This paper takes the Court of the Bank of England's Terms of Reference for the Bernanke Review seriously. We explore the underlying issue of radical uncertainty and what this means for forecasting and monetary policy-making. The only logical way to proceed is to embrace Bernanke's suggestion that we engage 'alternative modelling frameworks'. What might these be? We need a combination of different types of models, some with closed equilibrium solutions and others that rely on simulations that can provide different insights into what is happening in the economy. The old saying that 'it takes a model to beat a model' is just that. We now know that Agent Based Models can perform at least as well as equilibrium models, even on the latter's own narrow criteria, despite the fraction of resources used in their development. If the Bank is to serve its mission of 'promoting the good of the people of the UK' it must start by accepting reality and not limiting itself to a single model framework as if it will somehow deliver 'the truth' if only it had more resources. (c) 2025 Published by Elsevier B.V. on behalf of International Institute of Forecasters.

Economic and labour policies have a considerable influence on health and well-being through direct financial impacts, and by shaping social and physical environments. Strong economies are important for public health investment and employment, yet the rapid rise of generative artificial intelligence (AI) has the potential to reshape economies, presenting challenges beyond mere temporary market disruption. Generative AI can perform non-routine cognitive tasks, previously unattainable though traditional automation, creating new efficiencies. While this technology offers opportunities for innovation and productivity, its labour-displacing potential raises serious concerns about economic stability and social equity, both of which are critical to health. Job displacement driven by generative AI could worsen income inequality, shrink middle-class opportunities and reduce consumer demand, triggering recessionary pressures. In this article, we propose the existence of an AI-capital-to-labour ratio threshold beyond which a self-reinforcing cycle of recessionary pressures may emerge, and which market forces alone cannot correct. Traditional responses to such pressures, like fiscal stimulus or monetary easing, may be ineffective in addressing structural disruptions to labour markets caused by generative AI. We call for a proactive global response to harness the benefits of generative AI while mitigating risks. This response should focus on reorienting economic systems towards collective well-being, as emphasized in the World Health Assembly resolution Economics of health for all and the United Nations' Global Digital Compact. Integrated strategies that combine fiscal policy, regulation and social policies are critical to ensuring generative AI advances societal health and equity while avoiding harm from excessive job displacement.

The 2024 Lancet Commission Report on dementia prevention has identified 14 modifiable risk factors that account for approximately 45% of global dementia cases. We used a global multidimensional approach that integrates gender equity considerations, poverty, wealth shocks, income inequality and HIV infection rates to identify additional risk factors beyond those reported in 2024 report. This methodological framework aims to enhance equitable prevention strategies to mitigate the global burden of dementia. We demonstrate that adding four additional risk factors: poverty, wealth shocks, income inequality, and HIV, while also considering the influences of sex and gender will improve the global applicability of the 2024 report. This is important because, despite dementia primarily affecting women, 57% of the risk factors identified in the 2024 report are more prevalent in men. Our analysis suggests that incorporating these four additional factors could potentially increase the proportion of preventable dementia cases to about 65%. This approach would also reshape the understanding of dementia risk, indicating that around 56% of modifiable risks disproportionately impact women. Expanding risk models in this manner is crucial for developing equitable and effective global dementia prevention strategies, particularly in underrepresented regions. We present these considerations as enhancements to the Commission's significant work.

