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This article analyzes the problems of the implementation of accepting effective decisions in local authorities. Besides, certain suggestions and reccomendations related to the participation of social public control in decision accepting process in local state governmental bodies.

All the factors which influence political decision-making may (reasonably) be integrated into a model which combines operational concepts of power, influence, and authority. The problem-solving approach is applied to one class of decisions, defined here as those made for social situations involving both technical and political factors. Political power seems necessarily to be engaged in a twofold form of activity. On the one hand it formulates the content of decisions to be made and is thereby affected by both the technical and political definition of the problem to be resolved. On the other hand, power is both an agent and an object of influence at every stage of the decisional process. Political power appears, then, to be a more comprehensive concept than either authority or influence. Its basic constituents are found in a fusion of the function of influence with the function of defining issues authoritatively. Authority is but one kind of influence while influence itself is simply one of the two chief functions of power.Power, before it is influential, is creative, inventive of ideas, and of solutions. Incorporation of these different categories into a model provides us with a systematic representation of the decision-making process of formulation, adoption, and execution. Particular attention is devoted to differentiating those components of behaviour on which authority is based from those which make the assessment of authority possible. On the whole, authoritative decision-making seems to be circumscribed by the original definition of the problem and by the decision-maker's personal under-standing. Up to a certain point this permits us to distinguish the part played by the force of given circumstances from that attributable to the free choice of the actors in a democratic political system. ; SCOPUS: ar.j ; info:eu-repo/semantics/published

The article deals with the problem of constructing a model and algorithm for decision support in self-government bodies using machine learning. The method of multiple linear regression for processing the training sample was chosen as a machine learning method. In the training sample, independent data consists of parametric estimates in numerical form of self-government bodies in three areas of activity, such as education, social environment and crime. And the dependent parameter consists of generalized expert assessments of self-government bodies, also in numerical form. The model and algorithm of the decision support process using the method of multiple linear regression are constructed. Based on the constructed model and the proposed algorithm, the coefficients of the function for decision support are identified. Using this model, a generalized expert assessment is determined for the new self-government body in numerical form, which is interpreted as a proposed solution for improving the condition of the object.

The article deals with the problem of constructing a model and algorithm for decision support in self-government bodies using machine learning. The method of multiple linear regression for processing the training sample was chosen as a machine learning method. In the training sample, independent data consists of parametric estimates in numerical form of self-government bodies in three areas of activity, such as education, social environment and crime. And the dependent parameter consists of generalized expert assessments of self-government bodies, also in numerical form. The model and algorithm of the decision support process using the method of multiple linear regression are constructed. Based on the constructed model and the proposed algorithm, the coefficients of the function for decision support are identified. Using this model, a generalized expert assessment is determined for the new self-government body in numerical form, which is interpreted as a proposed solution for improving the condition of the object.

