targeted your casino is the first step in preventing these types of occurrences from happening. An advantage player can cost a casino tens of thousands of dollars in payouts, so it’s important to ensure they are identified in the facility before they can do any harm.

Challenge 2

Establishing Proper Communication Channels Between Security Teams

In a world where time is of the essence, a lack of direct information sharing from surveillance to security can lead to extraordinary losses for a casino. The surveillance team is in the control room and is responsible for identifying threats before they occur, but it’s very difficult for a human to identify every person that enters the facility across all cameras and properly communicate these findings with the security team. This constant need for over-communication results in operational friction and leads to security procedures that take more time, require more people, and work less efficiently.

Challenge 3

Protecting Sensitive Areas from Unauthorized Individuals

There may be areas of your facility, such as the bank vault or the control room, that are extremely sensitive and should only be accessed by specific personnel or employees of the casino. Security must be alerted right away if a non-authorized individual enters – or even attempts to enter – these areas.

Challenge 4

Preventing Self Excluders from Entering the Casino

While the impact can vary depending on local laws, it’s safe to say that allowing self-excluders to gamble in your casino can create significant liability and costs for your casino.

Challenge 5

Eliminating Violence, Loitering & Solicitation

Local offenders are nothing new for casinos, yet their continued presence puts a tremendous amount of pressure and stress on security personnel whose job is to ensure guests feel safe and protected without disrupting their experience on the casino floor or surrounding property.

Challenge 6

Creating Superior Experiences for Visitors

We all know the competition is fierce these days. Gamblers and slot players will gravitate to casinos that offer perks and provide the most enhanced gambling experiences. Being frequently asked to show ID, requiring membership and VIP key cards to keep track of points, and seeing dozens of security personnel at every station tends to worsen the ambiance of a casino.

Challenge 7

Adhering to COVID Regulations & Helping Guests Feel Safe

Wearing a mask and social distancing are important measures to reduce contamination. Having the ability to ensure guests are keeping their masks on is crucial to ensuring the safety of guests. However, simply issuing mask mandates and “Stay 6 Feet Apart Signs” aren’t enough when operating a casino that hosts hundreds of people at a time. Being able to track who was contaminated and trace who they were in contact with can help your casinos limit exposure, keep employees and visitors safe, and comply with ever-changing COVID-19 quarantine regulations. How AnyVision can help:

Using Access Point AI to Solve These Challenges

Access Point AI leverages state-of-the-art computer vision technology to help protect an organization’s physical access points. By identifying both authorized personnel and persons of interest in real-time — whether VIPs or bad actors — modern enterprises can layer in additional protection & operational insights to improve the customer experience. More specifically, here’s what Access Point AI can do:

• Allow you to receive real-time alerts whenever a bad actor or self-excluder enters your casino, non-authorized individual attempts to access a secured area, or a visitor removes his or her mask while indoors.
• Seamlessly and cost-effectively offer entry and benefits to visitors without requiring them to use key cards, membership chips, or any other physical device.
• Communicate efficiently and keep surveillance and security team members up-to-speed on everything that goes on “on the floor” in real-time.
• And so much more.
  
  

Reduce your operational overhead, utilize a single platform for all your security needs, and streamline your casino’s operational success by taking advantage of new recognition technology that handles the hard work for you.

The post 7 Challenges Casinos Need To Overcome To Stay Ahead Of The Game appeared first on Oosto.

Myth 1: Facial recognition software can identify everyone

You go to your local drug store, and as you’re in line to pay with your new shampoo bottle in hand, you see this sign above the cash register that you’d never noticed before: Your mind starts racing. Does this store know my name? Do they know how often I come here? The answer is no. Unless you’ve opted yourself into a facial recognition database, or have been added as part of a security watchlist as a “persons of interest,” then you cannot be identified through facial recognition. That’s because facial recognition algorithms depend on matching faces against other faces in a database: If there’s no match, then your face cannot be identified and is therefore ignored. Now you may be wondering who qualifies as a person of interest? In accordance with local biometric security regulations, anyone known as a threat can be added to a watchlist. This list is vital to security teams and their mission to protect people and spaces, as the teams are instantaneously alerted when these threats enter the store or another commercial space. Known threats can take many forms, such as:

