INDUSTRY PROFESSIONAL

Clearing Up Confusion

Taking a moment to clear up any misconceptions about AI

The confusion I hear in the industry starts with the definitions of these terms: artificial intelligence (AI), machine learning (deep and shallow), and analytics. Some believe these things are all the same and use them interchangeably. On the other end of the spectrum you have those using the terms accurately - and you have everything in between.

This creates market confusion even down to the one-on-one conversation level. So, for clarity:

  • AI (artificial intelligence) at its most basic is the ability for a machine to learn on its own;
  • Machine learning typically references how the AI is being applied (shallow/deep evaluation of data at different levels); and
  • Analytics are typically a catch-all word for the results that are presented back to the user (and this is also used with non-AI related analytics).

The most basic definition of AI is the ability for a machine to learn on its own. The expectations are that it would provide actionable results and potentially even take intelligent action based on those results.

Manufacturers in our industry are fairly astute and aware of AI, its subtleties, and the applications thereof. After all, they need to be thinking not about technology today, but innovating the technology of tomorrow. Milestone believes intelligence has a huge role in that.

So, What Does AI NOT Mean?

It is easy to jump on the bandwagon and consider anything “smart” as AI. To date, in our industry, most analytics are smart, not intelligent— meaning they can analyze video and conclude some fairly amazing things. However, most are simply algorithmic and not necessarily learning anything new over time.

The relationship to AI of deep learning and machine learning illustrates how these are different. Machine learning usually references how the AI is being applied (shallow/deep evaluation of data/levels). Shallow and deep learning are the mechanisms by which machine learning takes place.

Due to processing limitations, learning has typically taken place in a “shallow” way (i.e. by looking at only a few levels or dimensions). However, with the significant advances in processing power gained through the development of graphical processing units (GPUs), we can now look at data in a “deep” way (i.e. by looking at many more levels).

I think that what is reasonable to expect AI to accomplish in its applications is augmentation. It will be quite some time before AI has the potential to replace the capabilities of the average security industry end user. The more likely scenario is that AI will be leveraged to process much more data in much less time, empowering end users to make much better decisions more quickly.

In a post-event scenario (i.e. investigative forensics), speed has the potential to matter substantially. In a pre-event scenario (i.e. prevention), more data from more sources provides more intelligent decision-making regarding potential events. We still need people in the AI equation; we just want to give them better data with which to make their decisions.

AI can definitely enhance traditional security through augmentation of the tasks at hand: more data from more sources enables more intelligent decision making.

Is it Really a Learning Situation?

For those who are looking to implement AI, there are some things they should be aware of.

There is currently a trend regarding AI-driven solutions, where people typically think of them as ones that analyze video (either live or recorded) and learn over time, with the result that the system becomes more accurate and better in its assessment. However, that constant learning is not necessarily the case for many solutions today, so it’s important to truly understand the application of AI in the solution you are evaluating.

There are few truly AI-at-deployment solutions in the security industry today. Many solutions are “AI-trained”, meaning that back in the lab their algorithms are trained using AI capabilities, but once that algorithm is developed, it is deployed as just a smart algorithm and there is no further learning occurring. The only time these algorithms will improve is when they are updated to include improved learning. There are cloud-based AI solutions today that can be leveraged for augmenting your security solutions. And as time moves forward, cloud seems to be part of most people’s conversations when it comes to analytic processing (whether AI driven or not). In the cloud, there is a consumption-cost model built around processing, so using the cloud versus local servers comes down to a decision of ROI based on length of time/usage.

This article originally appeared in the April 2019 issue of Security Today.

Featured

  • New Report Reveals Top Trends Transforming Access Controller Technology

    Mercury Security, a provider in access control hardware and open platform solutions, has published its Trends in Access Controllers Report, based on a survey of over 450 security professionals across North America and Europe. The findings highlight the controller’s vital role in a physical access control system (PACS), where the device not only enforces access policies but also connects with readers to verify user credentials—ranging from ID badges to biometrics and mobile identities. With 72% of respondents identifying the controller as a critical or important factor in PACS design, the report underscores how the choice of controller platform has become a strategic decision for today’s security leaders. Read Now

  • Overwhelming Majority of CISOs Anticipate Surge in Cyber Attacks Over the Next Three Years

    An overwhelming 98% of chief information security officers (CISOs) expect a surge in cyber attacks over the next three years as organizations face an increasingly complex and artificial intelligence (AI)-driven digital threat landscape. This is according to new research conducted among 300 CISOs, chief information officers (CIOs), and senior IT professionals by CSC1, the leading provider of enterprise-class domain and domain name system (DNS) security. Read Now

  • ASIS International Introduces New ANSI-Approved Investigations Standard

    • Guard Services
  • Cloud Security Alliance Brings AI-Assisted Auditing to Cloud Computing

    The Cloud Security Alliance (CSA), the world’s leading organization dedicated to defining standards, certifications, and best practices to help ensure a secure cloud computing environment, today introduced an innovative addition to its suite of Security, Trust, Assurance and Risk (STAR) Registry assessments with the launch of Valid-AI-ted, an AI-powered, automated validation system. The new tool provides an automated quality check of assurance information of STAR Level 1 self-assessments using state-of-the-art LLM technology. Read Now

  • Report: Nearly 1 in 5 Healthcare Leaders Say Cyberattacks Have Impacted Patient Care

    Omega Systems, a provider of managed IT and security services, today released new research that reveals the growing impact of cybersecurity challenges on leading healthcare organizations and patient safety. According to the 2025 Healthcare IT Landscape Report, 19% of healthcare leaders say a cyberattack has already disrupted patient care, and more than half (52%) believe a fatal cyber-related incident is inevitable within the next five years. Read Now

New Products

  • ResponderLink

    ResponderLink

    Shooter Detection Systems (SDS), an Alarm.com company and a global leader in gunshot detection solutions, has introduced ResponderLink, a groundbreaking new 911 notification service for gunshot events. ResponderLink completes the circle from detection to 911 notification to first responder awareness, giving law enforcement enhanced situational intelligence they urgently need to save lives. Integrating SDS’s proven gunshot detection system with Noonlight’s SendPolice platform, ResponderLink is the first solution to automatically deliver real-time gunshot detection data to 911 call centers and first responders. When shots are detected, the 911 dispatching center, also known as the Public Safety Answering Point or PSAP, is contacted based on the gunfire location, enabling faster initiation of life-saving emergency protocols.

  • Connect ONE’s powerful cloud-hosted management platform provides the means to tailor lockdowns and emergency mass notifications throughout a facility – while simultaneously alerting occupants to hazards or next steps, like evacuation.

    Connect ONE®

    Connect ONE’s powerful cloud-hosted management platform provides the means to tailor lockdowns and emergency mass notifications throughout a facility – while simultaneously alerting occupants to hazards or next steps, like evacuation.

  • QCS7230 System-on-Chip (SoC)

    QCS7230 System-on-Chip (SoC)

    The latest Qualcomm® Vision Intelligence Platform offers next-generation smart camera IoT solutions to improve safety and security across enterprises, cities and spaces. The Vision Intelligence Platform was expanded in March 2022 with the introduction of the QCS7230 System-on-Chip (SoC), which delivers superior artificial intelligence (AI) inferencing at the edge.