At Axon our mission is to protect life. We are out to make the world a safer place by solving big problems and taking on the public safety challenges of our time. Since our founding in 1993, we have invested significantly in devices and integrated software solutions to help public safety agencies make their communities safer. Today, more than 17,000 law enforcement agencies in 100+ countries around the world are part of the Axon network.

As a leader in building hardware and software solutions for public safety, Axon is now making considerable strides in the area of Artificial Intelligence (AI). In the Axon ecosystem of products, every offering works together as a connected network, which requires innovative technologies driven by user-focused design every step of the way. By owning and delivering a large portion of the value chain from leading-edge devices to cloud services, there are multiple opportunities for AI to add unique value to our public safety customers and the communities they serve.

Yasser M. Ibrahim, SVP of AI at Axon, explains, "There is a lot to accomplish. There are many areas to explore, and it is truly exciting if you’re a builder and really want to work in an area where there is considerable potential that hasn’t been fully realized yet."

When does an organization need to consider building a solution using AI as opposed to conventional Software Engineering?

The primary question an organization should examine while innovating in this area, is whether the customer problem they are trying to solve really requires an algorithmically and operationally complex approach like AI, instead of a relatively more wieldy technology. For starters, a solution built using AI doesn’t usually give a single concrete answer to a given question or query, instead it gives probabilities representing which set of answers are likely to be correct. Furthermore, this process is not bullet proof as it lacks immunity to producing false positives and even missing the correct answers altogether.

Sometimes the newest technological advancement isn’t the most effective or suitable solution. AI, while becoming an increasingly hot topic in tech and the media, isn’t always the best choice. Instead, innovators need to evaluate the most effective technology options without overcomplicating the development process. Sometimes, the smartest choice is based on tried and tested legacy technology.

Imagine a law enforcement agency needs a dashboard containing crime statistics in a given geographical area. We can provide these reports by utilizing conventional software, including databases and the appropriate query language, to calculate those crime analytics. This is a deterministic approach by definition and as such it would be counterproductive to use AI for the same exact purpose. However, an algorithmic approach would be called for in a more complicated case, such as when a law enforcement agency wants a tool to optimize the allocation of patrol officers over a given geographical area based on myriad set of factors like time of day, crime rate and personnel availability. In this case AI might be a potential candidate for a solution that is worthy of investigating.

To summarize: while conventional software, analytics and AI algorithms maybe overlapping, they all have different purposes, risks and associated development costs. Making it is essential to educate an organization on what AI is and what it isn’t.

Furthermore, AI is quite unsustainable in the long-term unless you can apply it in a responsible manner. Irresponsible AI which doesn’t take into account the impact on society, is easy to implement for small problems, but it’s not scalable. On the other hand, using science and engineering responsibly, although time consuming, provides a competitive advantage because people who ignore ethics will erode both trust and performance over time.


A commitment to innovation, positive impact, and community

Ethics-by-Design is an organizational approach to the responsible use of technology, and as such there needs to be deliberate steps organizations take to implement it. This development cannot be done in a vacuum; its social impact ought to be considered from the beginning. Organizations that use technology ethically consider not only the benefits but also the potential harm to society at every stage of their decision-making process, which is especially important for Axon and how we serve our public safety customers.


“Before you start with new technologies, you have to define how it may impact society.”

To define this impact, Axon has an independent AI Ethics Board that provides expert advice and guidance during product conception and subsequent development. The Ethics Board has developed a framework for analyzing the ethical costs and benefits associated with new products. This is an important framework within Axon, even for products that do not use AI.

To create with an Ethics-by-Design framework, it is important that the team composition reflect the diversity we see in the world. A diverse, and importantly, inclusive team is required so you can apply a spectrum of opinions, genders, ethnicities, income levels and skill sets to a challenge. This allows the team to consider all angles when working with new ideas and products in a way that truly creates groundbreaking technology.

A diverse team that espouses and builds upon those ethical framework guidelines leads to innovation focusing more on how products can positively impact a community at large. With AI employed into the right product, in the right way and at the right time, it can become a great catalyst that helps address tangible societal issues.

Innovation starts with building a world-class AI team

As we grow our AI team, Axon aims to attract a diverse group of talented engineers and scientists at all levels, who are as excited as we are about our Ethics-by-Design ethos. A great candidate for our team starts with the eagerness to understand the customer problem as they responsibly develop an AI solution to address it. We seek candidates who are interested in developing something meaningful and impactful, such as how to operationalize AI in a way that preserves privacy, maintains fairness and avoids bias. It’s not enough to implement the latest and greatest approaches in AI when building new products; a successful candidate has to show they are able to take these ethical considerations into account and address the corresponding design challenges at scale with the team.

