As artificial intelligence becomes a central part of modern infrastructure, safety, transparency, and accountability have never been more critical.

At FLIR, we welcome this benchmark. Our proprietary AI model, developed specifically for Intelligent Traffic Systems (ITS), not only complies with global regulations, but it was built with these values in mind.

Principles of Responsible AI and Why They Matter for Traffic Safety

AI systems deployed across any industry must be safe, transparent, traceable and non-discriminatory. Upcoming regulations have introduced a clear framework for how AI can and cannot be used based on the level of risk posed to individuals and society. Key principles include:

• Human oversight over automated decisions
• Data privacy and anonymity
• No biometric identification or categorisation in public spaces
• No social scoring or manipulative AI
• Environmentally conscious development

These values are especially relevant in transportation, where AI influences traffic flow, incident detection, and, increasingly, vehicle autonomy. When system decisions affect public safety and mobility, the stakes are high, and the technology must meet the most rigorous standards.

FLIR's Proprietary AI: Built for Compliance and Confidence

FLIR has developed an entirely in-house AI model specifically for ITS and safety applications. Unlike generic solutions or open-source datasets, our AI model is:

• Trained exclusively on images from FLIR's own thermal and visible-light cameras, ensuring total control and data consistency.
• Version-controlled for full transparency and traceability, so we know exactly when, how and why a model was updated.
• Housed in a closed, secure environment with tightly managed access to training data and model repositories.
• Not connected to the internet during operation, meaning cameras are not susceptible to dynamic changes or third-party interference.

Most importantly, all data is anonymous; no images can be linked to identifiable individuals.

Why Closed Systems Matter in Traffic Applications

Because FLIR's ITS operate as closed systems and don't rely on internet access, data streaming, or AI model changes, their performance is safeguarded in critical infrastructure while eliminating exposure to real-time security threats or privacy breaches.

Furthermore, FLIR's solution is non-generic, so it doesn't generate new data during operation. It simply applies a highly specialised AI model to evaluate real-time events, like stopped vehicles, smoke, wrong-way drivers or pedestrians in a tunnel, against a robust library of known traffic behaviours. That library has been built using more than 30 years of data, giving our AI unmatched depth and accuracy without compromising personal privacy.

A Clear Contrast with Prohibited AI Use

The following practices are banned under certain regional legislation, and FLIR's ITS are fundamentally designed to avoid them:

• Cognitive manipulation: No FLIR ITS uses emotional triggers or behaviour-influencing tactics.
• Social scoring: We don't classify drivers or vehicles based on behaviour, demographics or socio-economic status.
• Biometric identification: Our systems do not identify individuals or collect biometric data.
• Remote facial recognition: No FLIR ITS are used to track or monitor people in public spaces.

Instead, our focus is singular: delivering accurate, real-time incident detection that helps traffic operators improve road safety and reduce response times, especially in high-risk environments like tunnels, highways and inter-urban networks.

Leading the Way in Ethical AI for Traffic Safety

AI is transforming transportation, but it must be implemented responsibly. At FLIR, innovation and regulation go hand in hand. Our proprietary, transparent and fully controlled AI model ensures traffic authorities can deploy cutting-edge safety solutions while staying compliant with global standards in AI ethics and governance.

As the world moves forward with AI legislation, FLIR is proud to set the example of what trustworthy, accountable AI in transportation looks like. Working closely with local governments and transport authorities to ensure every deployment meets regional regulations and remains fully compliant with evolving legal and ethical standards.