Work is fundamental to societal prosperity and mental health, providing financial security, a sense of identity and purpose, and social integration. Job insecurity, underemployment and unemployment are well-documented risk factors for mental health issues and suicide. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement and its corollary impacts on individual and social wellbeing. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupling of economic productivity from human input threatening jobs on an unprecedented scale. This study explores the conditions under which both may be true and examines the potential for a self-reinforcing cycle of recessionary pressures that would necessitate sustained government intervention to maintain job security and economic stability. A system dynamics model was developed to undertake ex ante analysis of the effect of AI-capital deepening on labour underutilisation and demand in the economy using Australian data as a case study. Results indicate that even a moderate increase in the AI-capital-to-labour ratio could increase labour underutilisation to double its current level, decrease per capita disposable income by 26% (95% interval, 20.6-31.8%), and decrease the consumption index by 21% (95% interval, 13.6-28.3%) by mid-2050. To prevent a reduction in per capita disposable income due to the estimated increase in underutilization, at least a 10.8-fold increase in the new job creation rate would be necessary. Results demonstrate the feasibility of an AI-capital-to-labour ratio threshold beyond which even high rates of new job creation cannot prevent declines in consumption. The precise threshold will vary across economies, emphasizing the urgent need for empirical research tailored to specific contexts. This study underscores the need for cross-sectoral government measures to ensure a smooth transition to an AI-dominated economy to safeguard the Mental Wealth of nations.

Despite increased advocacy and investments in mental health systems globally, there has been limited progress in reducing mental disorder prevalence. In this paper, we argue that meaningful advancements in population mental health necessitate addressing the fundamental sources of shared distress. Using a systems perspective, economic structures and policies are identified as the potential cause of causes of mental ill-health. Neoliberal ideologies, prioritizing economic optimization and continuous growth, contribute to the promotion of individualism, job insecurity, increasing demands on workers, parental stress, social disconnection and a broad range of manifestations well-recognized to erode mental health. We emphasize the need for mental health researchers and advocates to increasingly engage with the economic policy discourse to draw attention to mental health and well-being implications. We call for a shift towards a well-being economy to better align commercial interests with collective well-being and social prosperity. The involvement of individuals with lived mental ill-health experiences, practitioners and researchers is needed to mobilize communities for change and influence economic policies to safeguard well-being. Additionally, we call for the establishment of national mental wealth observatories to inform coordinated health, social and economic policies and realize the transition to a more sustainable well-being economy that offers promise for progress on population mental health outcomes.

The uncertainty that marks adolescence and early adulthood is heightened by the simultaneous crises of mental health, education and youth unemployment. This puts the brain capital of young people under threat. We must invest in youth brain health and skills that are orientated towards environmental sustainability. This can train future creatives to develop impactful solutions to the current climate crisis as well as develop citizens who are ecologically intelligent and willing to enact environmentally sustainable and resilient behaviors. In effect, we propose a youth green brain capital model. This approach aims to refine and advance this agenda, including specific policy innovations, new investment approaches, and the development of a dashboard of instruments to track green brain capital. Our vision is to empower the next generation with ecologically intelligent leadership skills to address the pressing challenges of the climate crisis.

The coming years are likely to be turbulent due to a myriad of factors or polycrisis, including an escalation in climate extremes, emerging public health threats, weak productivity, increases in global economic instability and further weakening in the integrity of global democracy. These formidable challenges are not exogenous to the economy but are in some cases generated by the system itself. They can be overcome, but only with far-reaching changes to global economics. Our current socio-economic paradigm is insufficient for addressing these complex challenges, let alone sustaining human development, well-being and happiness. To support the flourishing of the global population in the age of polycrisis, we need a novel, person-centred and collective paradigm. The brain economy leverages insights from neuroscience to provide a novel way of centralising the human contribution to the economy, how the economy in turn shapes our lives and positive feedbacks between the two. The brain economy is primarily based on Brain Capital, an economic asset integrating brain health and brain skills, the social, emotional, and the diversity of cognitive brain resources of individuals and communities. People with healthy brains are essential to navigate increasingly complex systems. Policies and investments that improve brain health and hence citizens' cognitive functions and boost brain performance can increase productivity, stimulate greater creativity and economic dynamism, utilise often underdeveloped intellectual resources, afford social cohesion, and create a more resilient, adaptable and sustainability-engaged population.