Collective decision making is a process in which many participants with different interests interact in order to build a solution to their problem. It is inherent to many organisations and companies. Nowadays, the advances in Artificial Intelligence, notably, Multi-Agents Systems enabled the automation of decision-making processes in order to analyse and to better understand how these mechanisms work. A collective decision may be made by using a voting system or by using negotiation. In this thesis, we focus on multilateral negotiation for collective decision making by proposing negotiation models. The proposed models based on heuristic approach. The agents interact with them in order to build a solution to their problem. This context is different from models based on game theory where the set of possible solutions are supposed to be known by all agents. So heuristic negotiation issue is that agents' reasoning may be very complex. This complexity grows where the number of agents and issues to be negotiated are important. The goal of this research work consists of devising negotiation mechanisms where agents'interaction are fully decentralized. We focus on organisation aspect of the multi-agent system by using divide and conquer approach in order to reduce the negotiation complexity and hence to facilitate research of agreements. Our works tackle negotiation under different contexts which lead us to bring three contributions which focus on agents' organization, interaction protocols, negotiation object, concession strategies and effective and fair solution concept. The proposed mechanisms are implemented in JavaJade. We analyse the convergence of the negotiation, negotiation time and quality of the solution. Our models are compared with a centralized approach where all of the agents are gathered around one group to negotiate. Our empirical analyses show that our propositions allow the agents to reach collectives agreements ; La prise de décision collective est un processus dans lequel un groupe d'individus, ayant des intérêts différents, se réunit pour trouver une solution collective à un problème. Ce processus est inhérent aux activités de toute organisation politique, économique ou sociale. Le développement de l'Intelligence Artificielle notamment les Systèmes Multi-Agents a permis la modélisation et l'automatisation des processus de prise de décision afin de mieux comprendre et d'analyser leur fonctionnement. Une décision collective peut être prise par vote ou par négociation. Dans le cadre de cette thèse, nous abordons les mécanismes de négociation multilatérale pour la prise de décision collective basés sur des approches heuristiques. Les agents construisent la solution à leur problème à travers leurs interactions à la différence des modèles basés sur la théorie des jeux dont l'espace des solutions est supposé connu par tous les agents. Le problème des négociations heuristiques réside dans les mécanismes de raisonnement des agents dont la complexité augmente lorsque le nombre d'agents et d'attributs à négocier devient important. L'objectif de cette thèse est ainsi de proposer des mécanismes de négociation décentralisés (sans médiateur) et distribués en mettant en exergue l'aspect organisationnel des agents. Notre approche s'inspire du concept diviser pour régner et permet aux agents de négocier de façon incrémentale. Le but est de faciliter la recherche d'accords et de limiter la complexité du raisonnement des agents. Les travaux de cette thèse ont abouti à trois contributions abordant la négociation multi-agents sous différents angles tels que l'organisation des agents, le protocole d'interaction et les stratégies de concession et de choix de solutions équitables et justes. Pour valider nos propositions, nous avons implémenté sous JavaJade les mécanismes de négociation proposés. Les critères de performance que nous avons évalués sont, notamment, la convergence, le temps de négociation et la qualité de la solution. Nous avons comparé nos modèles avec ceux existants et les résultats obtenus montrent leur efficacité pour l'obtention des accords entre les agents

Collective decision making is a process in which many participants with different interests interact in order to build a solution to their problem. It is inherent to many organisations and companies. Nowadays, the advances in Artificial Intelligence, notably, Multi-Agents Systems enabled the automation of decision-making processes in order to analyse and to better understand how these mechanisms work. A collective decision may be made by using a voting system or by using negotiation. In this thesis, we focus on multilateral negotiation for collective decision making by proposing negotiation models. The proposed models based on heuristic approach. The agents interact with them in order to build a solution to their problem. This context is different from models based on game theory where the set of possible solutions are supposed to be known by all agents. So heuristic negotiation issue is that agents' reasoning may be very complex. This complexity grows where the number of agents and issues to be negotiated are important. The goal of this research work consists of devising negotiation mechanisms where agents'interaction are fully decentralized. We focus on organisation aspect of the multi-agent system by using divide and conquer approach in order to reduce the negotiation complexity and hence to facilitate research of agreements. Our works tackle negotiation under different contexts which lead us to bring three contributions which focus on agents' organization, interaction protocols, negotiation object, concession strategies and effective and fair solution concept. The proposed mechanisms are implemented in JavaJade. We analyse the convergence of the negotiation, negotiation time and quality of the solution. Our models are compared with a centralized approach where all of the agents are gathered around one group to negotiate. Our empirical analyses show that our propositions allow the agents to reach collectives agreements ; La prise de décision collective est un processus dans lequel un groupe d'individus, ayant des intérêts différents, se réunit pour trouver une solution collective à un problème. Ce processus est inhérent aux activités de toute organisation politique, économique ou sociale. Le développement de l'Intelligence Artificielle notamment les Systèmes Multi-Agents a permis la modélisation et l'automatisation des processus de prise de décision afin de mieux comprendre et d'analyser leur fonctionnement. Une décision collective peut être prise par vote ou par négociation. Dans le cadre de cette thèse, nous abordons les mécanismes de négociation multilatérale pour la prise de décision collective basés sur des approches heuristiques. Les agents construisent la solution à leur problème à travers leurs interactions à la différence des modèles basés sur la théorie des jeux dont l'espace des solutions est supposé connu par tous les agents. Le problème des négociations heuristiques réside dans les mécanismes de raisonnement des agents dont la complexité augmente lorsque le nombre d'agents et d'attributs à négocier devient important. L'objectif de cette thèse est ainsi de proposer des mécanismes de négociation décentralisés (sans médiateur) et distribués en mettant en exergue l'aspect organisationnel des agents. Notre approche s'inspire du concept diviser pour régner et permet aux agents de négocier de façon incrémentale. Le but est de faciliter la recherche d'accords et de limiter la complexité du raisonnement des agents. Les travaux de cette thèse ont abouti à trois contributions abordant la négociation multi-agents sous différents angles tels que l'organisation des agents, le protocole d'interaction et les stratégies de concession et de choix de solutions équitables et justes. Pour valider nos propositions, nous avons implémenté sous JavaJade les mécanismes de négociation proposés. Les critères de performance que nous avons évalués sont, notamment, la convergence, le temps de négociation et la qualité de la solution. Nous avons comparé nos modèles avec ceux existants et les résultats obtenus montrent leur efficacité pour l'obtention des accords entre les agents

