Country-Specific External Costs of Abiotic Resource Use Based on User Cost Model in Life Cycle Impact Assessment.

Abiotic resources are indispensable in society, but there are concerns regarding their depletion, scarcity, and increasing prices, resulting in potential economic damage in the future. To address these concerns, it is effective to consider the external costs of resource use. Although resource availability is different among mining sites, and local conditions are relevant in assessing resource scarcity, previous studies have assessed external costs and potential impacts of abiotic resource use globally. This study provides country-specific characterization factors (CFs) of abiotic resource use in life cycle impact assessment based on the user cost model, which represents the external costs of abiotic resource use to reflect country-specific resource scarcity. We demonstrate considerable variations in the CFs depending on the mining country, suggesting that the choice of mining country can affect external costs. The global external cost of abiotic resource use in 2020 was estimated at 1.9 trillion $, with a major contribution from the extraction of fossil fuels in the United States. Historical trends of the CFs and relevant parameters showed temporal fluctuations, emphasizing the importance of regularly updating the data underlying the calculation of the CFs. Country-level assessments of the external costs of resource use can contribute to discussions on the responsibilities of consuming countries by incorporating material footprint studies.

Association of COVID-19 information media, providers, and content with vaccine uptake among Tokyo residents.

To elucidate appropriate ways to induce behavior that prevents the spread of infection, we examined the association between COVID-19 vaccination and COVID-19-related information after more than 85% of the population had been vaccinated. Nonprobability quota sampling was used to recruit 2000 Tokyo residents as participants. The association between previous vaccine uptake and how much people thought they were affected by each of nine media, seven providers, and four content types of information was assessed using an online survey form. Subjective influence was assessed, and order logistic regression analyses were performed. We further calculated standardized partial regression coefficients for the independent variables. The results showed that while people did not think they were strongly affected by any COVID-19 information, significant positive associations between 9 of 20 variables, and significant negative associations between 7 of 20 variables were observed with vaccine uptake. The regression analysis involving the interaction terms between independent variables and sex showed a significant association between vaccine uptake and only daily conversation. Simple slope analysis showed a stronger positive association for females than for males. Regression analysis with interaction terms between each independent variable and age showed a significant association between vaccine uptake and print newspapers, social networking services, prefectural governors, family/relatives, accessibility, side effects, and supply visibility. Simple slope analysis also showed that the positive association between the subjective influence of newspapers and vaccine uptake was observed only for older people (≥69 years), and that of prefectural governors was more significant for older than younger people (≤32 years). In contrast, the trustworthy information provided by family/relatives was positively associated with vaccine uptake only for younger people. These results suggest that careful consideration must be given to the differences in age and sex to provide appropriate information that motivates Tokyo residents to receive vaccination during COVID-19 pandemic.

When people are defeated by artificial intelligence in a competition task requiring logical thinking, how do they make causal attribution?

Given that artificial intelligence (AI) has been predicted to eventually take on human tasks demanding logical thinking, it makes sense that we should examine psychological responses of humans when their performance is inferior to AI. Research has demonstrated that after people fail a task, whether they reorient their behavior towards success depends on what they attribute the failure to. This study investigated the causal attributions people made in a competition task requiring such thinking. We also recorded whether they wanted to re-challenge the games after they were defeated by AI. Experiments 1 (N = 74) and 2 (N = 788) recruited Japanese participants, while Experiment 3 (N = 500) comprised American participants. There were two conditions: in the first, participants competed against an AI opponent and in the other, they believed they were competing against a human. The results of the three experiments showed that participants attributed the loss to their own and their opponent's abilities more than any other factor, irrespective of the opponent type. The number of participants choosing to re-challenge the game did not differ significantly between the AI and human conditions in Experiments 1 and 3, although the number was lower in the AI condition than in the human condition in Experiment 2. Besides providing fresh insight on how people make causal attributions when competing against AI, our findings also predict how people will respond after their jobs are replaced by AI. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-021-02559-w.

