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The increasing use of artificial intelligence (AI) systems in our daily lives through various applications, services, and products highlights the significance of trust and distrust in AI from a user perspective. AI-driven systems have significantly diffused into various aspects of our lives, serving as beneficial “tools” used by human agents. These systems are also evolving to act as co-assistants or semi-agents in specific domains, potentially influencing human thought, decision-making, and agency. Trust and distrust in AI serve as regulators and could significantly control the level of this diffusion, as trust can increase, and distrust may reduce the rate of adoption of AI. Recently, a variety of studies focused on the different dimensions of trust and distrust in AI and its relevant considerations. In this systematic literature review, after conceptualizing trust in the current AI literature, we will investigate trust in different types of human–machine interaction and its impact on technology acceptance in different domains. Additionally, we propose a taxonomy of technical (i.e., safety, accuracy, robustness) and non-technical axiological (i.e., ethical, legal, and mixed) trustworthiness metrics, along with some trustworthy measurements. Moreover, we examine major trust-breakers in AI (e.g., autonomy and dignity threats) and trustmakers; and propose some future directions and probable solutions for the transition to a trustworthy AI.

COVID-19 has prompted unprecedented government action around the world. We introduce the Oxford COVID-19 Government Response Tracker (OxCGRT), a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures. From 1 January 2020, the data capture government policies related to closure and containment, health and economic policy for more than 180 countries, plus several countries’ subnational jurisdictions. Policy responses are recorded on ordinal or continuous scales for 19 policy areas, capturing variation in degree of response. We present two motivating applications of the data, highlighting patterns in the timing of policy adoption and subsequent policy easing and reimposition, and illustrating how the data can be combined with behavioural and epidemiological indicators. This database enables researchers and policymakers to explore the empirical effects of policy responses on the spread of COVID-19 cases and deaths, as well as on economic and social welfare. The Oxford COVID-19 Government Response Tracker (OxCGRT) records data on 19 different government COVID-19 policy indicators for over 190 countries. Covering closure and containment, health and economics measures, it creates an evidence base for effective responses.

To what extent has the learning progress of school-aged children slowed down during the COVID-19 pandemic? A growing number of studies address this question, but findings vary depending on context. Here we conduct a pre-registered systematic review, quality appraisal and meta-analysis of 42 studies across 15 countries to assess the magnitude of learning deficits during the pandemic. We find a substantial overall learning deficit (Cohen's d = -0.14, 95% confidence interval -0.17 to -0.10), which arose early in the pandemic and persists over time. Learning deficits are particularly large among children from low socio-economic backgrounds. They are also larger in maths than in reading and in middle-income countries relative to high-income countries. There is a lack of evidence on learning progress during the pandemic in low-income countries. Future research should address this evidence gap and avoid the common risks of bias that we identify. (DIPF/Orig.).

Widespread acceptance of a vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will be the next major step in fighting the coronavirus disease 2019 (COVID-19) pandemic, but achieving high uptake will be a challenge and may be impeded by online misinformation. To inform successful vaccination campaigns, we conducted a randomized controlled trial in the UK and the USA to quantify how exposure to online misinformation around COVID-19 vaccines affects intent to vaccinate to protect oneself or others. Here we show that in both countries—as of September 2020—fewer people would ‘definitely’ take a vaccine than is likely required for herd immunity, and that, relative to factual information, recent misinformation induced a decline in intent of 6.2 percentage points (95th percentile interval 3.9 to 8.5) in the UK and 6.4 percentage points (95th percentile interval 4.0 to 8.8) in the USA among those who stated that they would definitely accept a vaccine. We also find that some sociodemographic groups are differentially impacted by exposure to misinformation. Finally, we show that scientific-sounding misinformation is more strongly associated with declines in vaccination intent. A randomized controlled trial reveals that exposure to recent online misinformation around a COVID-19 vaccine induces a decline in intent to vaccinate among adults in the UK and the USA.

The empirical science of subjective well-being, popularly referred to as happiness or satisfaction, has grown enormously in the past decade. In this Review, we selectively highlight and summarize key researched areas that continue to develop. We describe the validity of measures and their potential biases, as well as the scientific methods used in this field. We describe some of the predictors of subjective well-being such as temperament, income and supportive social relationships. Higher subjective well-being has been associated with good health and longevity, better social relationships, work performance and creativity. At the community and societal levels, cultures differ not only in their levels of well-being but also to some extent in the types of subjective well-being they most value. Furthermore, there are both universal and unique predictors of subjective well-being in various societies. National accounts of subjective well-being to help inform policy decisions at the community and societal levels are now being considered and adopted. Finally we discuss the unknowns in the science and needed future research. Diener et al. synthesize findings from psychology and economics on subjective well-being across cultures and identify outstanding questions, priorities for future research and pathways to policy implementation.

