Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

Collaborative learning techniques have the potential to enable training machine learning models that are superior to models trained on a single entity's data. However, in many cases, potential participants in such collaborative schemes are competitors on a downstream task, such as firms that each aim to attract customers by providing the best recommendations. This can incentivize dishonest updates that damage other participants' models, potentially undermining the benefits of collaboration. In this work, we formulate a game that models such interactions and study two learning tasks within this framework: single-round mean estimation and multi-round SGD on strongly-convex objectives. For a natural class of player actions, we show that rational clients are incentivized to strongly manipulate their updates, preventing learning. We then propose mechanisms that incentivize honest communication and ensure learning quality comparable to full cooperation. Lastly, we empirically demonstrate the effectiveness of our incentive scheme on a standard non-convex federated learning benchmark. Our work shows that explicitly modeling the incentives and actions of dishonest clients, rather than assuming them malicious, can enable strong robustness guarantees for collaborative learning.Comment: Accepted to NeurIPS 2023; 37 pages, 5 figure

Self-serving Bias in Redistribution Choices: Accounting for Beliefs and Norms

People with higher-incomes tend to support less redistribution than lower-income people. This has been attributed not only to self-interest, but also to psychological mechanisms including differing beliefs about the hard work or luck underlying inequality, differing fairness views, and differing perceptions of social norms. In this study, we directly measure each of these mechanisms and compare their mediating roles in the relationship between status and redistribution. In our experiment, participants complete real-effort tasks and then are randomly assigned a high or low pay rate per correct answer to exogenously induce (dis)advantaged status. Participants are then paired and those assigned the role of dictator decide how to divide their joint earnings. We find that advantaged dictators keep more for themselves than disadvantaged dictators and report different fairness views and beliefs about task performance, but not different beliefs about social norms. Further, only fairness views play a significant mediating role between status and allocation differences, suggesting this is the primary mechanism underlying self-serving differences in support for redistribution

A long-term outlook on Russian oil industry facing internal and external challenges

International audienceRussian petroleum industry plays a vital part in both the country’s economy and international hydrocarbon market, providing a third of state budget revenues and over 13% of global liquid hydrocarbon exports. Yet, nowadays the industry is facing a number of serious challenges, which threaten to undermine its sustainability. These challenges include depletion of the conventional oil resources, technological and economic sanctions and stagnating demand for liquid fuels, especially apparent in Russian traditional export destinations – Europe. The authors attempted to evaluate the impact of these issues and compile a forecast of Russian oil industry using state-of-the-art modelling tools. The calculations show, that even under fairly negative scenario assumptions, Russia is capable of maintaining crude oil and refined products exports above 250 mtoe up to 2040, remaining the world’s second liquid hydrocarbon supplier. This, however, is still a huge drop from 425 mtoe of exports in 2018. To ensure sustainability the government and oil companies need to work in conjunction in several fields: facilitate geologic survey of conventional and promising oil and gas basins; domestic development of new oil extraction technologies for accessing unconventional and low-margin oil resources; provide transport infrastructure for remote fields; reforming tax system to better suit the new environment. This way, crude production can be maintained above 500 mtoe in the forecast period and exports even surpass 2018 levels. In any case, however, the need for massive investments and tax incentives coupled with global movement away from fossil fuels means, that in the future oil will be becoming less and less profitable for the state budget, thus Russian government needs to redouble efforts on economic diversification and energy transition

Why is China's wind power generation not living up to its potential?

Following a decade of unprecedented investment, China now has the world's largest installed base of wind power capacity. Yet, despite siting most wind farms in the wind-rich Northern and Western provinces, electricity generation from Chinese wind farms has not reached the performance benchmarks of the United States and many other advanced economies. This has resulted in lower environmental, economic, and health benefits than anticipated. We develop a framework to explain the performance of the Chinese and US wind sectors, accounting for a comprehensive set of driving factors. We apply this framework to a novel dataset of virtually all wind farms installed in China and the United States through the end of 2013. We first estimate the wind sector's technical potential using a methodology that produces consistent estimates for both countries. We compare this potential to actual performance and find that Chinese wind farms generated electricity at 37%–45% of their annual technical potential during 2006–2013 compared to 54%–61% in the United States. Our findings underscore that the larger gap between actual performance and technical potential in China compared to the United States is significantly driven by delays in grid connection (14% of the gap) and curtailment due to constraints in grid management (10% of the gap), two challenges of China's wind power expansion covered extensively in the literature. However, our findings show that China's underperformance is also driven by suboptimal turbine model selection (31% of the gap), wind farm siting (23% of the gap), and turbine hub heights (6% of the gap)—factors that have received less attention in the literature and, crucially, are locked-in for the lifetime of wind farms. This suggests that besides addressing grid connection delays and curtailment, China will also need policy measures to address turbine siting and technology choices to achieve its national goals and increase utilization up to US levels

