arXiv subjects

Daniel W. O'Neill

Publications and source records attributed to Daniel W. O'Neill.

9 recordsLinked to original sources

arXiv2026

Towards post-growth policymaking: Barriers and enablers for wellbeing economy and Doughnut economics government initiatives

Providing wellbeing for all while safeguarding planetary boundaries requires governments to pursue post-growth policies. An important question is how transformative government-led post-growth initiatives can be within the existing institutional context. While first empirical studies on this question demonstrate some of the current limitations of government-led post-growth initiatives, a broader empirical assessment of underlying barriers and enablers across institutional contexts is so far lacking. To address this gap, we examine wellbeing economy and Doughnut economics government initiatives across governance scales in Europe, New Zealand, and Canada. To identify barriers and enablers as well as priorities for future action, we apply a framework that captures systemic and political dimensions to analyze the data. Overall, our results suggest that the overarching economic growth paradigm severely limits the initiatives scope of action. Important enablers of existing initiatives are crises, the political agency of key individuals and high-level political support. Policymakers who promote growth-critical perspectives often face tensions: they need to appeal to broad stakeholder groups while avoiding cooptation. Structural changes and a closer engagement with, and pressure from, civil society are required to support post-growth government initiatives.

econ.GN↗

arXiv2026

Change from within? The strategies used by public officials to advance post-growth approaches

Current societies face interconnected environmental and social crises. Post-growth research argues that addressing these challenges requires a reorganization of society around the priorities of environmental sustainability, social equity, and human wellbeing over economic growth. While scholars highlight the state's potential role in enabling post-growth transformations through changes from within government institutions, post-growth-minded public officials face tensions between aspiring for radical changes of established structures while working within these structures. To understand how public officials across contexts navigate this tension, we ask: How do post-growth-minded public officials promote post-growth approaches in their work? How do the strategies differ between civil servants and elected officials? What do these strategies reveal about the capacity of the state to advance post-growth transformations? To answer these questions, we interviewed 41 post-growth-minded civil servants and elected officials. Interviews covered seven European countries and local to supranational governance scales. We find that public officials aim to influence thinking and discourses as well as decision-making processes and the implementation of policies. Overall, elected officials tend to feel that they can be more outspoken in their activities whereas civil servants are more inclined to promote post-growth approaches indirectly. Both groups pursue coalitions with various actors within and beyond their institutions. Public officials strategies underscore the limited capacity of the state to advance post-growth approaches under the current growth paradigm. We suggest that cooperation with civil society actors is central to build a sense of collective agency and to foster the interactions between symbiotic and interstitial strategies for post-growth transformations.

econ.GN↗

arXiv2026

Modelling the Index of Sustainable Economic Welfare (ISEW) and its response to policies

Given the challenge of achieving societal welfare in an environmentally sustainable way, the Index of Sustainable Economic Welfare (ISEW) has emerged as an alternative indicator of progress in response to critiques of Gross Domestic Product (GDP). The ISEW compares the benefits of economic activity with its social and environmental costs. So far, most studies empirically analyse the ISEW for past developments, while no studies have simulated the ISEW using a dynamic macroeconomic model. We address this important gap by incorporating the ISEW into COMPASS, an ecological macroeconomic model that features the Doughnut of biophysical boundaries and social thresholds. First, we analyse how the ISEW is affected by three social and environmental policies: a carbon tax, income redistribution, and working-time reduction. We find that the ISEW grows in all scenarios. The strongest improvement over business-as-usual arises when all policies are combined, while the individual policies mostly affect the ISEW positively. Only in the case of working-time reduction, the ISEW decreases. Our study underscores the benefit of dynamically modelling the ISEW for anticipating the net effect of multiple impulses and their interconnections on the indicator. Second, we explore how the ISEW compares to GDP and the Doughnut when evaluating social and environmental policies. Our results suggest that the ISEW is better than GDP at capturing their effects, but it omits the full environmental costs of growth. We argue that the Doughnut, with its comprehensive picture of biophysical boundaries and social thresholds, provides better guidance for policymakers striving for sustainable wellbeing.

econ.GN↗

arXiv2026

The economic alignment problem of artificial intelligence

Artificial intelligence (AI) is advancing exponentially and is likely to have profound impacts on human wellbeing, social equity, and environmental sustainability. Here we argue that the "alignment problem" in AI research is also an economic alignment problem, as developing advanced AI within a growth-oriented economic system is likely to increase social, environmental, and existential risks. We show that post-growth research offers concepts and policies that could address the economic alignment problem and substantially reduce AI risks, such as by replacing optimisation with satisficing, using the Doughnut of social and planetary boundaries to guide development, and curbing systemic rebound with resource caps. We propose governance and business reforms that treat AI as a commons and prioritise tool-like autonomy-enhancing systems over agentic AI. Finally, we argue that the development of artificial general intelligence (AGI) requires new economic theories and models, for which post-growth scholarship provides a strong foundation.

econ.GN↗

arXiv2026

What is required for a post-growth model?