Collective decision making is a process in which many participants with different interests interact in order to build a solution to their problem. It is inherent to many organisations and companies. Nowadays, the advances in Artificial Intelligence, notably, Multi-Agents Systems enabled the automation of decision-making processes in order to analyse and to better understand how these mechanisms work. A collective decision may be made by using a voting system or by using negotiation. In this thesis, we focus on multilateral negotiation for collective decision making by proposing negotiation models. The proposed models based on heuristic approach. The agents interact with them in order to build a solution to their problem. This context is different from models based on game theory where the set of possible solutions are supposed to be known by all agents. So heuristic negotiation issue is that agents' reasoning may be very complex. This complexity grows where the number of agents and issues to be negotiated are important. The goal of this research work consists of devising negotiation mechanisms where agents'interaction are fully decentralized. We focus on organisation aspect of the multi-agent system by using divide and conquer approach in order to reduce the negotiation complexity and hence to facilitate research of agreements. Our works tackle negotiation under different contexts which lead us to bring three contributions which focus on agents' organization, interaction protocols, negotiation object, concession strategies and effective and fair solution concept. The proposed mechanisms are implemented in JavaJade. We analyse the convergence of the negotiation, negotiation time and quality of the solution. Our models are compared with a centralized approach where all of the agents are gathered around one group to negotiate. Our empirical analyses show that our propositions allow the agents to reach collectives agreements ; La prise de décision collective est un processus dans lequel un groupe d'individus, ayant des intérêts différents, se réunit pour trouver une solution collective à un problème. Ce processus est inhérent aux activités de toute organisation politique, économique ou sociale. Le développement de l'Intelligence Artificielle notamment les Systèmes Multi-Agents a permis la modélisation et l'automatisation des processus de prise de décision afin de mieux comprendre et d'analyser leur fonctionnement. Une décision collective peut être prise par vote ou par négociation. Dans le cadre de cette thèse, nous abordons les mécanismes de négociation multilatérale pour la prise de décision collective basés sur des approches heuristiques. Les agents construisent la solution à leur problème à travers leurs interactions à la différence des modèles basés sur la théorie des jeux dont l'espace des solutions est supposé connu par tous les agents. Le problème des négociations heuristiques réside dans les mécanismes de raisonnement des agents dont la complexité augmente lorsque le nombre d'agents et d'attributs à négocier devient important. L'objectif de cette thèse est ainsi de proposer des mécanismes de négociation décentralisés (sans médiateur) et distribués en mettant en exergue l'aspect organisationnel des agents. Notre approche s'inspire du concept diviser pour régner et permet aux agents de négocier de façon incrémentale. Le but est de faciliter la recherche d'accords et de limiter la complexité du raisonnement des agents. Les travaux de cette thèse ont abouti à trois contributions abordant la négociation multi-agents sous différents angles tels que l'organisation des agents, le protocole d'interaction et les stratégies de concession et de choix de solutions équitables et justes. Pour valider nos propositions, nous avons implémenté sous JavaJade les mécanismes de négociation proposés. Les critères de performance que nous avons évalués sont, notamment, la convergence, le temps de négociation et la qualité de la solution. Nous avons comparé nos modèles avec ceux existants et les résultats obtenus montrent leur efficacité pour l'obtention des accords entre les agents

В статье исследуются факторы и правила, которые оказывают влияние на процесс коллективного творчества по формированию технологии принятия коллективных решений и создания творческой атмосферы в коллективе. ; In article the considered factors and rules which influence process of collective creativity of formation of technology of adoption of collective decisions and creation of the creative atmosphere in collective.