At Axon, we focus intently on real problems while developing end-to-end solutions. This requires a multidisciplinary team with the right balance of AI Scientists, ML Engineers, Software Engineers and Product/Program Managers. As the team evolves, we’re looking to include subject matter experts in every AI modality to build proprietary models that include audio, video, text and images for our products.

In addition to building the right team, it is also imperative to keep pace with the ever-changing AI advancements. Still, as we add in novel AI layers to some of our products, we do so with the customer and impact to community in mind. Keeping Ethics-by-Design in the foreground of all we do helps Axon get closer to its goal of providing more effective tools in service of our mission to Protect Life and Preserve the Truth.


Yasser Ibrahim is Axon’s SVP of Artificial Intelligence and leads Axon’s AI Team from the Seattle office. Prior to joining Axon, Yasser served as Amazon’s head of distributed machine learning at Alexa AI. He led applied science and ML engineering teams developing state-of-the-art deep learning frameworks and distributed algorithms powering Alexa’s large scale ML experimentation and production platforms. He also led multidisciplinary engineering and science teams building computer vision systems and computational imaging algorithms for Amazon Go, the world’s first “Just Walk Out” store and technology platform. At Microsoft, Mr. Ibrahim led computer vision system teams to deliver technologies such as Pixelsense, and previously developed flight control and autopilot systems for flight simulators at CAE Inc., in Montreal.


ARTICLE: AI Ethics - The Role of Responsible AI Within the Axon Ecosystem

The Role of Responsible AI Within the Axon Ecosystem

Axon and its Ethics Board will work with public safety thought leaders and diverse community leaders to develop a model framework for law enforcement agencies to responsibly and ethically deploy this technology consistent with the Ethics Board's guidance, which was set forth in their report published today.

"ALPR is an important tool for keeping communities safe as it can help apprehend criminals, find missing children, and recover stolen vehicles," says Axon CEO and founder, Rick Smith. "We do, however, recognize that there are legitimate concerns about privacy protections, constitutionality of search and data security issues that need to be addressed. We embrace that we have an ethical obligation to develop this technology thoughtfully and bring new privacy safeguards to the industry. While building ALPR, we'll be addressing items such as data retention and data ownership, creating an ethical framework to help prevent misuse of the technology."

Axon is leveraging the power of AI to significantly reduce the cost of ALPR systems, making it affordable for every patrol. Axon is simultaneously addressing industry short-comings to improve data security, transparency and privacy as declining costs enable more widespread use of the technology. Axon plans to work collaboratively with communities to better understand and implement controls such as maximum retention periods and transparency tools.

One recommendation in the Ethics Board's report calls for agency ownership and control over the captured license plate data, declaring that data should not be sold for commercial purposes. For years, Axon has protected digital evidence by maintaining a secure cloud-based system that allows agencies to control data, ensuring use only for public safety purposes. Consistent with the Ethics Board's recommendations, Axon will maintain that same high level of security and privacy standards with ALPR data.

"We have not, and will not ever sell public safety data. We believe the data is owned by public safety agencies and the communities they serve, and should not be resold to private entities whose interests may not be aligned with the public good," concluded Smith.

"The unregulated use of ALPRs has exposed millions of people subject to surveillance by law enforcement, and the danger to our basic civil rights is only increasing as the technology is becoming more common," says Ethics Board member Barry Friedman, founder of the Policing Project at the New York University School of Law and the Jacob D. Fuchsberg Professor of Law at New York University. "If government is going to continue to abdicate its responsibility to regulate this technology appropriately, and we hope it doesn't, it is incumbent on companies like Axon to ensure that ALPRs serve the communities who are subject to ALPR usage. This includes guardrails to ensure their use does not compromise civil liberties or worsen existing racial and socioeconomic disparities in the criminal justice system."

Axon Fleet 3 will use AI for ALPR to help reduce officer distraction. For example, when searching for stolen vehicles or criminals today, patrol officers manually look up vehicle license plates by typing into their computers. ALPR helps eliminate the need for typing while driving. Today, most agencies deploy ALPR via specialized vehicle units with plate recognition systems that cost tens of thousands of dollars in only a portion of the vehicle fleet. Axon Fleet 3 will integrate ALPR capability in the dashboard camera of every patrol vehicle, allowing agencies to deploy more coverage at a lower cost. Axon Fleet 3 will also enable Axon Aware real-time telemetry and video streaming capabilities and will be upgradeable to 5G to leverage low-latency connectivity for enhanced real-time services and direct video offload to the cloud.

