The effort heuristic suggests that perceived effort enhances evaluations of products and artworks. While well-documented for human creators, it remains unclear whether this principle extends to artificial agents. We investigated whether longer generation times increase effort attribution to AI and, consequently, improve aesthetic evaluations of AI-generated artworks. Two pre-registered studies manipulated generation time: Study 1 (N = 207) used a between-subjects design with reported times (30 seconds vs. 4–8 minutes vs. 30+ minutes), while Study 2 (N = 209) employed a within-subjects design with experienced wait times (4 vs. 20 seconds). Results confirmed that longer generation times increased perceived effort in both studies. However, this heightened effort attribution did not translate into more favorable aesthetic evaluations across any dimension (liking, beauty, depth, quality, complexity, or monetary value). Positive attitudes toward AI and attribution of consciousness emerged as the strongest predictors of aesthetic appreciation. These findings suggest that the effort heuristic does not operate uniformly across human and artificial agents: while people recognize AI effort, they do not reward it with enhanced aesthetic valuations. This dissociation highlights that effort cues lose their normative value as quality signals in the absence of human agency, reinforcing identity-based biases against AI-generated art.

The COVID-19 pandemic has posed significant challenges to mental health worldwide, raising the need to identify stable psychological resources that promote sustainable well-being. This longitudinal study examined whether character strengths predict well-being, post-traumatic growth, and mental health over a 13-month period. Participants (N = 146) completed online measures of character strengths, mental health, life satisfaction, affect, and post-traumatic growth at two time points. First, we tested whether a single general factor of character predicted later mental health and whether life satisfaction, affect, and post-traumatic growth mediated this relationship. Then, we repeated this model but with five different character strengths factors as predictors. Results showed that character predicted all mediators and mental health over time, but only the affective components of well-being mediated the relationship between character and mental health, especially positive affect. When looking at the five character strengths factors, although the majority predicted higher well-being and better mental health over time, goodness and interpersonal and fortitude strengths yielded the strongest effects. These findings suggest that character strengths contribute to sustainable well-being by fostering affective resilience in the face of adversity, aligning with the goals of Sustainable Development Goal 3 (Good Health and Well-being).