Enablers of Excess: Mutual Funds & the Overpaid American CEO

[Excerpt] In this report, the American Federation of State, County and Municipal Employees (AFSCME), AFL-CIO, and The Corporate Library (TCL) examine mutual fund proxy voting on executive compensation issues. Our purpose is to determine the extent to which mutual funds have exercised their responsibility to vote in their shareholders’ best interests on measures that would reasonably restrain executive compensation and link CEO pay more closely to company performance. Recent media coverage has increased public understanding about the outrageously high pay packages afforded to company executives, independent of their performance. To date, however, little attention has been paid to the worst enablers of this trend—the largest institutional investors, who possess a unique opportunity to exert influence over a board’s executive pay decisions through their formidable voting power

Realizing the potential of distributed energy resources and peer-to-peer trading through consensus-based coordination and cooperative game theory

Driven by environmental and energy security concerns, a large number of small-scale distributed energy resources (DERs) are increasingly being connected to the distribution network. This helps to support a cost-effective transition to a lower-carbon energy system, however, brings coordination challenges caused by variability and uncertainty of renewable energy resources (RES). In this setting, local flexible demand (FD) and energy storage (ES) technologies have attracted great interests due to their potential flexibility in mitigating the generation and demand variability and improving the cost efficiency of low-carbon electricity systems. The combined effect of deregulation and digitalization inspired new ways of exchanging electricity and providing management/services on the paradigm of peer-to-peer (P2P) and transparent transactions. P2P energy trading enables direct energy trading between prosumers, which incentivizes active participation of prosumer in the trading of electricity in the distribution network, in the meantime, the efficient usage of FD and ES owned by the prosumers also facilitates better local power and energy balance. Though the promising P2P energy trading brings numerous advancements, the existing P2P mechanisms either fail to coordinate energy in a fully distributed way or are unable to adequately incentivize prosumers to participate, preventing prosumers from accessing the highest achievable monetary benefits and/or suffering severely from the curse of dimensionality. Therefore, this thesis aims at proposing three P2P energy trading enabling mechanisms in the aspect of fully distributed efficient balanced energy coordination through consensus-based algorithm and two incentivizing pricing and benefit distribution mechanisms through cooperative game theory. Distributed, consensus-based algorithms have emerged as a promising approach for the coordination of DER due to their communication, computation, privacy and reliability advantages over centralized approaches. However, state-of-the-art consensus-based algorithms address the DER coordination problem in independent time periods and therefore are inherently unable to capture the time-coupling operating characteristics of FD and ES resources. This thesis demonstrates that state-of-the-art algorithms fail to converge when these time-coupling characteristics are considered. In order to address this fundamental limitation, a novel consensus-based algorithm is proposed which includes additional consensus variables. These variables express relative maximum power limits imposed on the FD and ES resources which effectively mitigate the concentration of the FD and ES responses at the same time periods and steer the consensual outcome to a feasible and optimal solution. The convergence and optimality of the proposed algorithm are theoretically proven while case studies numerically demonstrate its convergence, optimality, robustness to initialization and information loss, and plug-and-play adaptability. Moreover, this thesis proposes two computationally efficient pricing and benefit distribution mechanisms to construct a stable grand coalition of prosumers participating in P2P trading, founded on cooperative game-theoretic principles. The first one involves a benefit distribution scheme inspired by the core tatonnement process while the second involves a novel pricing mechanism based on the solution of single linear programming. The performance of the proposed mechanisms is validated against state-of-the-art mechanisms through numerous case studies using real-world data. The results demonstrate that the proposed mechanisms exhibit superior computational performance than the nucleolus and are superior to the rest of the examined mechanisms in incentivizing prosumers to remain in the grand coalition.Open Acces

The Consistency of Fairness Rules: An Experimental Study

In the last two decades, experimental papers on distributive justice have abounded. Two main results have been replicated Firstly, there is a multiplicity of fairness rules. Secondly, fairness decisions differ depending on the context. This paper studies individual consistency in the use of fairness rules, as well as the structural factors that lead people to be inconsistent. We use a within-subject design, which allows us to compare individual behavior when the context changes. In line with the literature, we find a multiplicity of fairness rules. However, when we control for consistency, the set of fairness rules is considerably smaller. Only selfishness and strict egalitarianism seem to survive the stricter requirement of consistency. We observe that this result is mainly explained by a self-serving bias. Participants select the rule that is individually optimal in each situation.Justice, Fairness, Laboratory Experiments, Self-serving bias, Consistency

