Human-Centered AI · Wellbeing · Behavioral Analytics
Sound Balance — Behavioral Decision Support
Context
Product team operating in a wellbeing and productivity context where AI-driven insights must remain interpretable, ethical, and relevant for real-world use.
Scope
Scenario-based exercise using public dataset; designed to reflect enterprise decision workflows.
Problem
Teams and individuals lacked a clear understanding of how behavioral patterns influenced focus, wellbeing, and productivity.
My Role
Product analytics & UX-led dashboard design translating business and regulatory/ operational goals into KPI definitions, decision-ready views, and documentation. Designed interpretable, non-intrusive behavioral KPIs for ethical, human-centered decision support.
Key Decisions
Designed interpretable, non-intrusive behavioral
KPIs for ethical, human-centered decision support
Prioritized interpretability over
black-box AI outputs
Structured insights for actionable,
non-intrusive use
Outcome
Improved visibility into focus and wellbeing patterns
Supported ethical, human-centered wellbeing insights
Enabled more intentional productivity habits
Decision Impact Summary
Key Insight
Focus and emotional balance were influenced by behavioral patterns rather than individual habits, emerging only when music, mood, and productivity signals were analyzed together.
Decision Supported
Enabled teams and individuals to make informed adjustments to work rhythms and focus strategies, based on interpretable, non-intrusive behavioral insights.
Business Impact
Supported ethical, human-centered productivity decisions by providing actionable wellbeing signals without relying on opaque or black-box AI outputs.
UX Dashboard
UX Strategy & Dashboard Architecture
Designed an enterprise-grade AI dashboard structured by stakeholder needs.
Executive & HR Leadership —
Wellbeing Overview
For high-level clarity.
Includes:
Recommended actions
Daily Balance Score
Focus amplification trends
Mood & energy patterns
Wellbeing risks
Data & AI Teams — Behavioral
Correlation Analysis
For interpretability and AI insight modeling.
Includes:
Burnout risk detection
Music → Productivity correlation graphs
Mood forecast model
Genre emotional impact
Listening patterns segmentation
Individuals & Coaches —
Personalized Wellbeing Insights
Human-centered, actionable, non-technical.
Includes:
Personalized recommendation cards
“Best time for deep work” indicator
Habit loops & energy cycles
Smart playlist suggestions
Why it matters
Shows how human-centered analytics bridges AI, UX, and
and decision-making in wellbeing-oriented products.
Applicable contexts
Digital Wellbeing · Human-Centered AI · Behavioral Products
Extended case details available upon request.