Project Testbed: Argument Mapping and Deliberation Analytics

One key goal of the Catalyst project was to design metrics that could capture and represent aspects of the conversation’s structural quality, to assist harvesters and moderators. Many such metrics, alerts and visualizations were developed in the course of the project, but initial user testing has shown that users find it difficult to interpret abstract signals. Following that, we have both introduced new analytics that we felt could be more directly useful, and improved the representation of existing ones. We evaluated their usefulness in a smaller conversation and in experimental settings

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

ADD-up:Visual analytics for augmented deliberative democracy

We demonstrate the first prototype of the ADD-up visual analytics system. The Augmented Deliberative Democracy (ADD-up) project aims to enhance public deliberations by providing argument analytics in real time. The system will ultimately take a stenographic feed of a public deliberation meeting, automatically extract the arguments therein and project visual analytics intended to improve the deliberative quality of the event.publishe

Comprehension, Demonstration, and Accuracy in Aristotle

according to aristotle's posterior analytics, scientific expertise is composed of two different cognitive dispositions. Some propositions in the domain can be scientifically explained, which means that they are known by "demonstration", a deductive argument in which the premises are explanatory of the conclusion. Thus, the kind of cognition that apprehends those propositions is called "demonstrative knowledge".1 However, not all propositions in a scientific domain are demonstrable. Demonstrations are ultimately based on indemonstrable principles, whose knowledge is called "comprehension".2 If the knowledge of all scientific propositions were..

Augmenting Public Deliberations through Stream Argument Analytics and Visualisations

Public deliberations are organised by governments and other large institutions to take the views of citizens around controversial issues. Increasing public demand and the associated burden on public funding make the quality of public deliberation events and their outcomes critical to modern democracies. This paper focuses on technology developed around streams of computational argument data intended to inform and improve deliberative communication in real time. Combining state-of-the-art speech recognition, argument mining, and analytics, we produce dynamic, interactive visualisations intended for non-experts, deployed incrementally in real time to deliberation participants via large screens, hand-held and personal computing devices. The goal is to bridge the gap between theoretical criteria on deliberation quality from the political sciences and objective analytics calculated automatically from computable argument data in actual public deliberations, presented as a set of visualisations which work on stream data and are simple, yet informative enough to make a positive impact on deliberative outcomes

Discussion Tracker: Supporting Teacher Learning about Students' Collaborative Argumentation in High School Classrooms

Teaching collaborative argumentation is an advanced skill that many K-12 teachers struggle to develop. To address this, we have developed Discussion Tracker, a classroom discussion analytics system based on novel algorithms for classifying argument moves, specificity, and collaboration. Results from a classroom deployment indicate that teachers found the analytics useful, and that the underlying classifiers perform with moderate to substantial agreement with humans

Conceptualizing a Cognitive Analytics Capability

Gaining value from new, emerging technologies is a major concern for information systems researchers and practitioners. Prior research is unanimous in its argument that organizations need to develop capabilities around such novel technologies in order to leverage them effectively. In this short paper, we focus on the cognitive analytics technology. While it has attracted significant hype, the returns on investment in this technology have not been very impressive. This paper uses the resource-based view as a theoretical lens, interviews with domain experts, and a review of the academic literature on cognitive analytics to conceptualize a cognitive analytics capability. We identify the tangible, human, and intangible resources that underpin an organization\u27s cognitive analytics capability. This research can potentially contribute to the academic literature on business value of information technology. It can also help organizations extract maximum benefits from their investments in cognitive analytics technology. Future avenues of research are also discussed

Aristotle on Geometrical Potentialities

This paper examines Aristotle's discussion of the priority of actuality to potentiality in geometry at Metaphysics Θ9, 1051a21–33. Many scholars have assumed what I call the "geometrical construction" interpretation, according to which his point here concerns the relation between an inquirer's thinking and a geometrical figure. In contrast, I defend what I call the "geometrical analysis" interpretation, according to which it concerns the asymmetrical relation between geometrical propositions in which one is proved by means of the other. His argument as so construed is ultimately based on the asymmetrical relation between the corresponding geometrical facts. Then I explore this ontological priority in geometry by drawing attention to a parallel passage, Posterior Analytics II.11, 94a24–35, where Aristotle explains the relation between the same geometrical propositions in connection to material causation

Aristotle’s Treatment of Fallacious Reasoning in Sophistical Refutations and Prior Analytics

Aristotle studies syllogistic argumentation in Sophistical Refutations and Prior Analytics. In the latter he focuses on the formal and syntactic character of arguments and treats the sullogismoi and non-sullogismoi as argument patterns with valid or invalid instances. In the former Aristotle focuses on semantics and rhetoric to study apparent sullogismoi as object language arguments. Interpreters usually take Sophistical Refutations as considerably less mature than Prior Analytics. Our interpretation holds that the two works are more of a piece than previously believed and, indeed, that Aristotle\u27s treatment of fallacious reasoning presupposes the results of the formal theory