Could Artificial Intelligence deliver a green transition?

Can AI boost current efforts and innovation to move towards a clean energy model? This is the question addressed by recent research aiming to further our understanding of AI’s role in the transition to low-carbon technologies. Marion Dumas, one of the authors of this research, discusses some of the key – and sometimes surprising – findings

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry’s transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry’s markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms

Directed technological change and general purpose technologies: can AI accelerate clean energy innovation?

Transitioning away from dirty and towards clean technologies is critical to reduce carbon emissions, but the race between clean and dirty technologies is taking place against the backdrop of improvements in general-purpose technologies (GPT) such as information and communication technologies (ICT) and artificial intelligence (AI). We show how, in theory, a GPT can affect the direction of technological change and, in particular, the competition between clean and dirty technologies. Second, we use patent data to show that clean technologies absorb more spillovers from AI and ICT than dirty technologies and that energy patenting firms with higher AI knowledge stocks are more likely to absorb AI spillovers for their energy inventions. We conclude that ICT and AI have the potential to accelerate clean energy innovation

When does reputation lie? Dynamic feedbacks between costly signals, social capital, and social prominence

Performing a dramatic act of religious devotion, creating an art exhibit, or releasing a new product are all examples of public acts that signal quality and contribute to building a reputation. Signalling theory predicts that these public displays can reliably reveal quality. However, data from ethnographic work in South India suggests that more prominent individuals gain more from reputation-building religious acts than more marginalized individuals. To understand this phenomenon, we extend signalling theory to include variation in people's social prominence or social capital, first with an analytical model and then with an agent-based model. We consider two ways in which social prominence/capital may alter signalling: (i) it impacts observers' priors, and (ii) it alters the signallers' pay-offs. These two mechanisms can result in both a 'reputational shield,' where low quality individuals are able to 'pass' as high quality thanks to their greater social prominence/capital, and a 'reputational poverty trap,' where high quality individuals are unable to improve their standing owing to a lack of social prominence/capital. These findings bridge the signalling theory tradition prominent in behavioural ecology, anthropology and economics with the work on status hierarchies in sociology, and shed light on the complex ways in which individuals make inferences about others. This article is part of the theme issue 'The language of cooperation: reputation and honest signalling'

Directed technological change and general purpose technologies: can AI accelerate clean energy innovation?

Transitioning away from dirty and towards clean technologies is critical to reduce carbon emissions, but the race between clean and dirty technologies is taking place against the backdrop of improvements in general-purpose technologies (GPT) such as information and communication technologies (ICT) and artificial intelligence (AI). We show how, in theory, a GPT can affect the direction of technological change and, in particular, the competition between clean and dirty technologies. Second, we use patent data to show that clean technologies absorb more spillovers from AI and ICT than dirty technologies and that energy patenting firms with higher AI knowledge stocks are more likely to absorb AI spillovers for their energy inventions. We conclude that ICT and AI have the potential to accelerate clean energy innovation

Three essays on political institutions and environmental governance

This dissertation analyzes how political competition and judicial institutions shape environmental governance in democratic societies. The three chapters frame environmental problems in several different ways. In the first chapter, environmental policy is framed as an ideologically contentious public good. In the second chapter, two conceptions are juxtaposed: the environment as just another policy domain subject to political haggling, or the environment as bringing about new fundamental commitments in society, prone to becoming constitutionalized through legal deliberation. In the third chapter, the dynamic properties of technological transitions toward more sustainable modes of production are emphasized. Different types of institutions are considered in the three chapters. The first two chapters examine how political and legal processes interact. They also consider the different ways in which they channel the inputs and wishes of civil society. Chapter one is a formal model of the institution of citizen suits – a prevalent institution in environmental governance – and its interaction with the legislature. It shows that the reshaping of laws by citizens and courts after their enactment by the legislature might improve the decision process of the legislature and the public good outcomes that ensue. Chapter two is an empirical analysis of the dynamics of environmental legal rules. It uses the network of citations to legal precedent to test whether the dynamic body of law governing the environment is driven by political shifts in power or follows a process that is autonomous from these shifts in power. The results suggest that environmental law is now constitutionalized – its main principles entrenched in democratic culture rather than subject to the ebb and flow of democratic turnover of power. Chapter three also considers the dynamic aspects of governance. It uses a computational model to examine how political parties with different ideological commitments towards renewable energy might strategically use the path-dependence of technological transitions to shape policy over the long-term. It also examines how electoral pressures might constrain or help them in this endeavor

Implementing EEG hyperscanning setups.

Hyperscanning refers to obtaining simultaneous neural recordings from more than one person (Montage et al., 2002 [1]), that can be used to study interactive situations. In particular, hyperscanning with Electroencephalography (EEG) is becoming increasingly popular since it allows researchers to explore the interactive brain with a high temporal resolution. Notably, there is a 40-year gap between the first instance that simultaneous measurement of EEG activity was mentioned in the literature (Duane and Behrendt, 1965 [2]), and the first actual description of an EEG hyperscanning setup being implemented (Babiloni et al., 2006 [3]). To date, specific EEG hyperscanning devices have not yet been developed and EEG hyperscanning setups are not usually described with sufficient detail to be easily reproduced. Here, we offer a step-by-step description of solutions to many of these technological challenges. Specifically, we describe and provide customized implementations of EEG hyperscanning setups using hardware and software from different companies: Brain Products, ANT, EGI, and BioSemi. •Necessary details to set up a functioning EEG hyperscanning protocol are provided.•The setups allow independent measures and measures of synchronization between the signals of two different brains.•Individual electrical Ground and Reference is obtained in all discussed systems

Spodoptera frugiperda (Lepidoptera: Noctuidae) host-plant variants: two host strains or two distinct species?

International audienceThe moth Spodoptera frugiperda is a well-known pest of crops throughout the Americas, which consists of two strains adapted to different host-plants: the first feeds preferentially on corn, cotton and sorghum whereas the second is more associated with rice and several pasture grasses. Though morphologically indistinguishable, they exhibit differences in their mating behavior, pheromone compositions, and show development variability according to the host-plant. Though the latter suggest that both strains are different species, this issue is still highly controversial because hybrids naturally occur in the wild, not to mention the discrepancies among published results concerning mating success between the two strains. In order to clarify the status of the two host-plant strains of S. frugiperda, we analyze features that possibly reflect the level of post-zygotic isolation: (1) first generation (F1) hybrid lethality and sterility; (2) patterns of meiotic segregation of hybrids in reciprocal second generation (F2), as compared to the meiosis of the two parental strains. We found a significant reduction of mating success in F1 in one direction of the cross and a high level of microsatellite markers showing transmission ratio distortion in the F2 progeny. Our results support the existence of post-zygotic reproductive isolation between the two laboratory strains and are in accordance with the marked level of genetic differentiation that was recovered between individuals of the two strains collected from the field. Altogether these results provide additional evidence in favor of a sibling species status for the two strains