Optimal brain health is essential to smoothing major global skill-intensive economic transitions, such as the bioeconomy, green, care economy and digital transitions. Good brain health is vital to socio-economic sustainability, productivity and well-being. The care transition focuses on recognizing and investing in care services and care work as essential for economic growth and social well-being. The green transition involves shifting towards environmentally sustainable and fairer societies to combat climate change and environmental degradation. The digital transition aims to unlock digital growth potential and deploy innovative solutions for businesses and citizens, and to improve the accessibility and efficiency of services. The bioeconomy transition refers to the shift towards an economy based on products, services and processes derived from biological resources, such as plants and microorganisms. Brain capital, which encompasses brain health and brain skills, is a critical economic asset for the success of economies of the future. The brain economy transition from a brain-negative (brain-unhealthy) economy, which depletes brain capital, to a brain-positive (brain-healthy) economy, which arrests and reverses the loss of brain capital, will be foundational to these major transitions. Increased brain capital is vital to educational attainment, upskilling and reskilling. In this paper, we provide a detailed roadmap for the brain economy transition.

This paper aims to contribute to current efforts to improve methodologies to find more ambitious and integrated strategies to jointly pursue the Paris climate target and other Sustainable Development Goals. It suggests a means of further expanding the underlying societal perspectives in scenarios modelling through a model of deep institutional innovation for sustainability and human development (DIIS), which aims to reframe the narrative from sociotechnical transition to deep global cultural transformation. The paper posits the need for capturing irreversible transformation change through a fundamental reimagining of the key social institutions that together comprise contemporary societies. To illustrate the application of the DIIS framing to pathway scenarios an indicative scenario is offered to indicate the radical global cultural changes required to move to pathways capable of bringing about greater sustainability and human flourishing.

Work is fundamental to societal prosperity and mental health, providing financial security, identity, purpose, and social integration. The emergence of generative artificial intelligence (AI) has catalysed debate on job displacement. Some argue that many new jobs and industries will emerge to offset the displacement, while others foresee a widespread decoupling of economic productivity from human input threatening jobs on an unprecedented scale. This study explores the conditions under which both may be true and examines the potential for a self-reinforcing cycle of recessionary pressures that would necessitate sustained government intervention to maintain job security and economic stability. A system dynamics model was developed to undertake ex ante analysis of the effect of AI-capital deepening on labour underutilisation and demand in the economy. Results indicate that even a moderate increase in the AI-capital-to-labour ratio could increase labour underutilisation to double its current level, decrease per capita disposable income by 26

In the grand narrative of technological evolution, we are transitioning from the ‘Age of Information’ to the ‘Age of Intelligence.’ Rapid advancements in generative artificial intelligence (AI) are set to reshape society, revolutionize industries, and change the nature of work, challenging our traditional understanding of the dynamics of the economy and its relationship with human productivity and societal prosperity. As we brace for this transformative shift, promising advancements in healthcare, education, productivity, and more, there are concerns of large-scale job loss, mental health repercussions, and risks to social stability and democracy. This paper proposes the concept of Mental Wealth as an action framework that supports nations to proactively position themselves for a smooth transition to the Age of Intelligence while fostering economic and societal prosperity.

As your Editorial1 noted, sustainable development demands brain health. However, this Editorial also showed that brain health is primarily relevant for only one of the existing goals of the current UN agenda, namely the Sustainable Development Goal (SDG) 3: improving health and wellbeing. Given that brain health and skills are crucial to the economy and society, we seek a more comprehensive approach. Furthermore, the UN's SDG progress is in peril; therefore, a transformative approach seems to be a necessity.

This NeuroView assesses the interplay among exposome, One Health, and brain capital in health and disease. Physical and social exposomes affect brain health, and green brain skills are required for environmental health strategies. Ibanez et al. address current gaps and strategies needed in research, policy, and technology, offering a road map for stakeholders.