1. An ex-employee who makes violent threats against their former co-workers
2. An abusive parent who shows up at school during the day
3. A convicted criminal (e.g., shoplifter)  
4. A hooligan who has instigated fights and physical violence in the stands
5. Gamblers identified as “self-excluders” who are banned from casinos because of their gambling addiction

So you can leave your local drugstore with peace of mind. Because you’re not a threat, and because you’ve never opted into their database, the facial recognition engine doesn’t know who you are. Further, you now feel more secure because the store’s security team is automatically alerted when known threats enter the premises who can potentially harm you or steal from the retailer or commercial enterprise.

Myth 2: Facial recognition poses a major privacy risk

Contrary to the mainstream narrative, facial identification data is more secure than other biometric unique identifiers–such as fingerprints—as well as non-biometric identifiers such as Social Security Numbers or alphanumeric passwords.

This is because facial recognition engines, or neural nets, work by translating digital images of faces into long strings of 250 or so random numbers and letters. So while a facial recognition system appears to be comparing a face seen on a camera to an image saved in a database, it’s actually comparing a new string of numbers and letters to a database of known numbers and letters. No descriptive data on the face itself is stored in the database. And all of this information is encrypted–further protecting it from prying eyes.

If there’s a data breach, the hacker will be left with these sequences of numbers and letters, as well as names–not a set of facial images. This data is practically impossible to reverse engineer back into an image, and because the neural nets that create these sequences are proprietary, the data would hold virtually zero commercial value.

Some facial recognition software, including ours, also include built-in privacy features such as GDPR mode (blurs faces of non-watchlist detections) and privacy mode (discards all face detections of non-enrolled individuals). Together, these two advanced privacy features ensure that:

1. Only data of known threats are stored and personal data of all other detections are deleted
2. System operators can only view detections of known individuals on a watchlist.  This means that if you’re not on a watchlist, then your image and its associated data will never be visible to another human

On a more abstract level, facial recognition protects privacy by largely eliminating the need for manual investigations that invade privacy.

Let’s compare the workflows of two retail store security teams—one that doesn’t use facial recognition technology and another that does.

In both cases, the teams are on the lookout for a white man in his late 40’s who recently shoplifted $2 thousand worth of goods. The team has an image of the individual’s face.

Security Team 1 Workflow (CCTV cameras in use with no facial recognition)

1. A white male who appears to be in his late 40’s enters the store
2. The security guard is put on high alert. Although the guard had seen an image of the person’s face, there’s a list of 100 other faces he needs to be on the lookout for, and it’s easy to forget what a specific face looks like. It’s better for him to play it safe and keep this man on his radar than for him to ignore the suspect. The guard secretly watches the alleged suspect and tracks his movements throughout the store

This individual’s privacy has been violated, as his behavior has been watched without his consent. Security Team 2 Workflow (with AnyVision facial recognition technology)

1. The white male in his late 40’s enters the store.
2. The security guard does not get an automatic alert informing him that a person of interest has entered the store, meaning this man does not pose a threat. The security guard is not on high alert and does not track this individual’s movements throughout the premises.

This individual’s privacy has not been violated.

Myth 3: Facial recognition software is inherently biased against people of color

A number of recent news articles including this one from Wired make the case that facial recognition is inherently racist because, in some instances, they are less accurate at identifying people with darker skin tones. They cite an outdated statistic that black women are five times more likely than white men to be misidentified by facial recognition algorithms. While we recognize that some algorithms show unacceptable levels of racial bias, a deeper look reveals that market-leading algorithms, including ours, are far less prone to this bias, and in fact can prevent bias in security settings. The following four points dispel the myth that facial recognition software is inherently racist.