The constant growth of recoverable volumes of oil and gas, the increasing remoteness of fields from developed infrastructure, political pressure and regulation, the development and complication of the technologies used, and the ever-growing volume of information create multilevel decision-making systems in the oil and gas industry. The further socio-economic development of not only individual corporations and regions, but also the state as a whole, depends on rational and timely decisions made in this area. The article is devoted to the development of management decision-making tools in the oil and gas industry. Peculiarities of the process of making managerial decisions in this industry are identified, associated with special geographical restrictions, the large disunity of production facilities and control centers, the difficulty of obtaining reliable information about the resources mined at great depths underground, market volatility and political influence. A methodology for making managerial decisions is proposed, consisting of three stages, each of which uses a specific set of tools. Five elements are identified that can be identified in almost all decision-making situations. It is shown how the preferences of the decision maker form a hierarchy of goals and values. ; Постоянный рост извлекаемых объемов нефти и газа, все большая удаленность месторождений от развитой инфраструктуры, политическое давление и регулирование, развитие и усложнение используемых технологий, и постоянно растущий объем информации создают многоуровневые системы принятия решений в нефтегазовой отрасли. От рациональных и своевременно принятых решений в данной области зависит дальнейшее социально-экономическое развитие не только отдельно взятых корпораций и регионов, но и государства в целом. Статья посвящена развитию инструментов принятия управленческих решений в нефтегазовой отрасли. Выявлены особенности процесса принятия управленческих решений в данной отрасли, связанные с особыми географическими ограничениями, большой разобщенностью производственных объектов и центров управления, сложностью получения достоверной информации о добываемых ресурсах, находящихся на больших глубинах под землей, волатильностью рынка и политическим влиянием. Предложена методика принятия управленческих решений, состоящая из трех этапов, на каждом из которых применяется определенный набор инструментов. Определены пять элементов, которые могут быть идентифицированы практически во всех ситуациях принятия решений. Показано как предпочтения лица, принимающего решения, формируют иерархию целей и значений.

