PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 1, 20260 citationsOpen Access

CAPA: A Multiplicative Framework for Human Performance in the AI Age

View Full Paper
ASAnil Kumar Sharma

Key Points

  • This research aims to establish a framework that predicts human performance specifically in roles enhanced by AI technology.
  • Developed the CAPA framework comprising curiosity, attitude, passion, and aptitude.
  • Transformed the CAPA concept into a predictive instrument for human performance.
  • Analyzed the multiplicative nature of the framework compared to traditional additive models.
  • Found that human performance in AI contexts is multiplicative, meaning all elements must be positive for success.
  • Demonstrated that any zero in the four factors collapses overall performance.
  • Indicated that AI reduces the significance of aptitude in determining professional success.

Abstract

We present CAPA (Curiosity × Attitude × Passion × Aptitude), a multiplicative framework for predicting human performance in AI-enabled roles. The framework emerges from AACP (2023) and is transformed into a predictive instrument for the age in which AI removes the Aptitude gate from most professional roles. The central claim: human performance in AI-enabled contexts is multiplicative, not additive. One zero in the four-element chain collapses the entire product.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Anil Kumar Sharma (2026) studied this question.

synapsesocial.com/papers/69ccb7c216edfba7beb89d0fhttps://doi.org/10.5281/zenodo.19335544
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Human–AI Co-Agency for Competency-Based Talent Development: A Framework Integrating Creativity, Cognitive Skills, and Ethical Collaboration2026
  2. 2CAPS: Cognitive Accounting and Productivity Standard A Voluntary Disclosure Framework for Measuring AI-Driven Productivity Beyond GAAP2026
  3. 3The Adaptive Personality Match Index (APMI™): A Behavioral Framework for Matching Humans to AI Systems by Interaction Style2026
  4. 4Four practical questions for analysing your own performance when working with AI2026
  5. 5From Competency Models to Targeted Interventions: Fostering AI Competence as a Future Skill with AICompAss in Heterogeneous Teams – a Design-Based Approach2026