How AI Usage Affects Human Skills: A Multi-Era Analysis

By shrijeetverma13 · May 30, 2026

This analysis tracks how increased reliance on AI tools impacts core human capabilities like creativity, critical thinking, and problem-solving across…

Two bar charts were generated comparing Mental Wellbeing and AI Dependency scores across professions. For Mental Wellbeing, Science & Research scores highest (63.17) while Engineering scores lowest (62.6). For AI Dependency, Unemployed/Retired ranks highest (49.59) while Education ranks lowest (48.75). Notably, the differences across all professions are quite small, indicating these scores are broadly similar regardless of occupation.

Full AGI Integration is the clear winner, driving the highest scores in both Innovation Rate (60.09) and Learning Speed (69.32), giving it the top combined average score of 64.71. Two bar charts and supporting data tables were generated to visualize these comparisons across all AI tool categories.

The analysis produced two visualizations and supporting data tables to identify which Education Level and Scenario combinations show the highest AI Dependency Score paired with the lowest Human Decision-Making Involvement. A scatter plot maps all combinations by these two metrics, while a horizontal bar chart ranks the top 10 combinations by their 'gap score' (AI Dependency minus Human Decision Involvement) — the higher the gap, the more AI-reliant and human-disengaged the group is.

The analysis examined which Regions and Demographic Groups show the most favorable Outcome Label distributions. Three data tables were produced summarizing favorable outcome percentages broken down by Region, Demographic Group, and a combined Region × Demographic Group view.

A multi-line chart and data table were generated showing how Human Creativity Score, Problem Solving Skills, and Attention Span have trended from 2024 to 2075. Overall, the three metrics remain relatively stable across the years with no dramatic long-term rise or fall. Human Creativity Score stayed nearly flat (63.26 → 63.78, a +0.52 change), Problem Solving Skills showed the most notable improvement (+4.08, from 63.28 to 67.36), while Attention Span in Minutes slightly declined (-2.15 minutes, from 46.20 to 44.05). Year-over-year fluctuations are present, but the long-term averages — Creativity: 63.43, Problem Solving: 65.18, Attention: 44.97 — suggest broad stability across the period.

The analysis reveals that higher Weekly AI Usage Hours is associated with lower scores in both Human Creativity and Critical Thinking Ability. Two charts were generated: a grouped bar chart comparing average scores across usage tiers (Minimal, Low, Moderate, High, Very High), and a trend line chart showing how both scores change as weekly AI usage hours increase. Both metrics show the same moderate negative correlation of -0.221 with weekly AI usage hours.

The analysis successfully computed a composite Human Growth Index (HGI) for each Era by averaging five key metrics: Human Creativity Score, Critical Thinking Ability, Problem Solving Skills, Learning Speed, and Human Decision Making Involvement. Two visualizations were generated to display the results: a horizontal ranked bar chart showing each Era's overall HGI score from highest to lowest, and a grouped bar chart breaking down each metric's individual contribution per Era. These charts make it easy to compare both overall performance and the specific strengths of each Era across the five human growth dimensions.

The analysis successfully detected outliers across three columns — Weekly AI Usage Hours, Cognitive Load Index, and Attention Span Minutes — using the IQR 1.5x rule. Two visualizations were generated: a side-by-side box plot showing the distribution and outlier points for each column, and a bar chart comparing outlier counts per column. Summary tables were also produced with the calculated lower/upper bounds, outlier counts, and their percentage of total rows for each metric.

A data table was generated comparing average AI Tool Proficiency, AI Dependency Score, and Adaptability Score across education levels. The table presents these three key metrics grouped by education level, sorted from lowest to highest, giving you a clear side-by-side comparison of how AI-related skills and behaviors vary with educational background.

The Pearson correlation analysis of six cognitive and wellbeing metrics has been completed, with two visualizations generated: a heatmap showing all pairwise correlations with annotated coefficients, and a horizontal bar chart ranking all variable pairs by correlation strength. The strongest positive relationship is between Social Interaction Quality and Adaptability Score (r = 0.656), indicating that individuals with higher social interaction quality tend to score higher on adaptability. The strongest negative relationship is between Emotional Intelligence and Cognitive Load Index (r = -0.228), suggesting that higher emotional intelligence is modestly associated with lower cognitive load.