A comparison of perceived effectiveness of preventive behaviors against COVID-19 between the public and medical experts: Not so different in means, but in distributions.

This brief report documents the results of a survey that measured the public's and doctors' perceived effectiveness of preventive behaviors against COVID-19, in Japan. Medical doctors (n = 117) and the general public (n = 1086) participated in our online survey. The results of the analysis of mean scores indicate that there were only slight differences in perceived effectiveness between the two groups, while the differences in distributions were remarkable. The results of Silverman's test suggest the unimodality of doctors' responses and multimodality of the public's responses. Implications of the findings to combat the risk of infection are discussed.

Responsibility of consumers for mining capacity: decomposition analysis of scarcity-weighted metal footprints in the case of Japan.

Metal-consuming countries depend on mining activity in other countries, which may impose potential pressure on sustainable metal supply. This study proposes an approach to analyze the responsibility of consuming countries for mining activities based on the decomposition analysis of scarcity-weighted metal footprints (S-MFs) of Japan. The application results to the Japanese final demand (iron, copper, and nickel) demonstrate the significance of country- and metal-specific conditions in terms of metal footprints and mining capacity in assessing the responsibility of consuming countries. Consuming countries can identify influential factors to reduce their S-MFs based on the decomposition analysis by discriminating the directly controllable and uncontrollable factors for consuming countries, which can help to plan different countermeasures depending on the types of the identified influential factors. The proposed approach supports metal-consuming countries to determine the effective options for reducing the responsibility for the sustainability of metal supply.

Trust in Autonomous Cars: Exploring the Role of Shared Moral Values, Reasoning, and Emotion in Safety-Critical Decisions.

OBJECTIVE: Autonomous cars (ACs) controlled by artificial intelligence are expected to play a significant role in transportation in the near future. This study investigated determinants of trust in ACs. BACKGROUND: Trust in ACs influences different variables, including the intention to adopt AC technology. Several studies on risk perception have verified that shared value determines trust in risk managers. Previous research has confirmed the effect of value similarity on trust in artificial intelligence. We focused on moral beliefs, specifically utilitarianism (belief in promoting a greater good) and deontology (belief in condemning deliberate harm), and tested the effects of shared moral beliefs on trust in ACs. METHOD: We conducted three experiments (N = 128, 71, and 196, for each), adopting a thought experiment similar to the well-known trolley problem. We manipulated shared moral beliefs (shared vs. unshared) and driver (AC vs. human), providing participants with different moral dilemma scenarios. Trust in ACs was measured through a questionnaire. RESULTS: The results of Experiment 1 showed that shared utilitarian belief strongly influenced trust in ACs. In Experiment 2 and Experiment 3, however, we did not find statistical evidence that shared deontological belief had an effect on trust in ACs. CONCLUSION: The results of the three experiments suggest that the effect of shared moral beliefs on trust varies depending on the values that ACs share with humans. APPLICATION: To promote AC implementation, policymakers and developers need to understand which values are shared between ACs and humans to enhance trust in ACs.

Why Do Japanese People Use Masks Against COVID-19, Even Though Masks Are Unlikely to Offer Protection From Infection?

Wearing masks against 2019 coronavirus (COVID-19) is beneficial in suppressing pandemic spread, not through preventing the wearer from being infected but by preventing the wearer from infecting others. Despite not providing much protection, the custom of wearing masks has prevailed in East Asia from the early stages of the pandemic, especially in Japan, to such an extent that it caused a shortfall in supply. Why do many Japanese people wear masks during the COVID-19 pandemic, even though masks are unlikely to prevent them from getting infected? We examined six possible psychological reasons for wearing masks: three involved expectations about the risk of infection and three involved other driving psychological forces. The results of our nationwide survey revealed that people conformed to societal norms in wearing masks and felt relief from anxiety when wearing masks. However, risk reduction expectations did not affect mask usage. The social psychological motivations successfully explained much about mask usage. Our findings suggest that policymakers responsible for public health should consider social motivations when implementing public strategies to combat the COVID-19 pandemic.