Axon will be previewing Axon Fleet 3 at the 126th annual International Association of Chiefs of Police (IACP) conference, this week in Chicago at Axon's booth number 2211. There, Axon will be demonstrating enhanced 5G real-time services.

Axon is a global network of devices, apps, training and people that helps public safety personnel become smarter and safer. With a mission of protecting life, our technologies give customers the confidence, focus and time they need to protect their communities. Our products impact every aspect of a public safety officer's day-to-day experience.

We work hard for those who put themselves in harm's way for all of us. To date, there are more than 397,800 software seats booked on the Axon network around the world and more than 223,000 lives have been saved with the Axon network of devices, apps, training and people. Learn more at www.axon.com or by calling (800) 978-2737.

Facebook is a trademark of Facebook, Inc. and Twitter is a trademark of Twitter, Inc.

Axon, Axon Fleet, Axon Records, Axon Aware, Axon Detect and the Delta Logo are trademarks of Axon Enterprise, Inc., some of which are registered in the US and other countries. For more information, visit www.axon.com/legal. All rights reserved.

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CONTACT:
Carley Partridge
PR and Communications Manager
Press@axon.com

 View original content to download multimedia:http://www.prnewswire.com/news-releases/axon-announces-ai-powered-in-car-license-plate-reader-system-built-with-ethical-design-and-privacy-centric-framework-300943640.html

Axon Announces AI-Powered In-Car License Plate Reader System Built With Ethical Design and Privacy-Centric Framework

Axon Fleet 3 AI-Powered License Plate Reader System

ARTICLE: Axon Anncounces AI-Powered In-Car License Plate Reader System

In April of 2018, the Axon AI and Policing Technology Ethics Board (the board) was formed to provide us with advice on the development of AI products and services. Because of the business we are in, we asked them to pay particular attention to the impact of AI technologies on communities. The first board report provides us with thoughtful and actionable recommendations regarding face recognition technology that we, as a company, agree with. We believe it is important to share and discuss these recommendations here.

Current face matching technology raises serious ethical concerns. In addition, there are technological limitations to using this technology on body cameras. Consistent with the board's recommendation, Axon will not be commercializing face matching products on our body cameras at this time. 

We do believe face matching technology deserves further research to better understand and solve for the key issues identified in the report, including evaluating ways to de-bias algorithms as the board recommends. Our AI team will continue to evaluate the state of face recognition technologies and will keep the board informed about our research.

To date, Axon's work on face recognition has revolved around detecting, tracking and re-identifying faces in videos for the purpose of blurring out or redacting those faces prior to public release, in service of protecting people's privacy rights. “Re-identification” refers to the automated process of finding all the re-occurrences of a person's face in a single video. These algorithms do not attempt to match the identity of the individual to a database, only to identify video frames that are likely to include faces so that they can be redacted. Face detection (not face matching) and re-identification technology improves civic oversight by accelerating the speed and reducing the cost for agencies to disclose videos to the public, while protecting individual privacy during public records release events.

Technology is moving much faster than legislative bodies and courts can respond. Hence, we believe it is critical for technology leaders to work hard to understand the ethical, legal, and community implications for new technologies that are too new to be effectively covered by existing law.

With the guidance of our board, we are committed to developing technologies in an ethical and responsible manner. We will invest in working in a transparent manner and in tandem with leading independent researchers to de-bias training data and algorithms. 

Policing Transparency and Democratic Accountability

Our product development philosophy is clear and includes a wide array of oversight and audit technologies to deter abuse. This includes cartridge serialization (AFID), weapons data logs to record and report usage, integrated TASER cameras and body-worn cameras, automated sensors to activate camera recording, and soon gunshot detection to ensure events involving firearm discharges are recorded. None of these safeguards are required by law, but we see them as the right thing to do. Axon's goal is to build powerful new technologies with the right safeguards in place within the spirit of legal and ethical frameworks and community expectations. The board supports us in our pursuit to more clearly define and establish our ethical framework for new products. Our goal is to put the formal ethical framework policy in place later this year. We also share the board's desire to build the appropriate tools that will allow agencies to release to the public the appropriate data about the use of Axon products.

