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Haptic feedback

Haptic features in a design system for embedded AI, particularly in an SRE context like Golem, would have some unique characteristics:

  1. Urgency encoding: Use varying intensities and patterns of haptic feedback to convey the severity of system alerts or incidents.

  2. AI confidence indication: Subtle haptic pulses could indicate the AI's confidence level in its recommendations or predictions.

  3. State transitions: Provide haptic cues when transitioning between AI-assisted and manual control modes.

  4. Error prevention: Use haptic warnings to prevent critical actions without confirmation, especially for AI-suggested changes.

  5. Attention direction: Guide user attention to specific UI elements with localized haptic feedback, based on AI analysis of system state.

  6. Workload management: Adjust haptic intensity based on the user's current cognitive load, as assessed by the AI.

  7. Multimodal confirmation: Combine haptic feedback with visual and auditory cues for important AI-driven notifications.

  8. Personalized feedback: Allow AI to learn and adjust haptic patterns based on individual user preferences and responsiveness.

  9. Environmental adaptation: Modify haptic intensity based on the user's environment (e.g., stronger in noisy data centers).

  10. Silent alerts: Use haptics for discreet notifications in situations where visual or auditory alerts are inappropriate.

  11. Gesture completion: Provide haptic confirmation when gesture-based commands are successfully recognized by the AI.

  12. Training mode: Implement specific haptic patterns to guide users through new AI-assisted features or workflows.

  13. Bias indication: Use distinct haptic signals to alert users of potential AI biases in decision-making processes.

  14. Data collection notification: Provide a unique haptic signature when the system is collecting data for AI training purposes.

These guidelines ensure that haptic features in the Golem Design System enhance the user experience by providing intuitive, non-visual feedback that leverages AI capabilities while maintaining user awareness and control in critical SRE environments.