1.  A recent study performed by NIST, the National Institute of Standards and Technology, looked at the top facial recognition algorithms in the world and found “no good evidence for a difference in the face detection or failure-to-enroll rate between the African-American and Caucasian cohorts.” 
2. Facial recognition accuracy, as a whole, is significantly improving with time. As of April 2020, the top facial identification algorithms had an error rate of just 0.08%, compared to 4.1% in 2014. This improvement was uniform across all races.
3. AnyVision held the Fair Face Recognition Workshop and Challenge in late 2020, which evaluated the accuracy and bias of facial recognition algorithms with regards to gender and race on 1:1 face verification. The challenge found that the top-10 facial recognition teams exceeded 99.9% accuracy and were “able to minimize bias to the point where it was almost negligible.”
4. Facial recognition, by its very nature, is intended to minimize racial bias by taking much of the guesswork and “gut feeling” out of security operations. Without the aid of facial recognition, security teams may spend their time stalking and investigating individuals who appear to be “suspicious.” Unfortunately, there is often bias by the security guards themselves when it comes to determining which individuals are deemed suspicious.

With facial recognition technology, there simply isn’t room for this sort of bias. An algorithm has a watchlist of faces, and when there’s the match from a live camera feed, an alert is created. No judgment calls on who might look suspicious come into play.

Myth 4: Facial recognition is only used for security purposes

While the watchlist alerting use case for facial recognition is the most easy to understand, facial recognition technology can be used to enhance the wellbeing of society in a variety of different ways, including:

1. Recognizing VIPs at sporting events, casinos, and other events. This allows customer service teams to immediately approach VIPs with their favorite drink or snack in hand, leading to greater customer loyalty
2. Reuniting lost or kidnapped individuals with their families. In 2020, a middle-aged man who was abducted as a toddler was reunited with his family after 32 years with the help of facial recognition technology. 
3. Diagnosing diseases that cause changes in facial appearance. Researchers with the National Human Genome Research Institute were able to use facial recognition to accurately detect 96.6% of cases of DiGeorge syndrome, a rare genetic disease that often goes undetected for years
4. Tracking time and attendance for individuals at school & work. Utilizing facial recognition for these tasks mitigates the risk of time theft and buddy punching, and ensures students and workers are securely in the locations where they say they are when they’re supposed to be there.
5. Validating identity at airports and ATMs. Facial recognition technology can be used to instantaneously make sure that people are who they say they are, allowing people to board flights and withdraw cash in a more efficient and secure manner.

Myth 5: Americans want to severely limit the use of facial recognition

Despite the barrage of negative media stories about facial recognition technology, Americans largely support its use, especially with regards to security applications. Recently, the Center for Data Innovation surveyed 3,151 US adults, and their findings severely cut against common perception.

•  Only 26% of Americans think the government should strictly curb the use of facial recognition
• Just 18% of Americans think the government should strictly limit facial recognition usage if it comes at the expense of public safety
• Only 22% of Americans agree that the government should forbid use of facial recognition in retail stores if it can be used to reduce shoplifting
• Only 24% of Americans disagreed with the statement that police departments should be allowed to use facial recognition technology help find suspects if the software is accurate 90% of the time 

A different survey conducted by Schoen Cooperman Research amongst 1000 interviews also found that Americans have a more positive view of facial recognition than the media leads you to believe. Here are some of the key results from their 2020 survey:

• Nearly 60% of Americans have a favorable view toward facial recognition technology
• 70% of Americans believe facial recognition technology is accurate in identifying people of all races and ethnicities
• 70% of Americans support the use of Facial Recognition in office buildings
• 66% of Americans believe facial recognition searches by investigators are non-invasive and appropriate

Conclusion

Facial recognition is an extremely promising tool that the American public largely misunderstands. While there certainly has been some misuse of the technology, we believe they’re outweighed by positive outcomes–mainly identifying violent criminals before they cause harm, securing vulnerable spaces, and greatly improving the overall effectiveness of security & access control teams. Further, the responsible use of facial recognition:

• Captures the data of known threats, not common citizens
• Provides organizations one of the most secure sources of identifying data possible
• Prevents bias, doesn’t increase bias

Of course, it’s imperative that commercial entities and government bodies alike use this technology ethically. And we’ve provided guidance on how to do so here. We think the tide is turning with regards to facial recognition’s perception, as recent polls show its growing support. But even so, we must continue the effort to provide a balanced view of this technology and work to understand how and when to harness its power to protect employees, customers, and profits.

The post Mythbusting Facial Recognition: Separating Fact From Fiction appeared first on Oosto.

