264 research outputs found

    Conversations on Empathy

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    In the aftermath of a global pandemic, amidst new and ongoing wars, genocide, inequality, and staggering ecological collapse, some in the public and political arena have argued that we are in desperate need of greater empathy — be this with our neighbours, refugees, war victims, the vulnerable or disappearing animal and plant species. This interdisciplinary volume asks the crucial questions: How does a better understanding of empathy contribute, if at all, to our understanding of others? How is it implicated in the ways we perceive, understand and constitute others as subjects? Conversations on Empathy examines how empathy might be enacted and experienced either as a way to highlight forms of otherness or, instead, to overcome what might otherwise appear to be irreducible differences. It explores the ways in which empathy enables us to understand, imagine and create sameness and otherness in our everyday intersubjective encounters focusing on a varied range of "radical others" – others who are perceived as being dramatically different from oneself. With a focus on the importance of empathy to understand difference, the book contends that the role of empathy is critical, now more than ever, for thinking about local and global challenges of interconnectedness, care and justice

    Control and Archaism

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    The presentation will delve into the relationship between control society and archaism. Deleuze’s conceptualization of control implies the reconfiguration of former spaces of discipline. While the Foucauldian model of discipline was characterized by enclosed spaces (such as prisons, armies, and churches), Deleuze’s notion of control highlights a continuous network where individuals are no longer molded but modulated. This prompts us to ponder the shift in the temporal structure that occurs during the transition from a disciplinary society to one governed by control. Specifically, this presentation aims to explore the disparities in our historical perspectives when viewed from disciplinary and control paradigms. In this context, I will explore Deleuze and Guattari's concept of ‘archaism’. According to Deleuze and Guattari, archaism is an inherent aspect of capitalism, its continual endeavor to reconstruct territoriality and replicate antiquated coding patterns. Capitalism necessitates archaism due to its lack of inherent belief structures. In essence, the system, which the duo name the ‘age of cynicism’, requires the revival of old codes to sustain its systems of subjugation and dominance. As my presentation will demonstrate, one can discern a transformation in the evolution of archaism as society shifts from discipline to control. By comparing the fascist archaism of the thirties in Germany and the archaism of contemporary alt-right movements, I will show that a disciplinary society presupposes a more centralized form of archaism, which is highly susceptible to state control and deeply ingrained in the institutional fabric of social life. Conversely, a control society implies a diversification and creativity in archaic attitudes, hinting at its potential for emancipation—a viewpoint emphasized by Deleuze and Guattari themselves in ’Anti-Oedipus’

    Enactive artificial intelligence: subverting gender norms in human-robot interaction

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    IntroductionThis paper presents Enactive Artificial Intelligence (eAI) as a gender-inclusive approach to AI, emphasizing the need to address social marginalization resulting from unrepresentative AI design.MethodsThe study employs a multidisciplinary framework to explore the intersectionality of gender and technoscience, focusing on the subversion of gender norms within Robot-Human Interaction in AI.ResultsThe results reveal the development of four ethical vectors, namely explainability, fairness, transparency, and auditability, as essential components for adopting an inclusive stance and promoting gender-inclusive AI.DiscussionBy considering these vectors, we can ensure that AI aligns with societal values, promotes equity and justice, and facilitates the creation of a more just and equitable society

    Neural foundations of cooperative social interactions

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    The embodied-embedded-enactive-extended (4E) approach to study cognition suggests that interaction with the world is a crucial component of our cognitive processes. Most of our time, we interact with other people. Therefore, studying cognition without interaction is incomplete. Until recently, social neuroscience has only focused on studying isolated human and animal brains, leaving interaction unexplored. To fill this gap, we studied interacting participants, focusing on both intra- and inter-brain (hyperscanning) neural activity. In the first study, we invited dyads to perform a visual task in both a cooperative and a competitive context while we measured EEG. We found that mid-frontal activity around 200-300 ms after receiving monetary rewards was sensitive to social context and differed between cooperative and competitive situations. In the second study, we asked participants to coordinate their movements with each other and with a robotic partner. We found significantly stronger EEG amplitudes at frontocentral electrodes when people interacted with a robotic partner. Lastly, we performed a comprehensive literature review and the first meta-analysis in the emerging field of hyperscanning that validated it as a method to study social interaction. Taken together, our results showed that adding a second participant (human or AI/robotic) fostered our understanding of human cognition. We learned that the activity at frontocentral electrodes is sensitive to social context and type of partner (human or robotic). In both studies, the participants’ interaction was required to show these novel neural processes involved in action monitoring. Similarly, studying inter-brain neural activity allows for the exploration of new aspects of cognition. Many cognitive functions involved in successful social interactions are accompanied by neural synchrony between brains, suggesting the extended form of our cognition

    Ghost In the Grid: Challenges for Reinforcement Learning in Grid World Environments