There is increasing concern that the coronavirus disease 2019 (COVID-19) pandemic could harm psychological health and exacerbate suicide risk. Here, based on month-level records of suicides covering the entire Japanese population in 1,848 administrative units, we assessed whether suicide mortality changed during the pandemic. Using difference-in-difference estimation, we found that monthly suicide rates declined by 14% during the first 5 months of the pandemic (February to June 2020). This could be due to a number of complex reasons, including the government’s generous subsidies, reduced working hours and school closure. By contrast, monthly suicide rates increased by 16% during the second wave (July to October 2020), with a larger increase among females (37%) and children and adolescents (49%). Although adverse impacts of the COVID-19 pandemic may remain in the long term, its modifiers (such as government subsidies) may not be sustained. Thus, effective suicide prevention—particularly among vulnerable populations—should be an important public health consideration. During the COVID-19 pandemic, suicide rates in Japan declined by 14% during the initial wave (February to June 2020) but increased by 16% in the second wave (July to October 2020), with a larger increase (37%) among females.

As the COVID-19 pandemic lingers, the possibility of ‘pandemic fatigue’ has raised worldwide concerns. Here, we examine whether there was a gradual reduction in adherence to protective behaviours against COVID-19 from March through December 2020, as hypothesized in expectations of fatigue. We considered self-report behaviours from representative samples of the populations of 14 countries ( N  = 238,797), as well as mobility and policy data for 124 countries. Our results show that changes in adherence were empirically meaningful and geographically widespread. While a low-cost and habituating behaviour (mask wearing) exhibited a linear rise in adherence, high-cost and sensitizing behaviours (physical distancing) declined, but this decline decelerated over time, with small rebounds seen in later months. Reductions in adherence to physical distancing showed little difference across societal groups, but were less intense in countries with high interpersonal trust. Alternative underlying mechanisms and policy implications are discussed. In the context of the COVID-19 pandemic, Petherick, Goldszmidt et al. show that, from March to December 2020, adherence to physical distancing fell worldwide, while mask-wearing adherence increased.

Reducing energy usage is important for climatechange mitigation. This Perspective focuses on the use and promise of agent-based modelling to understand the complexities of energy demand, including consumer behaviour. Strategies to mitigate global climate change should be grounded in a rigorous understanding of energy systems, particularly the factors that drive energy demand. Agent-based modelling (ABM) is a powerful tool for representing the complexities of energy demand, such as social interactions and spatial constraints. Unlike other approaches for modelling energy demand, ABM is not limited to studying perfectly rational agents or to abstracting micro details into system-level equations. Instead, ABM provides the ability to represent behaviours of energy consumers — such as individual households — using a range of theories, and to examine how the interaction of heterogeneous agents at the micro-level produces macro outcomes of importance to the global climate, such as the adoption of low-carbon behaviours and technologies over space and time. We provide an overview of ABM work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of both fundamental scientific and applied aspects of the demand side of energy to aid the design of better policies and programmes. Future research needs for improving the practice of ABM to better understand energy demand are also discussed.

Water resources are essential for every development activity, not only in terms of available quantity but also in terms of quality. Population growth and urbanisation are increasing the number of users and uses of water, making water resources scarcer and more polluted. Changes in rainfall patterns threaten to worsen these effects in many areas. Water scarcity, due to physical lack or pollution, has become one of the most pressing issues globally, a matter of human, economic and environmental insecurity. Wastewater, whose value had not been appreciated until recently, is increasingly recognised as a potential ‘new’ source of clean water for potable and non-potable uses, resulting in social, environmental and economic benefits. This paper discusses the potential of recycled wastewater (also known as reused water) to become a significant source of safe water for drinking purposes and improved sanitation in support of the Sustainable Development Goals.

Since 2013, China has initiated a rapid energy transition that replaces traditional solid fuels with modern clean energy. Despite the tremendous success of the energy transition, its impacts on household energy costs and associated energy inequality remain largely unexplored. Here we use data from a large nationwide household survey to investigate these trends. We find that about two-fifths (43.0%) of surveyed households switched from traditional solid fuels to clean energy during 2013–2017. However, 56.1% to ~61.0% of them were from extremely poor or poor households, causing deep concern for increasing household energy burden. Accordingly, the share of surveyed households in energy poverty increased from 30.1% to 34.2%. Despite the declining inequality in energy cost, a growing inequality in energy burden was revealed during 2013–2017. Our results demonstrate that the energy burden on rural households increased due to the dramatic rise in the cost of clean energy, while urban households tend to spend a lower and decreased proportion of their income on energy. Between 2013 and 2017, China enacted a series of policies to improve air quality by promoting a switch to cleaner fuels for households. This study examines the changes in energy cost and associated energy burden across regions and income groups during this period, finding an increased burden on rural households.