The article considers the features of transport as an object of technological innovation, due, on the one hand, to the service nature of the main activity and the specifics of innovative processes during provision of transport and logistics services, and, on the other hand, to the high capital intensity and technological complexity of the infrastructure transport complex, which is the focus point of technological innovation.The objective of the article is to substantiate the initial prerequisites for developing an alternative approach to making strategic decisions on development of transport organisations based on technological innovations, which, besides the traditional justification of economic efficiency, considers several non-economic factors. The method of substantiation is a systemic strategic analysis, which allows to study the features of the transport complex in the context of the factors of external environment and their dynamics.Regarding the Russian Federation, the scale of the national territory, natural and climatic diversity and uneven territorial distribution of the resource and production base determine the special role and place of transport in the national economy, which quite often leads to the need to make decisions on development of the transport complex based on predominantly non-economic factors (such as security, reliability, environmental friendliness, etc.) and on scientific, technical, political and socio-economic forecasts. At the same time, private enterprises (with or without participation of the state) dominate currently almost all transport sectors where they operate on the principles of profitability, investment attractiveness and competitiveness, which leads to inconsistency of internal decision-making criteria in the field of technological strategies.The ongoing change in the technological paradigm is an additional and significant factor determining trends in transport developments. It is based on the processes of digitalisation and digital transformation of the transport and logistics business. The problems of decision-making in implementation of technological innovations in transport industry, arising from its peculiarities, necessitate a revision of approaches since economic assessments of efficiency are not always able to reflect the real needs and feasibility of choosing mainstream trends in technological development of the transport system.The analysis of the features of the transport and logistics industry based on universal experience and cases in Russian practices in the context of formation of a new technological paradigm makes it possible to substantiate the methodology for making strategic decisions on implementation of technological innovations. ; В статье рассматриваются особенности транспорта как объекта технологических инноваций, обусловленные, с одной стороны, сервисным характером основной деятельности и спецификой инновационных процессов при транспортно-логистическом оказании услуг, а, с другой стороны, высокой капиталоёмкостью и технологической сложностью инфраструктурного транспортного комплекса, в котором сосредоточены технологические инновации.Цель статьи – обосновать исходные предпосылки для разработки альтернативного подхода к принятию стратегических решений о развитии транспортных организаций на основе технологических инноваций, который наряду с традиционным обоснованием экономической эффективности учитывает ряд внеэкономических факторов. Методом обоснования является системный стратегический анализ, позволяющий исследовать особенности транспортного комплекса в контексте факторов внешней среды и их динамики.Применительно к Российской Федерации масштабы территории, природно-климатическое разнообразие и неравномерность территориального распределения ресурсной и производственной базы обусловливают особую роль и место транспорта в национальной экономике, что достаточно часто приводит к необходимости принятия решений о развитии транспортного комплекса, исходя из преимущественно внеэкономических факторов (таких, как безопасность, надёжность, экологичность и др.) и на основе научно-технических, политических и социально-экономических прогнозов. В то же время практически во всех отраслях транспорта в современных российских условиях доминируют частные предприятия (с участием государства или без), работающие на принципах рентабельности, инвестиционной привлекательности и конкурентоспособности, что приводит к противоречивости внутренних критериев принятия решений в области технологических стратегий.Дополнительным и существенным фактором, определяющим общие направления развития транспорта, является происходящая в настоящее время смена технологической парадигмы, в основе которой лежат процессы цифровизации и цифровой трансформации транспортно-логистического бизнеса. Проблемы принятия решений о реализации технологических инноваций на транспорте, возникающие вследствие его особенностей, обусловливают потребность пересмотра подходов, поскольку экономические оценки эффективности не всегда способны отразить реальную необходимость и целесообразность выбора направлений технологического развития транспортного комплекса.Анализ особенностей транспортно-логистической отрасли на основе обобщения универсального опыта и привлечения примеров российской практики в контексте становления новой технологической парадигмы позволяет обосновать методологию принятия стратегических решений о реализации технологических инноваций.

Принятие решений в институтах высшего образования реализуется в условиях VUCA-мира: нестабильности, неопределенности, сложности, неоднозначности, являющимися значимыми контекстами современной социокультурной и организационной реальности. Данная статья представляет собой кейс-исследование процесса проектирования и открытия новой образовательной программы в одном российском университете, представленного в виде цепи взаимосвязанных решений, анализ которых выявляет и объясняет специфику принятия управленческих решений в современных университетах. Исследование опирается на смешанные методы, включающие: пять глубинных интервью с наиболее важными стейкхолдерами; включенное наблюдение за этапами развития ситуации; интервью с остальными стейкхолдерами; анализ государственных регулирующих документов и стандартов; анализа университетских регулирующих документов и стандартов. Кейс был проанализирован с использованием теории ограниченной рациональности, теории организационной анархии; идей распределения власти и влияния в организациях; концепции избегания риска при принятии решений. Анализ кейса выявил наличие размытости границ власти вовлеченных сторон, неопределенность «правил игры», исключение некоторых важных заинтересованных сторон из процесса принятия решений, частичный недостаток опыта и экспертизы в новых ситуациях принятия решений, неоднозначность ряда востребованных организационных процедур. Представлен ряд стратегий, способных потенциально редуцировать уровень неопределенности и повысить качество принимаемых решений в университетах. К ним относятся: декомпозиция проблемной ситуации, применение техник анализа сложных решений, повышение роли участия и вовлеченности, управление распределением потоков информации, недопущение феномена группового мышления. Предложены меры по организации политических переговоров, повышению качества коммуникации, применению принципов самообучающейся организации. Статья содержит новый и мало представленный в российской научной литературе анализ теории и практики принятия управленческих решений, описанные стратегии призваны помочь формированию оснований для наиболее зрелых управленческих решений в университетском контексте. ; Making decisions in higher education institutions is realized in the context of the VUCA-world – that is, in the conditions of instability, uncertainty, complexity, and ambiguity, which are significant markers of today's social, cultural, and organizational reality. The article is a case study of designing and implementing a new educational program in one Russian university. The analysis is shaped in a chain of interconnected decisions revealing the specifics of management decisions in modern universities. The study is based on mixed research methods, including five in-depth interviews with the most important actors involved; observation of the situation development stages; interviews with other actors involved; analysis of state regulatory documents and standards; analysis of university regulatory documents and standards. The case is studied via organized anarchy theory, power and authority in organization theory, risk avoidance and bounded rationality perspectives were used. The analysis of the case has identified the involved parties' power boundaries blurring, the uncertainty of the «game rules», the exclusion of some important stakeholders from the decision-making process, the experience and expertise partially lacking in new decision-making situations, the ambiguity of several demanded organizational procedures. There are presented a number of strategies that can potentially reduce the level of uncertainty and improve the quality of decisions taken at universities. These include decomposing a problem situation, using techniques for analyzing complex decisions, increasing the role of participation and involvement, managing the distribution of information flows, preventing the phenomenon of group thinking. The article proposes measures of organizing political negotiations, improving the quality of communication, applying the principles of self-learning organization. The article contains a new and weakly presented in Russian scientific literature analysis of the theory and practice of decision-making management. The described strategies are designed to create solid background for mostly mature management decisions in universities. ; Публикация подготовлена при поддержке гранта РФФИ 18‑013‑01125 А «Модель управления научно-образовательной деятельностью в классическом исследовательском университете (магистратура)».