AnyVision is a world-leading developer of visual AI platforms. Our solutions are built to function on any sensor, with any resolution and are proven to operate in real-time and real-world scenarios with unmatched accuracy, performance and privacy protection. We bring together the best and brightest minds in AI, deep learning and computer vision to make the world a safer, more intuitive and more connected place. That’s why we’ve partnered with AWS, whose best-in-class managed services enable AnyVision to eliminate limitations and benefit from top security, flexibility and scalability, helping us ensure our cutting-edge visual AI platform is available to you anytime, anywhere, with no downtime. Using AnyVision and AWS together, your system can easily adapt to changing technical and business conditions across every use case.

Customer Stories

One of the largest supermarket chains in Europe leverages AnyVision’s AWS-backed Watchlist Alerting platform to protect employees from violence and stop theft.

The first digital-only bank in a major middle-eastern country relies on AWS and AnyVision’s Remote Authentication platform to securely onboard new customers – and keep them there – with a safe and seamless user experience.

For more information on these use cases, or to receive a personalized demo, feel free to contact us using the form below.

The post Our Solutions for Businesses Working with Amazon Web Services appeared first on Oosto.

As they embark on the reentry phase and step into what many are calling the “next normal,” leaders across every industry are looking for ways to elevate trust by managing health risks and implementing the right processes and procedures to ensure safe back-to-work conditions, where employees feel informed, confident and productive.

Computer vision technology can help turn these criteria into a working reality.

The AnyVision team has been on the front-lines with our customers since the pandemic began. Over the last few months, we’ve had multiple conversations with business owners across many verticals and we’ve compiled a list of actionable steps these organizations are taking to reopen safely.

1/Minimize Surface Contamination
Surface contamination is one of the most common ways to spread infection, especially in high traffic areas. While placing hand sanitizers all over the office is certainly necessary nowadays in any workplace, this should be coupled with an aim to minimize surface contact.

2/Encourage Physical Distancing
We know that maintaining social distance is key to defeating the virus. This might seem simple, but because human beings are social by nature, enforcing distance is extremely difficult.Try to monitor high traffic spaces at peak socialization hours, like the kitchen during coffee breaks and lunch time.

3/Provide Easy Access to Remote Services
A good rule of thumb for returning to work is that whatever can be done remotely, should be done remotely. This helps minimize the number of people coming through the facility. The more flexibility people have between physical and online services, the lower the risk of overcrowding. Nevertheless, to comply with strict privacy regulations and to keep your sensitive information safe, you must have a secure way to authenticate your audience. Choosing a privacy-conscious and accurate digital authentication provider is critical to accomplishing flexible accessibility without sacrificing security.

4/Divide and Conquer
It is recommended that workforces separate employees into teams, or capsules, with staggered schedules. For example, if you divide your team in half and configure workplace access so that the teams never come into contact with one another, risk of exposure and viral spread is significantly reduced. If an outbreak does occur within a team or pod, not everyone will have been exposed.

5/Managing Contractors and Visitors
It’s important to be aware of everyone in your space – including any contractors and visitors who enter your facility – and understand who they’ve been in contact with. Accurate contact tracing is critical to ensuring you can not only manage a contamination scenario but also prevent a full lockdown by informing and isolating only those who have been exposed – while keeping all other operations running.

Unfortunately, these 5 measures require hours of manpower to implement efficiently.

That’s why our customers carefully considered and ultimately chose to implement AI visual intelligence – a powerful and critical tool that’s become instrumental in helping organizations overcome these challenges.

Through our unified visual intelligence platform, AnyVision offers four critical capabilities that are helping companies rethink safety and reimagine the way people access physical spaces and virtual services:

• Watchlist Alerting: Receive instant recognition notifications on any device based on the detection of known individuals in real-time or in historical footage
• Contact Tracing: Use historical footage to trace a known carrier and understand in real-time who they’ve come in contact with (and for how long) so that isolation decisions can be made
• Touchless Access Control: Create safe, seamless entry experiences with face recognition to provide contactless access that’s easy to customize by teams and zones
• Remote Authentication: Easily onboard and authenticate users, creating a frictionless and secure experience through an elegant and quick-to-deploy mobile SDK

COVID-19 and its impact on the global economy have intensified the speed at which businesses must adapt and respond to disruption. What we’ve heard from our customers around the world is that it also offers a unique opportunity for organizations to reimagine the workplace by creating better, faster and safer experiences for their onsite and virtual workforces – and in the process, build deeper trust and purpose for the long-term.

