51 research outputs found

    A Bayesian explanation of the 'Uncanny Valley' effect and related psychological phenomena

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    There are a number of psychological phenomena in which dramatic emotional responses are evoked by seemingly innocuous perceptual stimuli. A well known example is the ‘uncanny valley’ effect whereby a near human-looking artifact can trigger feelings of eeriness and repulsion. Although such phenomena are reasonably well documented, there is no quantitative explanation for the findings and no mathematical model that is capable of predicting such behavior. Here I show (using a Bayesian model of categorical perception) that differential perceptual distortion arising from stimuli containing conflicting cues can give rise to a perceptual tension at category boundaries that could account for these phenomena. The model is not only the first quantitative explanation of the uncanny valley effect, but it may also provide a mathematical explanation for a range of social situations in which conflicting cues give rise to negative, fearful or even violent reactions

    Climate and southern Africa's water-energy-food nexus

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    In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and Gross Domestic Product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose; the Southern African Development Community, the Southern African Power Pool, and trade of agricultural products amounting to significant transfers of embedded water

    How AI Systems Challenge the Conditions of Moral Agency?

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    The article explores the effects increasing automation has on our conceptions of human agency. We conceptualize the central features of human agency as ableness, intentionality, and rationality and define responsibility as a central feature of moral agency. We discuss suggestions in favor of holding AI systems moral agents for their functions but join those who refute this view. We consider the possibility of assigning moral agency to automated AI systems in settings of machine-human cooperation but come to the conclusion that AI systems are not genuine participants in joint action and cannot be held morally responsible. Philosophical issues notwithstanding, the functions of AI systems change human agency as they affect our goal setting and pursuing by influencing our conceptions of the attainable. Recommendation algorithms on news sites, social media platforms, and in search engines modify our possibilities to receive accurate and comprehensive information, hence influencing our decision making. Sophisticated AI systems replace human workforce even in such demanding fields as medical surgery, language translation, visual arts, and composing music. Being second to a machine in an increasing number of fields of expertise will affect how human beings regard their own abilities. We need a deeper understanding of how technological progress takes place and how it is intertwined with economic and political realities. Moral responsibility remains a human characteristic. It is our duty to develop AI to serve morally good ends and purposes. Protecting and strengthening the conditions of human agency in any AI environment is part of this task.Peer reviewe

    Critical reflection on knowledge and narratives of conservation agriculture

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    In the context of contemporary concerns about climate change and food security, Conservation Agriculture (CA) has emerged as a well-supported and central component of the agricultural sector development strategy across sub-Saharan Africa, including in Zambia, which is the focus of this paper. A variety of narratives about the benefits of CA over conventional agricultural systems underpin endeavours towards ‘scaling up’ CA and increasing rates of adoption amongst smallholder farmers nationwide. However, there is a knowledge politics underlying the translation of a weak evidence base around CA into persuasive narratives and financial and political support. In this paper, we trace the evolution of five narratives around CA in Zambia in relation to changing political agendas and the involvement of new public and private sector actors, and review the development of evidence bases and knowledge that support and challenge each of these narratives. We discuss the potential to open up space within this knowledge politics to alternative narratives and the contestation of the pervasive CA scaling up agenda. Critical reflection is essential to ensure that national and local evidence is more effectively used to guide national climate and agricultural policy developments and international donor initiatives

    Pathways for scale and discipline reconciliation: current socio-ecological modelling methodologies to explore and reconstitute human prehistoric dynamics

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    International audienceThis communication elaborates a plea for the necessity of a specific modelling methodology which does not sacrifice two modelling principles: explanation Micro and correlation Macro. Three goals are assigned to modelling strategies: describe, understand and predict. One tendency in historical and spatial modelling is to develop models at a micro level in order to describe and by that way, understand the connection between local ecological contexts, acquired through local ecological data, and local social practices, acquired through archaeology. However, such a method faces difficulties for expanding its validity: It is validated by its adequacy with local data, but the prediction step is unreachable and quite nothing can be said for places out where. On the other hand, building models at a far larger scale, for instance at the continent and even the world level, enhances the connection between ecology and its temporal variability. Such connections are based on well-founded theories but lower the " small causes, big effects " emergence corresponding to agent-based approaches and the related inherent variability of socio-ecological dynamics that one can notice at a lower scale. We then propose a plea for combining both elements for building large-scale modelling tools, which aims are to describe and provide predictions on long-term past evolutions, that include the test of explaining socio-anthropological hypotheses, i.e. the emergence and the spread of local social innovations

    Internet of Things in Agricultural Innovation and Security

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    The agricultural Internet of Things (Ag-IoT) paradigm has tremendous potential in transparent integration of underground soil sensing, farm machinery, and sensor-guided irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. The aim of the IoT in agricultural innovation and security chapter is to present agricultural IoT research and paradigm to promote sustainable production of safe, healthy, and profitable crop and animal agricultural products. This chapter covers the IoT platform to test optimized management strategies, engage farmer and industry groups, and investigate new and traditional technology drivers that will enhance resilience of the farmers to the socio-environmental changes. A review of state-of-the-art communication architectures and underlying sensing technologies and communication mechanisms is presented with coverage of recent advances in the theory and applications of wireless underground communications. Major challenges in Ag-IoT design and implementation are also discussed
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