Post-growth has emerged as an umbrella term for various sustainability visions that advocate the pursuit of environmental sustainability, social equity, and human wellbeing, while questioning the continued pursuit of economic growth. Although there are increasing calls to include post-growth scenarios in high-level assessments, a coherent framework with what is required to model post-growth adequately remains absent. This article addresses this gap by: (1) identifying the minimum requirements for post-growth models, and (2) establishing a set of model elements for representing specific policy themes. Drawing on a survey of modellers and on relevant post-growth literature, we develop a framework of minimum requirements for post-growth modelling that integrates three spheres: biophysical, economic, and social, and links them to post-growth goals. Within the biophysical sphere, we argue that embeddedness requires the inclusion of resource use and pollution, environmental limits, and feedback mechanisms from the environment onto society. Within the economic sphere, models should disaggregate households, incorporate limits to technological change and decoupling, include different types of government interventions, and calculate GDP or output endogenously. Within the social sphere, models should represent time use, material and non-material need satisfiers, and the affordability of essential goods and services. Specific policies and transformation scenarios require additional features, such as sectoral disaggregation or representation of the financial system. Our framework guides the development of models that can simulate both post-growth and pro-growth policies and scenarios, an urgently needed tool for informing policymakers and stakeholders about the full range of options for pursuing sustainability, equity, and wellbeing.

econ.GN↗

arXiv2026

The impacts of artificial intelligence on environmental sustainability and human well-being

Artificial Intelligence (AI) is changing the world, but its impacts on the environment and human well-being remain uncertain. We conducted a systematic literature review of 1,291 studies selected from 6,655 records, identifying the main impacts of AI and how they are assessed. The evidence reveals an uneven landscape: 72% of environmental studies focus narrowly on energy use and CO2 emissions, while only 11% consider systemic effects. Well-being research is largely conceptual and overlooks subjective dimensions. Strikingly, 83% of environmental studies portray AI's impacts as positive, while well-being analyses show a near-even split overall (44% positive; 46% negative). However, this split masks differences across well-being dimensions. While the impacts of AI on income and health are expected to be positive, its impacts on inequality, social cohesion, and employment are expected to be negative. Based on our findings, we suggest several areas for future research. Environmental assessments should incorporate water, material, and biodiversity impacts, and apply a full life-cycle perspective, while well-being research should prioritise empirical analyses. Evaluating AI's overall impact requires accounting for computing-related, application-level, and systemic impacts, while integrating both environmental and social dimensions. Bridging these gaps is essential to understand the full scope of AI's impacts and to steer its development towards environmental sustainability and human flourishing.

cs.CY↗

arXiv2025

Modelling the Doughnut of social and planetary boundaries with frugal machine learning

The 'Doughnut' of social and planetary boundaries has emerged as a popular framework for assessing environmental and social sustainability. Here, we provide a proof-of-concept analysis that shows how machine learning (ML) methods can be applied to a simple macroeconomic model of the Doughnut. First, we show how ML methods can be used to find policy parameters that are consistent with 'living within the Doughnut'. Second, we show how a reinforcement learning agent can identify the optimal trajectory towards desired policies in the parameter space. The approaches we test, which include a Random Forest Classifier and $Q$-learning, are frugal ML methods that are able to find policy parameter combinations that achieve both environmental and social sustainability. The next step is the application of these methods to a more complex ecological macroeconomic model.

cs.LG↗

arXiv2025

Efficiency Will Not Lead to Sustainable Reasoning AI

AI research is increasingly moving toward complex problem solving, where models are optimized not only for pattern recognition but for multi-step reasoning. Historically, computing's global energy footprint has been stabilized by sustained efficiency gains and natural saturation thresholds in demand. But as efficiency improvements are approaching physical limits, emerging reasoning AI lacks comparable saturation points: performance is no longer limited by the amount of available training data but continues to scale with exponential compute investments in both training and inference. This paper argues that efficiency alone will not lead to sustainable reasoning AI and discusses research and policy directions to embed explicit limits into the optimization and governance of such systems.

cs.AI↗

arXiv2025

The labour and resource use requirements of a good life for all

We use multi-regional input-output analysis to calculate the paid labour, energy, emissions, and material use required to provide basic needs for all people. We calculate two different low-consumption scenarios, using the UK as a case study: (1) a "decent living" scenario, which includes only the bare necessities, and (2) a "good life" scenario, based on the minimum living standards demanded by UK residents. We compare the resulting footprints to the current footprint of the UK, and to the footprints of the US, China, India, and a global average. Labour footprints are disaggregated by sector, skill level, and region of origin. We find that neither low-consumption scenario provides a realistic path to providing a good life for all. While the decent living scenario would require only an 18-hour working week, and on a per capita basis, 35 GJ of energy use, 4.0 tonnes of emissions, and 5.5 tonnes of materials per year, it fails to provide essential needs. The good life scenario encompasses these needs, but would require a 46-hour working week, 73 GJ of energy use, 7.5 tonnes of emissions, and 13.2 tonnes of materials per capita. Both scenarios represent substantial reductions from the UK's current labour footprint of 65 hours per week, which the UK is only able to sustain by importing a substantial portion of its labour from other countries. We conclude that limiting consumption to the level of basic needs is not enough to achieve sustainability. Substantial changes to provisioning systems are also required.

econ.GN↗