We thank the members of our board for the advice they have provided us, and we appreciate the time and effort that each member has dedicated to this effort. Outside ethical advisory boards like this are a new concept among technology companies, and we are proud to embrace it and design an ethical roadmap that we hope other companies can emulate. Our hope is that Axon’s and the board’s lessons learned can help guide other companies and organizations that may be considering implementing similar advisory boards. 

Axon has formed an AI ethics board to give advice on the development of AI products and services. Read the first board report to see recommendations regarding face recognition technology we agree with.

AI Ethics Board Report

ARTICLE: AI Ethics Board Report

By: Rick Smith

The Future of Face Matching at Axon and AI Ethics Board Report

Hear Stuart McKee, National Technology Officer - U.S. Public Sector, from Microsoft and former Axon VP of AI and Machine Learning talking about how we believe building responsible and trusted AI is important. Axon has established AI Ethics Board to guide our AI research, and makes sure that our work is CJIs compliant. Watch the Webinar below to learn more.

Learn from Axon and our partner Microsoft about Ethical AI application in Law Enforcement

Ethical AI in Law Enforcement Webinar Replay

Learn from Axon and Microsoft about AI application in Law Enforcement

Axon Ethical AI in Law Enforcement Webinar

ARTICLE: Ethical AI in Law Enforcement Webinar

Ethical AI in Law Enforcement Webinar

It's not often that companies the size of Axon are compared favorably to Google. But it happened last week in a Forbes article:

"This week, Axon ... demonstrated the kind of transparency that Google should aspire towards when it announced an AI ethics board to 'help guide the development of Axon's AI-powered devices and services'."

Let's recall that Google started with a machine-learned algorithm called PageRank. Since then, it has been a powerhouse for machine learning (ML), and arguably no other company has commercialized ML and artificial intelligence (AI) more than Google. They have also been paying attention to the ethical side of AI for a relatively long time. DeepMind's ethics board was formed in 2014. In his 2017 Founders’ Letter, Sergey Brin (the Google co-founder with the beard - in case you mix them up like I do) writes about AI: “such powerful tools also bring with them new questions and responsibilities. How will they affect employment across different sectors? How can we understand what they are doing under the hood? What about measures of fairness? How might they manipulate people? Are they safe?”

So being positioned above Google in the AI ethics space is a tall order.

For most people, the conversation about ethics of AI starts with the thought of sentient AI that could take over and rule us all one day. Before a congressional hearing on AI, Congressman Hurd asked people on the street about AI, and no surprise, most people's idea of AI is formed by movies. Naturally, doomsday scenario is the #1 notion in their mind.

The AI-apocalypse-frenzy has happened many times when a new technology has made a breakthrough. The printing press, the Internet, the mobile phone, Snapchat...the list goes on. Perhaps when the wheel was invented, concerned parents were skeptical. At the same time, if data is the new oil as they say, we obviously made a mess with the previous oil we discovered.

Which scenario is going to unfold then? Is it going to be all rosy or all gloomy? What can we do about it? Freeze and take no action? Or take a swing and see how things will unfold?

We don't have to accept what the movies or any pundit or expert predicts. We can help forge the world around us at present and create the future. There are talkers - people who freeze at the sight of any potential change and their only response is inaction and talking about how things are not going to work out. And then there are doers - people who work on making the world a better place every day by facing challenges, taking risks, and walking into uncharted territories. At Axon we are doers, and we believe that the world will be a better place with AI, if developed responsibly.

As a technologist, I believe that technology should—as it has in many cases so far—allow us to be more human. I am optimistic that AI, done the right way, will allow us to be more human.

The Michael Jordan of ML wrote in a recent blog post that what is clumped together as “AI” these days can be divided into three main categories which are in fact different things:

Human-imitative Artificial Intelligence (HIAI): Making machines that understand the world and have similar cognitive capabilities as humans. This is what most people know as AI.

Intelligence Augmentation (IA): The kind of AI that augments human intelligence and improves our productivity. The same way that eyeglasses can make us see better or cars can make us move faster, this kind of AI can enable us to do more by achieving higher levels of cognitive abilities. Examples include search engines and smart speakers.

Intelligent Infrastructure (II): When we use AI to improve the infrastructure of our information-based society and usually involves many connected devices. For example, Uber uses AI to create an Intelligent Infrastructure that moves millions of people around the world every week, and dating websites use AI to create an intelligent infrastructure for matching couples.

