Discussion
The present study investigated the effects of our designed messages reminding people of familial support to increase positive attitudes toward IT innovations. The messages showed statistically significant effects, similar to our previous study of nudging attitudes toward air pollution caused by industrialization [There were three main similarities to our previous study. First, the effect sizes were in the order CG (the simplest textual message) < TG1 (textual message with additional descriptions of familial support) < TG2 (textual message with additional descriptions of familial support and an illustration), where the size of the effect was strongly correlated with perceptions of being supported by previous generations. Adding a textual description of support from previous generations and to future generations in TG1 increased perceptions of familial support and the effects of information provision to increase positive attitudes toward IT innovations. Further additional illustrations increased the perceptions of familial support and the effect of information provision, even though the illustration contained the same information as the textual descriptions for TG1. Second, before the intervention, the respondents initially perceived the influence of the risk sources as larger on Future generations than on Yourself, and women were more risk-averse. Third, respondents with high agreeableness showed larger intervention effects on Future generations, where they expected the IT innovations to benefit more people.These consistent trends in the effects suggest that the framework of our designed message could be applied to information provision for a wider variety of topics. The message effects of increasing positive attitudes toward new technologies are especially meaningful. Introducing new technologies to society is difficult irrespective of the quantitative risks or benefits, due to the low familiarity of the technologies to the general public, which is associated with risk-averse attitudes. The proposed framework of information provision could be used to promote new technologies other than IT technologies.However, there were also several differences from the previous study. First, the message effect of TG2 for Yourself, not just for Future generations, was much stronger and statistically significant compared with CG. This may be because IT is a current hot topic that affects respondents directly via personal computers or smartphones, whereas the air pollution caused by industrialization investigated in the previous study is much improved and they rarely see relevant information in their daily life, even though they perceive the risks of the air pollution as much higher than those of IT innovations [These kinds of responses showing expectations of realistic benefits from AI are consistent with previous studies on public perception of AI risks. For example, Stephen Hawking’s warning about how we should handle AI technologies [Regarding the differences in personality effects on the pre-intervention attitudes and the attitude change, the relationship between the pre-intervention risk-averse attitudes and HEXACO measures (One of the most influential models for understanding technology acceptance, TAM [The boosted message effect of providing additional visual information with textual information in the present study may correspond to the multimedia effect [The balance of positive and negative sentences in the designed messages may also have mattered; the first two positive sentences were longer than the last single negative sentence, even in the CG. The message effect for the CG was not significantly different from 0 (