Wearables and AI: How Artificial Intelligence can improve (or weaken) security

Artificial intelligence (AI) is revolutionizing wearable technology. From personalized fitness recommendations to early disease detection, AI enables wearables to do far more than just track steps. But while AI unlocks new capabilities, it also creates new security challenges. This article explores how AI is transforming wearable security—and where the risks lie.

1. How AI Is Used in Wearables

AI systems analyze large volumes of biometric and behavioral data in real time to:

• Predict health risks (e.g., irregular heartbeat, sleep disorders)
• Recognize patterns in activity or mood
• Detect anomalies such as falls or dangerous symptoms
• Enable adaptive interfaces and real-time feedback

These intelligent features offer major advantages in terms of health monitoring and user personalization.

2. Security Benefits of AI

When implemented responsibly, AI can enhance wearable security in several ways:

• Anomaly detection: AI can spot unusual device behavior—such as unexpected data access—that may signal a cyberattack.
• Behavior-based authentication: Instead of PINs or passwords, AI can authenticate users based on movement patterns, heartbeat rhythms, or even walking gait.
• Dynamic risk assessment: AI can assess device environments and trigger protective actions (e.g., locking a device when in an unfamiliar location).
• Automated threat response: AI can quarantine devices, block connections, or initiate alerts when a threat is detected.

3. How AI Can Undermine Security

Despite its benefits, AI can also become a liability—especially when poorly implemented:

• Black-box algorithms: Many AI systems operate without transparency, making it hard to identify and fix security flaws.
• Data overcollection: AI thrives on data—but excessive collection increases privacy risks and attack surfaces.
• Bias and false positives: AI might misidentify normal behavior as suspicious—or miss actual threats, leading to false security.
• Adversarial attacks: Hackers can manipulate AI models through specially crafted inputs, causing incorrect behavior or bypassing authentication.

4. Ethical and Legal Considerations

Using AI in wearables raises important ethical and legal questions:

• Informed consent: Users must know how their data is being used and whether it is shared with third parties.
• Data minimization: Only the data necessary for specific AI functions should be collected.
• Accountability: If an AI system causes harm—who is responsible? The manufacturer, the developer, or the user?

Regulations such as the EU AI Act and GDPR are beginning to address these concerns—but many questions remain unresolved.

5. Best Practices for Secure AI in Wearables

• Use explainable AI: Algorithms should be understandable and auditable.
• Apply strong data encryption: All AI-related data processing must follow strict security standards.
• Limit model access: Prevent unauthorized access or manipulation of AI models.
• Regularly test for adversarial vulnerabilities.
• Ensure continuous monitoring and retraining to detect model drift and new threat patterns.

6. Conclusion: AI Is Powerful—But Not Infallible

Artificial intelligence can significantly improve the security of wearables—but only when implemented with care. Manufacturers must balance innovation with transparency, accountability, and data protection. As AI continues to evolve, only those who build trust into their systems will succeed in creating the secure wearables of tomorrow.