Table 1 The effect of gender and knowledge on AI appreciation in the first week ‘one-shot’ experiment. The dependent variable is the weight on advice (WOA), with values between 0 and 1. Our main explanatory variables (Gender, AI advice and High-knowledge) are binary; thus, the coefficients can be interpreted in percentage terms. The table reports OLS coefficient estimates and (in parentheses) p-values based on robust standard errors. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed), respectively.
From: Gender, knowledge, and trust in artificial intelligence: a classroom-based randomized experiment
(1) | (2) | (3) | (4) | ||
|---|---|---|---|---|---|
WOA | WOA | WOA | WOA | ||
AI advice | RQ1 | 0.0718*** | 0.146*** | 0.161*** | 0.214*** |
(0.006) | (0.002) | (0.000) | (0.000) | ||
Gender | -0.0560** | -0.00754 | -0.0413 | -0.00289 | |
(0.038) | (0.816) | (0.118) | (0.928) | ||
High-knowledge | -0.152*** | -0.141*** | -0.0811** | -0.0783** | |
(0.000) | (0.000) | (0.014) | (0.017) | ||
AI advice x Gender | RQ2 | -0.121** | -0.0988* | ||
(0.031) | (0.076) | ||||
AI advice x High-knowledge | RQ2 | -0.168*** | -0.155*** | ||
(0.001) | (0.003) | ||||
Task easiness | -0.361*** | -0.361*** | -0.361*** | -0.361*** | |
(0.000) | (0.000) | (0.000) | (0.000) | ||
Conceptual task | -0.0702* | -0.0702* | -0.0702** | -0.0702** | |
(0.050) | (0.051) | (0.048) | (0.049) | ||
Advice accuracy | 0.0448* | 0.0448* | 0.0448* | 0.0448* | |
(0.090) | (0.088) | (0.088) | (0.087) | ||
Constant | 0.507*** | 0.474*** | 0.459*** | 0.436*** | |
(0.000) | (0.000) | (0.000) | (0.000) | ||
r2 | 0.124 | 0.130 | 0.135 | 0.139 | |
Adjusted r2 | 0.118 | 0.122 | 0.128 | 0.131 | |
Number of participants | 59 | 59 | 59 | 59 | |
N | 826 | 826 | 826 | 826 |