Despite ample research demonstrating the developmental and clinical importance of psychosocial competencies (e.g., prosociality, attention regulation, compliance to caregivers) in early childhood, few measures exist that are clinically relevant, developmentally appropriate, psychometrically validated, and pragmatic to administer, score, and interpret. One promising option is the Psychosocial Strengths Inventory for Children and Adolescents (PSICA), a parent-report measure of affective, attentional, and social competencies in youth. Although the PSICA has growing psychometric support, it remains a relatively lengthy measure (i.e., 36 items). Thus, we sampled 865 community caregivers (75

Generative Artificial Intelligence (AI) stands as a transformative force that presents a paradox; it offers unprecedented opportunities for productivity growth while potentially posing significant threats to economic stability and societal wellbeing. Many consider generative AI as akin to previous technological advancements, using historical precedent to argue that fears of widespread job displacement are unfounded, while others contend that generative AI`s unique capacity to undertake non-routine cognitive tasks sets it apart from other forms of automation capital and presents a threat to the quality and availability of work that underpin stable societies. This paper explores the conditions under which both may be true. We posit the existence of an AI-capital-to-labour ratio threshold beyond which a self-reinforcing cycle of recessionary pressures could be triggered, exacerbating social disparities, reducing social cohesion, heightening tensions, and requiring sustained government intervention to maintain stability. To prevent this, the paper underscores the urgent need for proactive policy responses, making recommendations to reduce these risks through robust regulatory frameworks and a new social contract characterised by progressive social and economic policies. This approach aims to ensure a sustainable, inclusive, and resilient economic future where human contribution to the economy is retained and integrated with generative AI to enhance the Mental Wealth of nations.

Apart from security issues, war-torn societies and countries face immense challenges in rebuilding damaged critical infrastructure. Existing post-conflict recovery frameworks mainly focus on social impacts and mitigation. Also, existing frameworks for resilience to natural hazards are mainly based on design and intervention, yet, they are not fit for post-conflict infrastructure recovery for a number of reasons explained in this paper. Post-conflict peacebuilding can be enhanced when resilience by assessment (RBA) is employed, using standoff observations that include data from disparate remote-sensing sources, e.g. public satellite imagery, forensics and crowd -sourcing, collected during the conflict. This paper discusses why conflicts and warfare require a new framework for achieving post-conflict infrastructure resilience. It then introduces a novel post-conflict framework that in-cludes different scales of resilience with a focus on asset and regional resilience. It considers different levels of knowledge, with a focus on standoff observations and data-driven assessments to facilitate prioritisation during reconstruction. The framework is then applied to the transport network of the area west of Kyiv, Ukraine to demonstrate how resilience by assessment can support decision-makers, such as governments and multilateral financial institutions, to address infrastructure needs and accelerate financial and humanitarian assistance, absorb shocks and maximise infrastructure recovery after conflict.

There is a growing global movement among economic, public policy and academic communities questioning the appropriateness of gross domestic product (GDP), and specifically its growth, as an indicator of progress. Despite the broad range of indices and dashboards that have been developed to challenge it, GDP remains entrenched as the essential indicator of national prosperity, despite its purpose being to measure the size and performance of the economy. The strength of GDP lies in its established centrality in policymaking as well as its rhetorical and conceptual simplicity; it is in essence the value of monetized tangible goods and services produced in a given period. Unlike well-being indicator dashboards, GDP provides a single measure against which governments, the media and the general community can track and compare national economic performance. And, while many composite indices offer monotonously stable findings, the weekly, quarterly and annual fluctuations of GDP prompt policymakers to act (that is, to assess reforms, identify constraints and shift policy levers to enhance its growth). By contrast, the Mental Wealth metric offers a new approach. Rather than joining the chorus of moving beyond GDP, the Mental Wealth Initiative first recognises the system of national accounts that underpins GDP as a significant human achievement. The initiative then seeks to refine, augment and improve GDP as a measure of social welfare by broadening the boundary of production to include the value of goods and services provided by populations that are not currently monetized but make genuine contributions to social prosperity and quality of life. Hence, the Mental Wealth metric provides a holistic measure of national prosperity, capturing the value of both economic and social production, and recognizing the fundamental importance of brain capital (mental capital, mental health and brain health) and collective cognitive and emotional health and well-being. This paper provides a simple, practical strategy for augmenting GDP by monetizing social production, thereby establishing a more accurate indicator of the wealth of nations. Occhipinti and co-authors argue in this Perspective that by contrast to gross domestic product, the Mental Wealth metric provides an improved indicator for assessing economic and social production, including brain capital, measuring mental health and capital and emotional health and well-being.