At Axon, the AI Research Team has focused on #2 and #3 and not on #1. We see AI as an assistant to our customers in public safety. It will help and support them in making decisions. It will provide a very effective set of tools for the officers to do more (efficiency) and have better access to crucial information and real-time safety measures (vigilance). In doing this we ensure that our AI technologies complement and augment the human intelligence while leaving all decision making to human judgment. In short, Axon AI technologies will empower the officers to be more human.

We do our AI development while keeping the ethical aspects front and center to every step of the process - from data collection to model training, inference, evaluation, and interpretation of the results. By avoiding AI type #1, we ensure that there is always a human-in-the-loop to make the final judgments whenever there might be a risk of impinging upon privacy or civil rights. Axon's AI Ethics Board keeps us in check.

We are committed to ensuring that the technology we develop makes the world a better and safer place. Our first-of-its-kind AI Ethics Board is a profound statement in that direction.

We are nowhere near done. There will be critics who point out shortcomings, fairly or unfairly, but this is a journey and it matters that we have started it. Theodore Roosevelt once said:

It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better. The credit belongs to the man who is actually in the arena, [..] who does actually strive to do the deeds;

WANT TO KNOW MORE ABOUT AXON'S AI RESEARCH? Learn More

Axon AI team shares the vision for the AI research, focusing on ethical development of Intelligence Augmentation (IA) and Intelligent Infrastructure (II).

ARTICLE: Responsible AI

Axon is leading the industry in Responsible AI

The development of body-worn cameras for law enforcement created a new way to collect and manage evidence and provided a clearer avenue of transparency between officers and citizens. However, this new technology initially created a vacuum around how to govern the use of this new tool. Prior to the wide deployment of body cameras, state, county, and municipal governments did not have specific laws or policies to deal with such technology. Many states did have some laws that were applicable to body-worn cameras as it relates to two-party consent or restrictions of recordings where privacy is expected, but these laws were not enacted for dealing with body-worn cameras.

The question became: do these current laws apply to body cameras — and if so, how — or do new laws need to be drafted and enacted to deal with this emerging technology?

Well, the answer to this question is complex and still being debated nationwide. The reason why it is so complex, is because all 50 states, the District of Columbia, large cities, and county governments are each individually forming laws and policies that govern the use and deployment of body-worn cameras. There is no one policy or nationwide law, but varying guidelines based on a web of state, county, or city laws and regulations. These laws and regulations may be drastically different depending on what part of the country you find yourself in.

State and local laws and policies, are living, breathing documents that can stand the test of time or be changed without a moment’s notice.

In general, about 30 states and the District of Columbia have created some type of law regarding body-worn cameras. The initial trend of legislation in 2014 and 2015 mostly focused on authoring government to create commissions or committees to study body-worn cameras or to begin to pilot and evaluate the technology. In many cases, the primary purpose of these commissions was to create recommendations on best practices and policies for a body-worn camera program.

As state and local governments gain more information from studying body-worn cameras, and as their local law enforcement agencies, began to test the technology, a second wave of legislation began. This second wave, in late 2015 and 2016, focused on public access to body-worn cameras footage, creating standard policy requirements, requiring certain type of officers to be equipped with cameras, and creating grant programs to help law enforcement agency procure the technology.

The legislation we are seeing in 2017 is similar to 2016. States are continuing to push for standardization of policy, this time around the balance of keeping police data for evidence and allowing public access to the data for transparency purposes. In addition, we are seeing, in some cases, legislation that would adjust state laws already pertaining to body-worn cameras to allow for easier use of the technology. This comes through trial and error. It is difficult to legislate new technology before seeing it fully deployed and operational for a few years.

State and local laws and policies, are living, breathing documents that can stand the test of time or be changed without a moment’s notice. As body-worn cameras become standard issue over the next few years, and as new hardware and software features are added to body-worn camera programs – new laws and regulations will continue to be promulgated.

The development of body-worn cameras for law enforcement created a new way to collect and manage evidence and provided a clearer avenue of transparency between officers and citizens. Learn about the history of body-worn camera policy in this article written by Esmael Ansari, Axon Director of Government Affairs.

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The Role of Responsible AI Within the Axon Ecosystem

Axon Announces AI-Powered In-Car License Plate Reader System Built With Ethical Design and Privacy-Centric Framework

The Future of Face Matching at Axon and AI Ethics Board Report

Ethical AI in Law Enforcement Webinar

Axon is leading the industry in Responsible AI

History of Body-Worn Camera Legislation