If you want to learn more about how other companies are preparing to reopen their operations, or need help planning for your organization’s return to work, reach out to us using the form below. We’re here for you.

The post Getting Back To Work Safely appeared first on Oosto.

It seems fitting to launch a video today that reflects on past challenges the world has faced that have made the world safer, stronger, and more connected by how we’ve overcome them.

AnyVision has invested a great deal of thought into our purpose as a company and how our technology can best serve humanity. A few long months ago, our vision was to boldly and aggressively apply our visual intelligence technology as far and wide as possible – and as quickly as possible – to make AI accessible to the world.

The pandemic has compelled us to reconsider how and where we can best serve our customers and humanity, and we have aligned our business around three core capabilities to enhance safety now and in the future:

Touchless access control, which eliminates the need for contact at secure points of entry by using face recognition to open doors, turnstiles and gates for authorized people.

Automated watchlist alerting, which protects perimeters and interiors and provides contact tracing by identifying persons of interest and the people with whom they have had contact.

Remote authentication and verification, which reduces digital fraud and increases the security of services delivered to personal devices by using face recognition to onboard and authenticate customers.

On Monday, all of us at AnyVision will take a moment to remember the people who have lost or dedicated their lives to the protection of others, and on this Memorial Day we will include in our thoughts the many people on the front lines of this crisis who are working to overcome it. We thank everyone who has done their part, and we have faith that the same courage and collaboration the world has mustered in past challenges will serve us in this one.

The post Why We Do What We Do appeared first on Oosto.

• How can our technology reduce the spread of the virus?
• How can our technology mitigate risk during economic stress?
• How can our technology help people safely get the services they need?

AnyVision has a big vision for how it can serve the world. We see limitless potential for how and where our AI-driven computer vision technology can be deployed to make the world a more seamless, intuitive and connected place. Like many businesses, the pandemic has forced us to rethink everything: the trajectory of our growth, the application of our technology, and how we serve the world. The new and uncertain reality we find ourselves in has compelled us to focus on doing our part to make it safer for the world to reopen and safer to stay open.

We are dedicating our visual intelligence research, expertise and core technology to enhancing safety. Our visual intelligence products enhance safety in three ways:

• Allow people to access controlled spaces without the need to touch surfaces
• Protect people and property by identifying threats beyond human detection ability
• Make it safer for businesses to provide services through customer devices

We’ve published a white paper that defines these critical capabilities, and we provide a webinar to bring them to life in order to help spread practical knowledge on how visual intelligence supports global efforts to enhance safety.

Computer vision, the most powerful application of AI, has had a controversial past. As with every breakthrough technology, computer vision has been met with equal parts fear, curiosity and excitement. The ethics and value of every technology are judged by how it is applied, and the world has an opportunity – a mandate – to rapidly apply computer vision in ways that preserve privacy while making people safer. We see parallels in medicine: the world has unified to rapidly research, develop and deploy new medical technology in order to save lives. This sense of focus, urgency and collaboration has prevailed over historical bureaucracy, national borders and partisan lines.

Just as the medical community has optimized for speed to save lives, every organization that has employees and customers must rapidly adopt new technologies to protect lives. The focused use of facial recognition is now critical to reducing the need to touch surfaces to gain access to controlled spaces, to detecting individuals who further threaten the safety of people and property, and to reducing potential fraud in digital services. This global crisis must and will accelerate the adoption of a variety of technologies, and it is our mission to provide ethical, unbiased and battle-proven visual intelligence solutions to every organization working to return the world to safety.

The post Returning the World to Safety Through Visual Intelligence appeared first on Oosto.

Privacy

Privacy is of the utmost importance to AnyVision. Our focus on privacy protection is instrumental to both our business strategy and our own standard of ethics.

