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Keane, Mark T.
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Keane, Mark T.
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Keane, Mark T.
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Now showing 1 - 10 of 35
- PublicationSurprising findings: Comparing patterns of surprise, explanation, and probability(2015-03-14)
; Why are some events more surprising than others? We suggest that some surprises are more surprising because they are harder to explain.Two factors impacting surprise are explored here:different classes of surprising outcome (Outcome-Type) increasing/decreasing the difficulty of explaining with added cues (Keywords)Three experiments using the same materials but different measures: 1) produced explanations, 2) surprise ratings, and 3) subjective probability ratings.127 - PublicationOn Supporting Digital Journalism: Case Studies in Co-Designing Journalistic Tools(2017-10-14)
; ; ; ; ; Since 2013 researchers at University College Dublin in the Insight Centre for Data Analytics have been involved in a significant research programme in digital journalism, specifically targeting tools and social media guidelines to support the work of journalists. Most of this programme was undertaken in collaboration with The Irish Times. This collaboration involved identifying key problems currently faced by digital journalists, developing tools as solutions to these problems, and then iteratively co-designing these tools with feedback from journalists. This paper reports on our experiences and learnings from this research programme, with a view to informing similar efforts in the future.187 - PublicationPlotting Markson's "Mistress"The post-modern novel WittgensteinsMistress by David Markson (1988) presentsthe reader with a very challengingnon-linear narrative, that itself appears toone of the novels themes. We present adistant reading of this work designed tocomplement a close reading of it by DavidFoster Wallace (1990). Using a combinationof text analysis, entity recognition andnetworks, we plot repetitive structures inthe novels narrative relating them to itscritical analysis.
378 - PublicationA Computational Theory of Subjective Probability [Featuring a Proof that the Conjunction Effect is not a Fallacy](Cognitive Science Society, 2013-08-03)
; ; ; In this article we demonstrate how algorithmic probability theory is applied to situations that involve uncertainty. When people are unsure of their model of reality, then the outcome they observe will cause them to update their beliefs. We argue that classical probability cannot be applied in such cases, and that subjective probability must instead be used. In Experiment 1 we show that, when judging the probability of lottery number sequences, people apply subjective rather than classical probability. In Experiment 2 we examine the conjunction fallacy and demonstrate that the materials used by Tverksy and Kahneman(1983) involve model uncertainty. We then provide a formal mathematical proof that, for every uncertain model, there exists a conjunction of outcomes which is more subjectively probable than either of its constituents in isolation.100 - PublicationBayesian Case-Exclusion and Explainable AI (XAI) for Sustainable Farming(2021-01-15)
; ; ; ; ; Smart agriculture (SmartAg) has emerged as a rich domain for AI-driven decision support systems (DSS); however, it is often challenged by user-adoption issues. This paper reports a case-based reasoning system, PBI-CBR, that predicts grass growth for dairy farmers, that combines predictive accuracy and explanations to improve user adoption. PBI-CBR’s key novelty is its use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for different variants of PBI-CBR, and how updating Bayesian priors each year improves performance.354 - PublicationThe Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning(2019-08-11)
; The notion of twin-systems is proposed to address the eXplainable AI (XAI) problem, where an uninterpretable black-box system is mapped to a white-box “twin” that is more interpretable. In this short paper, we overview very recent work that advances a generic solution to the XAI problem, the so-called twin-system approach. The most popular twinning in the literature is that between an Artificial Neural Networks (ANN1) as a black box and Case Based Reasoning (CBR) system as a white-box, where the latter acts as an interpretable proxy for the former. We outline how recent work reviving this idea has applied it to deep learning methods. Furthermore, we detail the many fruitful directions in which this work may be taken; such as, determining the most (i) accurate feature-weighting methods to be used, (ii) appropriate deployments for explanatory cases, (iii) useful cases of explanatory value to users.276 - PublicationThe Unexpected Unexpected and the Expected Unexpected: How People's Conception of the Unexpected is Not That Unexpected(2019-07-27)
; ; The answers people give when asked to “think of the unexpected” for everyday event scenarios appear to be more expected than unexpected. There are expected unexpected outcomes that closely adhere to the given information in ascenario, based on familiar disruptions and common plan-failures.There are also unexpected unexpected outcomesthat are more inventive, that depart from given information, adding new concepts/actions. However, people seem to tend to conceive of the unexpected as the former more than the latter. Study 1 tests these proposals by analysing the object-concepts people mention in their reports of the unexpected and the agreement between their answers. Study 2 shows that object-choices are weakly influenced by recency, that is, the order of sentences in the scenario. The implications of these results for ideas in philosophy, psychology and computing are discussed.254 - PublicationA neural network model of Irish farmers perceptions of land mobility(2015-03-10)
; ; ; Land has always been one of the most important and controversial assets in Ireland and land mobility continues to be a critical issue to the future success of the Irish agricultural sector (FH2020). The Irish agricultural sector is still portrayed by a low level of land mobility and late transfer pattern with small farms and an older farming population. Policies and schemes applied to the agricultural sector to improve land mobility situation appear to be failing to have the desired effect. The overall objective of this study is to assess the present situation and identify potential solutions that could improve land mobility and smooth land transfer in the Irish agricultural sector as perceived by the Irish farmer.140 - PublicationRe-reading the Ryan report: Witnessing via close and distant readingIn the days following the publication of the Final Report of the Commission to Inquire into Child Abuse (2009), also known as the Ryan Report, there was widespread national and international public reaction to the conclusions of the report that over the course of nine decades abuse had been severe and systemic in the Irish residential-institution system for children run by the religious congregations of the Catholic church.
493Scopus© Citations 7 - PublicationModeling and Predicting News Consumption on TwitterRelatively little is known about the news consumption amongst social media users, despite the proliferation of news sharing, distribution platforms and news aggregators. In this paper, we present the Twitter News Model (TNM), a computational data-driven approach to elucidate the dynamics of news consumption on Twitter. We apply the TNM to a dataset of interactions between users and journalists/ newspapers to reveal what drives users’ consumption of news on Twitter, and predictively relate users’ news beliefs, motivations, and attitudes to their consumption of news.
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