Conceptualizing Blockchain in The Music Industry

As blockchain technology continues to evoke interest and engagement across companies, organizations, industries, and governments, the desire to integrate the technology is evident. The discussion around blockchain often implies promises of decentralization, transparency, and disruption. The music industry specifically has been noted to potentially gain from the implementation of blockchain, making it a great context for exploration: the industry is constructed of multiple stakeholders with complicated and often dysfunctional connections. This research aims to understand how blockchain is utilized in the context of music industry. It distinctively tries to understand the technical structure of the applied blockchain, the implications to business logic and structures, and lastly the long-term intersection of blockchain and the music industry. This research was conducted as a qualitative multiple-case study. With an inductive and intensive approach, the objective was to explore the use of blockchain in a holistic nature from the perspective of each case. The empirical data was collected from secondary whitepapers published by each case company. Each whitepaper detailed the technical and the business structure as it pertains to blockchain. The data revealed how blockchain governs engagement and the positioning of each stake-holder in the ecosystem and in relation to each other in the presence, or lack thereof, of blockchain. It was concluded that blockchain can be utilized in varying ways and to varying degrees. The consequential effects can be observed in the governance, structure, and business logic of each case, which this research showcases in detail. While this research was able to provide differing possibilities for use, it could not provide evidence of blockchain being mature enough for mass adoption, supporting arguments presented in previous research and theory.Blockchain-teknologian noustessa yhä tunnetummaksi, monen yrityksen ja tahon tavoitteena on tutkia tämän teknologian hyödyntämistä. Musiikkiteollisuus on erityisesti mainittu sopivan kyseiseen integroimiseen: musiikkiteollisuudessa on monia sidosryhmiä, joiden välillä on monimutkaisia ja usein ongelmallisia suhteita. Tämän tutkimuksen tavoitteena on ymmärtää blockchain-teknologian käyttö musiikkiteollisuudessa. Ymmärrys ulottuu tekniseen hyödyntämiseen, liiketoiminnallisiin seuraamuksiin ja musiikkiteollisuuden ja teknologian pitkäaikaiseen risteytymään. Tutkimus suoritettiin laadullisena monitapaustutkimuksena, jonka tarkoituksena oli kerätä kokonaisvaltainen ymmärrys blockchain-teknologian käytöstä jokaisen tapauksen näkökulmasta. Empiirinen data kerättiin sekundääriaineistosta, josta tuli ilmi jokaisen tapauksen tekninen ja liiketoiminnallinen malli. Aineistoa lähestyttiin induktiivisesti ja analysoitiin intensiivisesti. Tulokset paljastivat kuinka blockchain-teknologia ohjasi kanssakäymistä ja miten eri sidosryhmät asennoituivat teknologiaan ja toisiinsa nähden. Teknologiaa hyödynnettiin eri tavoilla ja eri laajuudella. Teknologian seurauksena jokaisessa tapauksessa ilmestyi huomattavia eroja tapausten hallinnoinnissa, rakenteissa ja liiketoiminnan logiikassa. Tämä tutkimus erittelee tarkasti jokaisen tapauksen tekniset yksityiskohdat ja niistä seuraavat edellä mainitut erot. Johtopäätöksenä kuitenkin todetaan, että tutkimuksessa esiintyvät tapaukset ovat vielä kehittymisvaiheessa, eivätkä voi näin puoltaa teknologian olevan valmiina täysmittaiseen adoptioon. Tämä osaltaan tukee teoriassa esiin tuotuja väitteitä teknologian epäkypsyydestä

Social Capital, Culture, and Institutions as Determinants of Entrepreneurship in a Development Context

Entrepreneurship is still a social term that scholars have difficulty defining, and a lack of consistency in theory in turn leaves researchers without an accurate way to measure entrepreneurial activity. A working definition and theory of the entrepreneur is provided as a way to synthesize the various multi-disciplinary approaches taken towards entrepreneurship in past literature, with emphasis on welfare and judgmental decision-making under uncertainty. Past studies find significant relationships between economic growth and the level of entrepreneurial activity in a country. Little is known, however, on which elements of a society contribute to entrepreneurship and which do not. This study examines the effects that social capital, culture, and institution measures have on the level of self-employment in a country, with specific focus on developing countries. Results of this cross-country regression analysis form a model of entrepreneurship with significant explanatory power from property rights, productivity, and trust