ArticleRoyal Society open science2026
Optimizing for happiness in EU technology policy to repay public subsidies for AI.
Article in Royal Society open science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Backlash against the artificial intelligence (AI) industry is growing globally in recognition of the high costs and highly uncertain risks borne by society. General-purpose AI systems are sold predominantly on the basis of economic benefits, with little attention given to social or non-financial benefits. Policymakers tasked with regulating AI while balancing European Union (EU) rights and values with innovation and free market competition face a seemingly impossible task. A change of priorities is urgently needed in EU tech policy. Current policy predominantly focuses on risk mitigation rather than delivering socially beneficial technologies. EU tech policy should be rebalanced in favour of societal interests owing to the substantial (in)direct subsidies paid to support the AI industry via tax breaks, public funding, privileged access to public lands, resources, data and infrastructure and widespread deregulation. We propose adding a third goal to rebalance EU AI policy-making: happiness. When policymakers are deciding whether subsidies should be granted for the AI industry, they should require companies to concretely predict measurable benefits for happiness, and hold them accountable for delivering on their predictions. To unpack this proposal, we examine decades of research in psychology to identify key determinants of happiness, focusing on three widely accepted traits: relatedness, competence and autonomy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.