Ryerson Project Ryerson Project

Ryerson Project Item 145

I think artificial intelligence technology is positive for humanity.

American adults' average (mean) response was 4.74 on a scale of 0 (Disagree) to 10 (Agree). 140 responses have been collected (so far) from 2026-07-08 to 2026-08-26.

Descriptive Statistics

Mean4.74
Median5.00
Standard deviation3.04
N140
Standard error0.257

All-Time Distribution

Response 0: 21 Response 1: 6 Response 2: 12 Response 3: 8 Response 4: 9 Response 5: 23 Response 6: 24 Response 7: 10 Response 8: 10 Response 9: 6 Response 10: 11 0 1 2 3 4 5 6 7 8 9 10 0 24 Response value Count

Comparison to Other Items

Based on all-time mean agreement, this item ranks 99 out of 132 qualifying items and is at the 25.2 percentile.

Qualifying items have 100 or more total observations. Higher means indicate more agreement and therefore a higher rank.

Monthly Trend

0 1 2 3 4 5 6 7 8 9 10 0% 50% 100% 0 5 10 2026-07 response 0: 19.1% 2026-07 response 1: 5.9% 2026-07 response 2: 11.8% 2026-07 response 3: 2.9% 2026-07 response 4: 4.4% 2026-07 response 5: 19.1% 2026-07 response 6: 14.7% 2026-07 response 7: 4.4% 2026-07 response 8: 4.4% 2026-07 response 9: 4.4% 2026-07 response 10: 8.8% 2026-08 response 0: 11.1% 2026-08 response 1: 2.8% 2026-08 response 2: 5.6% 2026-08 response 3: 8.3% 2026-08 response 4: 8.3% 2026-08 response 5: 13.9% 2026-08 response 6: 19.4% 2026-08 response 7: 9.7% 2026-08 response 8: 9.7% 2026-08 response 9: 4.2% 2026-08 response 10: 6.9% Jul 2026 Aug 2026 Observation month Percent of responses Monthly mean

Observed Trend

Observations suggest unchanging agreement over the observed period, from 2026-07-08 to 2026-08-26. The estimated change over that period is 1.478 points on a 0 to 10 scale. Regression results place a 95% confidence interval around that observed-period change of [-0.296, 3.253].
Regression table

The daily slope annualized over 365.25 days is 11.020 points per year, with a 95% confidence interval of [-2.210, 24.249]. This short-window annualized number is provided for reference, but the observed-period change above is the primary trend estimate.

Call:
lm(formula = response_value ~ days_since_start, data = model_data)

Residuals:
    Min      1Q  Median      3Q     Max 
-5.4678 -2.4194  0.4826  1.8404  5.9804 

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)       3.98942    0.52015   7.670  2.8e-12 ***
days_since_start  0.03017    0.01832   1.647    0.102    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.022 on 138 degrees of freedom
Multiple R-squared:  0.01928,	Adjusted R-squared:  0.01217 
F-statistic: 2.713 on 1 and 138 DF,  p-value: 0.1018