International audience ; For 40 years, to increase farm income per farmer, the major strategy has been to achieve labour productivity gains through massive investments in equipment and buildings. Cost competitiveness is not yet finished. The modernization process includes increased information technology. According to Brynjolfsson and McAfee (2014), we have entered the Second Machine Age with the digital revolution. Drones, robots, connected tools, algorithms, and artificial intelligence are now present on farms. Are we building a technological monster? One question is: what are the consequences of these changes concerning capital-intensive technology on farms and on the autonomy of farmers' decision? To answer, we have completed the analysis of data from literature surveys and experts. These developments call into question the relationship between farmers to work in organization, advice and decision-making autonomy. The results show Second Machine Age is at work. Our communication aims to discuss 2 possible consequences of this big change: (1) Farmers may lose their decision-making because the machines know how to calculate and to learn, and are able to make better decisions than farmers.(2)Because digital technologies are expensive and neednew skills, the agro-equipment sector may take control offarms because engineers will process Big Data and thus control decisions. ; L'évolution de l'agriculture française entre 1980 et 2016 a été marquée par la poursuite des gains de productivité du travail permis par la forte substitution du capital au travail. Le processus de modernisation inclut de plus en plus les technologies de l'information. Une question se pose :quelles sont les conséquences de la révolution numérique sur les exploitations ? Pour répondre, nous analysons les données tirées de la littérature scientifique et professionnelle et d'enquêtes auprès d'experts. Ces évolutions interrogent le rapport des agriculteurs au travail en termes d'organisation, de conseil et d'autonomie de la décision. Ne ...

International audience ; For 40 years, to increase farm income per farmer, the major strategy has been to achieve labour productivity gains through massive investments in equipment and buildings. Cost competitiveness is not yet finished. The modernization process includes increased information technology. According to Brynjolfsson and McAfee (2014), we have entered the Second Machine Age with the digital revolution. Drones, robots, connected tools, algorithms, and artificial intelligence are now present on farms. Are we building a technological monster? One question is: what are the consequences of these changes concerning capital-intensive technology on farms and on the autonomy of farmers' decision? To answer, we have completed the analysis of data from literature surveys and experts. These developments call into question the relationship between farmers to work in organization, advice and decision-making autonomy. The results show Second Machine Age is at work. Our communication aims to discuss 2 possible consequences of this big change: (1) Farmers may lose their decision-making because the machines know how to calculate and to learn, and are able to make better decisions than farmers.(2)Because digital technologies are expensive and neednew skills, the agro-equipment sector may take control offarms because engineers will process Big Data and thus control decisions. ; L'évolution de l'agriculture française entre 1980 et 2016 a été marquée par la poursuite des gains de productivité du travail permis par la forte substitution du capital au travail. Le processus de modernisation inclut de plus en plus les technologies de l'information. Une question se pose :quelles sont les conséquences de la révolution numérique sur les exploitations ? Pour répondre, nous analysons les données tirées de la littérature scientifique et professionnelle et d'enquêtes auprès d'experts. Ces évolutions interrogent le rapport des agriculteurs au travail en termes d'organisation, de conseil et d'autonomie de la décision. Ne serions-nous pas déjà entrés dans le deuxième âge des machines, celui des machines capables de prendre de décisions plus efficaces que les humains ?