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    The current state-of-the-art deep reinforcement learning techniques require agents to gather large amounts of diverse experiences to train effective and general models. In addition, there are also many other factors that have to be taken into consideration: for example, how the agent interacts with its environment; parameter optimization techniques; environment exploration methods; and finally the diversity of environments that is provided to an agent. In this thesis, we investigate several of these factors. Firstly we introduce Griddly, a high-performance grid-world game engine that provides a state-of-the-art combination of high performance and flexibility. We demonstrate that grid worlds provide a principled and expressive substrate for fundamental research questions in reinforcement learning, whilst filtering out noise inherent in physical systems. We show that although grid-worlds are constructed with simple rules-based mechanics, they can be used to construct complex open-ended, and procedurally generated environments. We improve upon Griddly with GriddlyJS, a web-based tool for designing and testing grid-world environments for reinforcement learning research. GriddlyJS provides a rich suite of features that assist researchers in a multitude of different learning approaches. To highlight the features of GriddlyJS we present a dataset of 100 complex escape-room puzzle levels. In addition to these complex puzzle levels, we provide human-generated trajectories and a baseline policy that can be run in a web browser. We show that this tooling enables significantly faster research iteration in many sub-fields. We then explore several areas of RL research that are made accessible by the features introduced by Griddly: Firstly, we explore learning grid-world game mechanics using deep neural networks. The {\em neural game engine} is introduced which has competitive performance in terms of sample efficiency and predicting states accurately over long time horizons. Secondly, {\em conditional action trees} are introduced which describe a method for compactly expressing complex hierarchical action spaces. Expressing hierarchical action spaces as trees leads to action spaces that are additive rather than multiplicative over the factors of the action space. It is shown that these compressed action spaces reduce the required output size of neural networks without compromising performance. This makes the interfaces to complex environments significantly simpler to implement. Finally, we explore the inherent symmetry in common observation spaces, using the concept of {\em geometric deep learning}. We show that certain geometric data augmentation methods do not conform to the underlying assumptions in several training algorithms. We provide solutions to these problems in the form of novel regularization functions and demonstrate that these methods fix the underlying assumptions

    Control and Archaism

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    The presentation will delve into the relationship between control society and archaism. Deleuze’s conceptualization of control implies the reconfiguration of former spaces of discipline. While the Foucauldian model of discipline was characterized by enclosed spaces (such as prisons, armies, and churches), Deleuze’s notion of control highlights a continuous network where individuals are no longer molded but modulated. This prompts us to ponder the shift in the temporal structure that occurs during the transition from a disciplinary society to one governed by control. Specifically, this presentation aims to explore the disparities in our historical perspectives when viewed from disciplinary and control paradigms. In this context, I will explore Deleuze and Guattari's concept of ‘archaism’. According to Deleuze and Guattari, archaism is an inherent aspect of capitalism, its continual endeavor to reconstruct territoriality and replicate antiquated coding patterns. Capitalism necessitates archaism due to its lack of inherent belief structures. In essence, the system, which the duo name the ‘age of cynicism’, requires the revival of old codes to sustain its systems of subjugation and dominance. As my presentation will demonstrate, one can discern a transformation in the evolution of archaism as society shifts from discipline to control. By comparing the fascist archaism of the thirties in Germany and the archaism of contemporary alt-right movements, I will show that a disciplinary society presupposes a more centralized form of archaism, which is highly susceptible to state control and deeply ingrained in the institutional fabric of social life. Conversely, a control society implies a diversification and creativity in archaic attitudes, hinting at its potential for emancipation—a viewpoint emphasized by Deleuze and Guattari themselves in ’Anti-Oedipus’

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments

    Robot e cobot nell’impresa e nella scuola

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    The book deals with the transversal theme of hymn-technological development through robots and cobots, the introduction of which crosses now business, scholastic and educational contexts. Starting from an introduction aimed at questioning what is meant from for innovation and what could be the minimum conditions for it we can actually speak of innovative contexts, the volume takes the distances from techno-enthusiastic or techno-critical approaches assumed a priori and suggested manages a departure from a win win perspective at any cost which does not properly reflect on some crucial issues in supporting the innovative processes, including the training of workers (in primis), the legal perspectives, as well as the needs in the terms of new tools to ensure the management of health and safety at work. The volume continues by addressing the potential of collaborative robots in helping people to carry out more or less complex tasks, ibid including learning; therefore, some uses of robotics are presented in educational contexts of school or higher education where robotics could be used as a tool to support people with autism, contrast bullying phenomena, help develop skills transversal and space-time trends, also through the use of the so-called swarm robotics. Despite the difference of languages and specific perspectives that distinguish the different chapters, the volume is oriented to a reader curious and aware that business, school and university can play the their game in synergy, learning to listen to each other and to reflect more frequently-mind about the challenges that unite them
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