Table 2 The effect of gender and knowledge on AI appreciation using the sample including the extended experimental period. 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. Feedback is a binary variable that takes the value of ‘1’ for observations after the second week. The table reports OLS coefficient estimates and (in parentheses) p-values based on robust standard errors clustered by subject and question. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed), respectively.

AI advice

RQ3

0.0614*

0.134**

0.143***

0.195***

(0.055)

(0.022)

(0.008)

(0.002)

Gender

-0.0247

0.0309

-0.00973

0.0354

(0.465)

(0.444)

(0.757)

(0.356)

High-knowledge

-0.205***

-0.193***

-0.132***

-0.129***

(0.000)

(0.000)

(0.003)

(0.003)

Feedback

0.0827**

0.0800**

0.0793**

0.0768*

(0.022)

(0.027)

(0.028)

(0.053)

AI advice x Gender

RQ2

-0.128*

-0.107*

(0.054)

(0.080)

AI advice x High-knowledge

RQ2

-0.163***

-0.149**

(0.007)

(0.013)

AI advice x Feedback

0.00136

(0.981)

Task easiness

-0.364***

-0.368***

-0.367***

-0.370***

(0.000)

(0.000)

(0.000)

(0.000)

Conceptual task

0.0531

0.0518

0.0523

0.0513

(0.142)

(0.152)

(0.147)

(0.155)

Advice accuracy

0.0306

0.0302

0.0301

0.0298

(0.296)

(0.301)

(0.300)

(0.303)

Constant

0.427***

0.395***

0.385***

0.362***

(0.000)

(0.000)

(0.000)

(0.000)

r2

0.137

0.142

0.145

0.149

Adjusted r2

0.135

0.140

0.144

0.147

Number of participants

82

82

82

82

N

3667

3667

3667

3667