International audience ; For 40 years, to increase farm income per farmer, the major strategy has been to achieve labour productivity gains through massive investments in equipment and buildings. Cost competitiveness is not yet finished. The modernization process includes increased information technology. According to Brynjolfsson and McAfee (2014), we have entered the Second Machine Age with the digital revolution. Drones, robots, connected tools, algorithms, and artificial intelligence are now present on farms. Are we building a technological monster? One question is: what are the consequences of these changes concerning capital-intensive technology on farms and on the autonomy of farmers' decision? To answer, we have completed the analysis of data from literature surveys and experts. These developments call into question the relationship between farmers to work in organization, advice and decision-making autonomy. The results show Second Machine Age is at work. Our communication aims to discuss 2 possible consequences of this big change: (1) Farmers may lose their decision-making because the machines know how to calculate and to learn, and are able to make better decisions than farmers.(2)Because digital technologies are expensive and neednew skills, the agro-equipment sector may take control offarms because engineers will process Big Data and thus control decisions. ; L'évolution de l'agriculture française entre 1980 et 2016 a été marquée par la poursuite des gains de productivité du travail permis par la forte substitution du capital au travail. Le processus de modernisation inclut de plus en plus les technologies de l'information. Une question se pose :quelles sont les conséquences de la révolution numérique sur les exploitations ? Pour répondre, nous analysons les données tirées de la littérature scientifique et professionnelle et d'enquêtes auprès d'experts. Ces évolutions interrogent le rapport des agriculteurs au travail en termes d'organisation, de conseil et d'autonomie de la décision. Ne serions-nous pas déjà entrés dans le deuxième âge des machines, celui des machines capables de prendre de décisions plus efficaces que les humains ?

International audience ; For 40 years, to increase farm income per farmer, the major strategy has been to achieve labour productivity gains through massive investments in equipment and buildings. Cost competitiveness is not yet finished. The modernization process includes increased information technology. According to Brynjolfsson and McAfee (2014), we have entered the Second Machine Age with the digital revolution. Drones, robots, connected tools, algorithms, and artificial intelligence are now present on farms. Are we building a technological monster? One question is: what are the consequences of these changes concerning capital-intensive technology on farms and on the autonomy of farmers' decision? To answer, we have completed the analysis of data from literature surveys and experts. These developments call into question the relationship between farmers to work in organization, advice and decision-making autonomy. The results show Second Machine Age is at work. Our communication aims to discuss 2 possible consequences of this big change: (1) Farmers may lose their decision-making because the machines know how to calculate and to learn, and are able to make better decisions than farmers.(2)Because digital technologies are expensive and neednew skills, the agro-equipment sector may take control offarms because engineers will process Big Data and thus control decisions. ; L'évolution de l'agriculture française entre 1980 et 2016 a été marquée par la poursuite des gains de productivité du travail permis par la forte substitution du capital au travail. Le processus de modernisation inclut de plus en plus les technologies de l'information. Une question se pose :quelles sont les conséquences de la révolution numérique sur les exploitations ? Pour répondre, nous analysons les données tirées de la littérature scientifique et professionnelle et d'enquêtes auprès d'experts. Ces évolutions interrogent le rapport des agriculteurs au travail en termes d'organisation, de conseil et d'autonomie de la décision. Ne serions-nous pas déjà entrés dans le deuxième âge des machines, celui des machines capables de prendre de décisions plus efficaces que les humains ?