ai-impact

An interpretable system that models the future of work as an equilibrium under AI-driven forces. Instead of predicting job loss, it decomposes workforce disruption into automation pressure, adaptability, skill transferability, demand, and AI augmentation to explain stability, tension, and transition paths by 2030.

Power BI dashboard analyzing AI's impact on job roles by 2030, including automation risk, salary trends, AI exposure, and technology growth factors.

Simulation and analysis of employment skill optimization under AI-driven labor-market change.

"An end-to-end data analysis and advanced engineering pipeline exploring the impact of AI automation on job displacement, salaries, and future hiring trends. Features rigorous multi-tier data cleaning."

Analysis of the 2025 Stack Overflow Survey exploring AI's impact on Data Science jobs. Built with Python, Pandas, Seaborn, and Scikit-Learn.

Reproducible Bayesian model of how AI capability progression projects onto global labour displacement. Sigmoid-fitted SWE-bench, vectorised Monte Carlo, hierarchical PyMC sector model, temporal CV.

NLP analysis of ~200K AI news articles to identify impacted industries, companies, technologies, topics, and sentiment trends.

A Streamlit dashboard analyzing the impact of AI announcements and model releases on equity prices and derivatives markets. Features event study methodology (CAR/CAAR), 3D implied volatility surfaces, real-time sentiment analysis with VADER, and interactive portfolio simulation.

AI exposure index for the European workforce built from Eurostat employment data, ESCO skills taxonomy, and LLM task scoring.

AI career impact ratings for 1,028 skills across 88 roles. Python SDK + MCP server + OpenAI/Anthropic adapters + CLI. Install from source.

🤖 Analyze the future of work with the Workforce Disruption Equilibrium Engine, a system for understanding job changes in an AI-driven world.