AI is popping up everywhere. How much it helps depends on the situation and how it is being used. In security, AI integrations have improved efficiency and monitoring, while enhancing capabilities. From video surveillance and fall monitoring to access control and more, the proper implementation and integration of AI can elevate your security solution.

6 Ways AI is Improving Access Control

Here’s how AI is improving access control:

1. Faster Access
2. Better Authentication Methods
3. Improved Contextual Awareness
4. More Scalability and Adaptability
5. Improved Accuracy and False Positive Reduction
6. More Support For Broader Operational Goals

1. Faster Access

Electronic access control is faster and more efficient than manual review and approvals for access. The addition of AI makes the review, validation, authentication, and access approval process even more efficient. Not only can it help speed up the process and reduce the oversight needed for access control, but it can also help reduce errors and further prevent intentional or accidental unauthorized access.

If you’re still using traditional keys and locks and have people manually reviewing credentials for access, upgrading to an access control system can be a big improvement. Even if you already have a modern access control system, it may be time for an upgrade.

Outdated equipment, new integrations or configurations not being available, and more are signs it’s time to upgrade your access control system. If your current access control system isn’t built to integrate AI and take advantage of the enhanced capabilities, it may be time to upgrade your system to one that can keep up with evolving technology and evolving security threats.

2. Better Authentication Methods

Another one of the ways AI is improving access control is by facilitating better authentication methods. Multi-modal access control readers and systems are already more efficient and more secure. Integrating AI advances authentication from simple to more advanced, making it even more efficient and accurate, while better supporting multiple types of credentials and authentication methods, and resisting biometric spoofing.

3. Improved Contextual Awareness

One of the biggest ways AI is improving access control is by improving contextual awareness. AI is a valuable resource that can proactively identify signals and patterns that indicate potential issues earlier and more accurately, while enhancing the contextual awareness of integrated security solutions for unified situational awareness.

In the realm of access control, this means an access control system designed to integrate seamlessly with other systems to better monitor entrances, exits, secure areas, and security gates. AI can process a large volume of data quickly and analyze behavioral cues, input from other security systems, environmental factors, and more for improved contextual awareness.

This makes these systems better at recognizing and preventing tailgating, credential sharing, advanced spoofing attempts, and other unauthorized access attempts that traditional systems may struggle to prevent. Leveraging video surveillance, facial authentication, behavior-based authentication, machine learning, and more, access control systems with AI-integrated capabilities can proactively identify threats and make real-time decisions to mitigate them effectively.

This type of contextual awareness also has other applications, within and beyond access control. In addition to applications of AI in video surveillance, the contextual awareness it can add to your operations can assist with fall monitoring and patient protection, event security, and more.

AI and Fall Monitoring in Senior Living

Senior living facilities and assisted living facilities have been using video surveillance and wearables equipped with AI to help predict and prevent senior falls to enhance their fall monitoring solutions and improve patient safety. Intelligent cameras and predictive analytics work together to monitor for and identify mobility cues and visual cues that are common predictors of a potential fall. When identified, alerts are triggered via sensors and nurse call systems to alert staff for improved response times, better fall monitoring and prevention, and patient protection that provides better outcomes for residents.

AI Integration for Event Security

In event security situations where monitoring crowd activity is essential, AI can help manage access as well as monitor and identify early signals of crowd crush, escalating aggression or impending fights, the presence of weapons, and more. Early detection and predictive analytics with contextual awareness mean:

• More proactive monitoring
• Earlier detection
• More response time for physical security systems and security personnel to respond
• More opportunities for early intervention, de-escalation, and prevention

4. More Scalability and Adaptability

One of the benefits of AI in access control is that it reduces administrative burden and overhead. In addition to reducing human error, this also makes these systems even more scalable and adaptable than traditional access systems.

Traditional methods and legacy security systems often require a lot of management and oversight, and tend to facilitate reaction to security threats. Over time, this can lead to outdated systems that respond to evolving security threats more slowly and less effectively than needed, and systems that are difficult to update and maintain. These are risks and challenges of legacy security systems.

Although many modern systems do allow security to be more proactive, strategically integrating AI to enhance capabilities allows organizations to truly become proactive in their security by facilitating early detection and prevention, instead of just reaction. With AI also accelerating security risks and threats, your access control systems and other security systems must keep pace.

5. Improved Accuracy and False Positive Reduction

Just as false alarms create problems by triggering alerts unnecessarily, so do false positives in access control when access is authorized or denied incorrectly. With better authentication methods and contextual awareness, AI is improving accuracy in access control, even as environmental conditions shift and user behaviors change. This reduces false positives and reduces errors across the board.

Intelligently and strategically incorporating AI capabilities makes identifying and flagging unusual activity faster and more precise for advanced anomaly detection. Taking in behavioral patterns and other information, like typical entry and exit patterns, the level of security for a specific building or area, local security alerts, mobility cues, dwell time, and more, AI in access control and other systems can assess access requests and user identity with full context for improved accuracy and access authentication.