AnyVision does not collect or share user data. In fact, we don’t even capture images. The data that we capture is rendered using mathematical vectors that act as secure cryptography, preventing identity hacking even if data is stolen.

In order to provide our clients with the necessary tools to meet local and regulatory privacy requirements, we’ve designed several features that:

• Allow the application of default privacy settings, like face-blurring and privacy mode, which ignore unknown individuals
• Allow only the collection of data that is strictly necessary for the purposes of data processing (data minimization)
• Allow customers to automatically and/or selectively clear data from an active database at the end of a certain period, or to easily delete unused data

These privacy protections are a significant leap forward against the backdrop of an estimated 600 million existing video cameras blindly recording and storing every move a person makes in cities across the globe

Ethics

We recognize that such powerful technology has the potential to be misused if placed in the wrong hands, and that we have an inherent responsibility to ensure our technology and products are used properly. As stated in our end-user license agreement, all customers are prohibited from using the technology for inappropriate, improper or unlawful purposes.

Additionally, we will soon announce an AI Ethics Advisory Board comprised of external experts both inside and outside of our field that will:

• Collaboratively help establish AnyVision’s AI Ethics Guiding Principles, and serve as a third-party check and balance to ensure adoption and adherence
• Guide AnyVision through the challenges that arise as part of our work and business
• Contribute to public discussion around the topic by exchanging ideas and raising awareness of potential challenges
• Advise on fair and responsible development and use of the technology

At Border Crossings

Much has been made publicly regarding facial recognition at border crossings, with misleading information and suggestions of surveillance and human rights abuses.

In reality, AnyVision’s facial recognition systems at border crossings work in the same way and for the same purposes as they do in airports, for example. For commuters and others who want to simply cross country borders, facial recognition drastically decreases wait times at border crossings. The other advantage is that they provide an unbiased safeguard at the border to detect and deter persons who have committed unlawful activities.

Algorithmic Bias & Discrimination

We believe a truly effective solution is only as valuable as the design and training of its algorithms. We pay close attention to which data sets we use and how we annotate that data, utilizing scenarios as diverse as the world itself. We strive to train our algorithm with the most well-balanced data sets possible, enabling our technology to be agnostic to ethnicity, skin color and gender, in addition to functioning in occluded and low-lit environments.

Regulation

As mentioned before, powerful technology like facial recognition has the ability to be misused when guidelines are not put in place. We have invested millions of dollars to ensure our technology not only complies with, but exceeds, local laws and regulations concerning privacy (such as GDPR) and are in favor of regulation where none currently exists. We have supported the proposed facial recognition legislation in the U.S. Senate and will continue to advocate for regulations in geographies where we do business.

Nothing is more important to AnyVision than ensuring we are providing a truly beneficial technology without compromising on ethical practices. As we move forward, we will uphold these principles and pave the way for other industry players to follow.

The post Ethical and Responsible AI at AnyVision appeared first on Oosto.

AnyVision is in strong support of the bill, and we applaud the U.S. government for taking a proactive role in regulating facial recognition technology. Though it may seem strange for a technology company that focuses on facial recognition to support regulation in its own backyard, we believe that thoughtful consideration must be given to this important topic.

AnyVision’s technology is already compliant with what is being proposed in the U.S. Senate, as we do not collect or share user data. In fact, we don’t even capture images. The data we capture is rendered in the form of mathematical vectors that employ deep machine learning methods. These vectors act as unbreakable cryptography and prevent identity hacking, even if data is stolen.

But our technology does not just stop there. We are also compliant with the General Data Protection Regulation (GDPR) standards of the European Union since its inception in May of 2018. In order to provide our clients with the necessary tools to meet the GDPR requirements and to protect the rights of their data subjects, we implanted several features that are designed to:

1. Allow our clients to apply default privacy settings and to easily apply such settings as desired.
2. Allow our clients to collect only the data that is strictly necessary for the purposes of the processing (data minimization).
3. Allow our clients to automatically and selectively clear data from an active database at the end of a certain period, or to easily delete unused data.

Though the GDPR in the European Union is stricter than what the US bill is currently proposing, we will continue to ensure that personal data stays personal and is fully compliant with local laws and regulations.

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