Correspondence to Professor JoAn Occhipinti; joan. occhipinti@ sydney. edu. au © Author(s) (or their employer(s)) 2023. Reuse permitted under CC BYNC. No commercial reuse. See rights and permissions. Published by BMJ. InTroduCTIon Countries face dynamic, multidimensional and interconnected crises. The pandemic, climate change, rising inequalities, food and energy insecurity, polarisation, misinformation and declining trends in youth mental health, are converging to cause enormous sociopolitical and economic consequences that are weakening democracies, corroding the social fabric of communities, and posing threats to social stability and national security. A Mental Wealth perspective argues that the extent to which nations can respond to these polycrises depends on the quality of, and investments in, a critical national asset: brain capital. Brain capital encompasses a nation’s cognitive and emotional resources including (1) brain skills—cognitive capability, emotional intelligence and the ability to collaborate, be innovative and solve complex problems, (2) brain health which includes mental health, wellbeing and neurological disorders that critically impact the ability to deploy brain skills effectively, build and maintain positive relationships, and display resilience against challenges and uncertainties. Although brain skills and brain health are commonly examined at an individual level, brain capital represents a broader, collective concept and national asset that is a fundamental contributor to economic and social productivity (Mental Wealth—box 1). The aim of this paper is to provide a systemic perspective on the interdependencies between brain capital (particularly mental health), economic and social wellbeing, and resilience. By transcending traditional disciplinary boundaries, the paper explores the drivers and potential strategies for enhancing systemic resilience. As global health researchers endeavour to improve health outcomes and foster more resilient societies, and business and economic policy audiences seek to promote productivity and economic prosperity, this paper advocates for a more interconnected approach. It urges global public health and business audiences Summary box

Critical infrastructure is vulnerable to systemic long-term stressors such as climate change, as well as shocks from extreme weather events, economic disruptions, and cyber failures.The complexity and interdependencies across critical infrastructure domains makes it susceptible to cascading failures, with the SARS-CoV-2 pandemic is the most recent example of disruptions in supply chains, healthcare and emergency facilities.Stress testing offers a conceptual framework and methodology for identifying risks associated with cascading failures and selecting mitigation and recovery strategies.This paper reviews the fundamentals of stress-testing science and practice in different fields (medicine, engineering, economics) and identifies challenges associated with the application of existing methodologies to infrastructure systems.The currently practiced risk-based stress testing approaches may only be of limited use because they merely aim to identify the components of failing systems by varying stress loads.Adding a systems-thinking perspective and consideration of interconnectedness across system domains facilitates resilience stress testing (i.e., the impact of disruptions on the system's ability to recover and adapt).We propose combining risk and resilience stress testing into a tiered approach applicable to complex, interconnected infrastructure.

Adaptive capacity is a critical component of building resilience in healthcare (RiH). Adaptive capacity comprises the ability of a system to cope with and adapt to disturbances. However, "shocks," such as the current coronavirus disease 2019 (COVID-19) pandemic, can potentially exceed critical adaptation thresholds and lead to systemic collapse. To effectively manage healthcare systems during periods of crises, both adaptive and transformative changes are necessary. This commentary discusses adaptation and transformation as two complementary, integral components of resilience and applies them to healthcare. We treat resilience as an emergent property of complex systems that accounts for multiple, often disparately distinct regimes in which multiple processes (eg, adaptation, recovery) are subsumed and operate. We argue that Convergence Mental Health and other transdisciplinary paradigms such as Brain Capital and One Health can facilitate resilience planning and management in healthcare systems.