6. More Support For Broader Operational Goals

Another one of the ways AI is improving access control is by helping to provide more support for broader operational goals. In addition to enhanced capabilities within access control systems, AI and improved technology also offer more seamless integrations, more scalability, and more adaptability.

Not only does this improve access control and security overall, but it also provides more capabilities in other areas and more support for broader operational goals in doing so. From reducing manual labor and optimizing resource use to providing cost savings over time, AI-powered access control and other applications can help deliver operational efficiencies.

Being able to learn, evolve, and adapt to changing and emerging threats is essential for modern, sophisticated security solutions. AI is facilitating this in modern access control systems and other security systems, while offering capabilities that can extend into facility monitoring and management, inventory management, supply chains, and more.

5 Considerations For Ethical AI Use in Access Control

Security, data collection, and privacy require balance. Your systems have to be able to provide security without compromising individual privacy and protections, especially around sensitive data. With evolving technologies, like AI, video surveillance, access control, and more, there are considerations for incorporating these ethically and accurately. These are some considerations for ethical AI in access control:

1. Remaining Compliant With Data Collection and Data Privacy
2. Limiting Algorithmic Bias and Ensuring Accuracy
3. Ensuring Accountability and Transparency of Systems
4. Keeping Proprietary Information Confidential
5. Aligning With Regulatory and Governance Standards

1. Remaining Compliant With Data Collection and Data Privacy

There are regulations around data collection and privacy that your facility and your security systems are required to meet. In the United States, examples of these include the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Depending on where you are located, whether your facility is private or public, and who will be engaging with your access control systems, you may need to comply with stricter rules and regulations.

This is a consideration for systems incorporating AI because of the expanded data collection. In the case of access control, this often includes biometric data. When dealing with biometric data, you have to make sure it is:

• Collected compliantly and lawfully
• Stored securely and protected
• Processed with explicit user consent

Users will need to be informed of how their data is being used, including how it is collected, processed, stored, protected, and more. Data collection and privacy processes, transparent privacy policies, enhanced cybersecurity, and how users will be informed and able to manage their data will need to be considered when incorporating AI.

2. Limiting Algorithmic Bias and Ensuring Accuracy

Algorithms are trained on datasets. If those datasets are not representative and biases are not accounted for, AI models can perpetuate those biases and disparities while operating unfairly or inaccurately. Part of incorporating systems equipped with AI is ensuring that datasets are representative to prevent biased results for fair operation and improved accuracy.

Working to limit algorithmic bias in the beginning sets up a more accurate foundation at the time of installation and integration. Regular audits and evaluations after installation will help systems continue to learn and improve over time, while also mitigating potential bias before it becomes a problem.

3. Ensuring Accountability and Transparency of Systems

Part of ensuring accountability with AI-powered systems is transparency within those systems. AI-powered systems can be powerful and effective because they can quickly process multiple data points and streams and make decisions, while also learning and adapting based on the information they gather. However, the system needs to be transparent to ensure accountability. This is crucial for being able to identify biases or potential errors.

If an AI-powered access control system granted or denied access, you should be able to review the system logs and information around an event to see how and why the system made that decision. If there is a discrepancy or error, this allows you to identify potential errors in the system’s logic or biases that you need to address. With a “black-box AI system,” where the system logic is hidden or not easily accessible, it is difficult to ensure accountability and consistent accuracy.

4. Keeping Proprietary Information Confidential

LLMs (large language models) are useful technologies that can help complete tasks based on trained information and datasets. AI-powered systems, including access control, may use a company’s internal data for training to continue to build out the system logic powering authentication processes and access authorization decisions.

However, it’s important to consider how this information will be protected and secured as well. Proprietary information must remain confidential with any security systems installed. This only becomes more important with sensitive, protected information, like biometric data.

5. Aligning With Regulatory and Governance Standards

Especially in areas like healthcare, security, and access control, aligning with regulatory and governance standards is a huge consideration for ethical AI use. For AI governance, aligning with the ISO 42001 standard provides a framework to follow for responsibility and ethically incorporating AI.

ISO/IEC 42001 is an international standard for an Artificial Intelligence Management System (AIMS). It lays out a specific “how-to” framework to follow and parameters for measuring compliance that allow companies to incorporate and use AI effectively, safely, and ethically. Plus, aligning and meeting a standard like this tends to encompass all of the other considerations for ethical AI in access control and other areas.

A good security systems integrator will be able to help you navigate these standards and practices and ensure implementation through installation, integration, and configuration of systems incorporating AI. Prioritizing objectives and identifying needs can help you choose the right security systems integrator.

Upgrade Your Access Control Solution With NEPPS

These are just a few examples of how AI is improving access control. Integrations and capabilities will continue to evolve, and so will security threats and vulnerabilities. Make sure your security solution stays modern and comprehensive by updating your systems, components, and configurations when needed. If you’re interested in enhancing or upgrading your facility security, contact NEPPS at 1-800-736-1456.