Report of ECol Workshop Report on the First International Workshop on the Evaluation on Collaborative Information Seeking and Retrieval (ECol'2015)

Report of the ECol Workshop @ CIKM 2015The workshop on the evaluation of collaborative information retrieval and seeking (ECol) was held in conjunction with the 24 th Conference on Information and Knowledge Management (CIKM) in Melbourne, Australia. The workshop featured three main elements. First, a keynote on the main dimensions, challenges, and opportunities in collaborative information retrieval and seeking by Chirag Shah. Second, an oral presentation session in which four papers were presented. Third, a discussion based on three seed research questions: (1) In what ways is collaborative search evaluation more challenging than individual interactive information retrieval (IIIR) evaluation? (2) Would it be possible and/or useful to standardise experimental designs and data for collaborative search evaluation? and (3) For evaluating collaborative search, can we leverage ideas from other tasks such as diversified search, subtopic mining and/or e-discovery? The discussion was intense and raised many points and issues, leading to the proposition that a new evaluation track focused on collaborative information retrieval/seeking tasks, would be worthwhile

Collective Cognitive Capital

This Article calls for a new project for law and neuroscience. It outlines a structural, not individual, application of brain and behavioral science that is aligned with the general goal of basic science research: improving the lives of citizens with a better understanding of the human experience. It asks brain and behavioral science to move explicitly into public policy territory, and specifically onto ground more traditionally occupied by economists—but in ways the project of “behavioral economics” has not yet ventured. Put simply, policy analysts should focus on brains—“collective cognitive capital”—with the same intensity with which they focus on money, rights, or other policy metrics. To that end, this Article introduces and explores the novel framework of “collective cognitive capital”: a way of thinking of brain health and brain function as an aggregated resource. Collective cognitive capital is a conceptual framework for synthesizing brain and behavioral data and using it to assess the impacts of policy choices. The core thesis for this future of “law and neuroscience” is simple: we can and should use brain and behavioral science to evaluate public policy decisions by how they affect the brain functioning of the people. Normatively, policies should seek to maximize “collective cognitive capital” because it is inherently valuable. Cognitive and emotional functioning, and overall brain health, subserve and maximize individual agency and freedom

Minding Accidents

Tort doctrine states that breach is all about conduct. Unlike in the criminal law context, where jurors must engage in amateur mindreading to evaluate mens rea, jurors are told that they can assess civil negligence by looking only at the defendant’s external behavior. But this is false. Here I explain why, by incorporating the psychology of foresight. Foreseeability is at the heart of negligence—appearing as the primary test for duty, breach, and proximate cause. And yet, it has been called a “vexing morass” and a “malleable standard” because it is so poorly understood. This Article refines and advances the construct of foresight by describing it as an epistemic mental state—similar to intent, knowledge, or recklessness. We cannot ask whether a defendant should have foreseen a risk without interrogating what they subjectively perceived, realized, or remembered at the time. Indeed, the focus on actions in negligence is misleading because unreasonable actions are not necessary for negligence liability, while a negligent mental state is. It is time for negligence doctrine to “mind” accidents. Unfortunately, when we assume that foreseeability can be assessed objectively through conduct, jurors are left rudderless to engage in hindsight bias. The phrasing of “objectively reasonable foreseeability” encourages jurors to superimpose what should have been foreseen ex post on what could have been foreseen ex ante. Further, while the outputs of mental states may be labeled reasonable or unreasonable, some of the underlying mental states themselves cannot be. There is no such thing as “objectively reasonable memory” or “objectively reasonable perception.” If we are committed to basing negligence on breach, we must pay more attention to whether a particular defendant is capable of foresight. This is not about eliminating the reasonable person standard, but rather recognizing that what is reasonable is constrained by what is possible. Given these insights, I propose significant revisions to negligence doctrine. I reshuffle and simplify the prima facie elements to focus the jury’s attention on the descriptive aspects of breach (i.e., whether foresight and prevention were possible in this instance) and the judge’s attention on the normative aspects (whether there should be duties imposed in cases like this and whether this particular defendant should be held responsible). This proposal aims to decrease hindsight bias by requiring an assessment of the defendant’s capacity for foresight before asking whether the outputs of this mental process were reasonable. My proposal brings to the surface processes that are already occurring. It has the added benefit of distinguishing the tests for duty, breach, and proximate cause, which at present overlap considerably. Because breach, proximate cause, and duty all ask whether the outcome was reasonably foreseeable, courts frequently conflate the breach analysis (which should be for the jury) with that of duty (for the judge). My proposal eliminates this confusion by defining descriptive elements that are uniquely for the jury and normative elements that are uniquely for the judge

Time- and space-dependent uncertainty analysis and its application in lunar plasma environment modeling

”During an engineering system design, engineers usually encounter uncertainties that ubiquitously exist, such as material properties, dimensions of components, and random loads. Some of these parameters do not change with time or space and hence are time- and space-independent. However, in many engineering applications, the more general time- and space-dependent uncertainty is frequently encountered. Consequently, the system exhibits random time- and space-dependent behaviors, which may result in a higher probability of failure, lower average lifetime, and/or worse robustness. Therefore, it is critical to quantify uncertainty and predict how the system behaves under time- and space- dependent uncertainty. The objective of this study is to develop accurate and efficient methods for uncertainty analysis. This study contains five works. In the first work, an accurate method based on the series expansion, Gauss-Hermite quadrature, and saddle point approximation is developed to calculate high-dimensional normal probabilities. Then the method is applied to estimate time-dependent reliability. In the second work, we develop an adaptive Kriging method to estimate product average lifetime. In the third work, a time- and space-dependent reliability analysis method based on the first-order and second-order methods is proposed. In the fourth work, we extend the existing robustness analysis to time- and space-dependent problems and develop an adaptive Kriging method to evaluate the time- and space-dependent robustness. In the fifth work, we develop an adaptive Kriging method to efficiently estimate the lower and upper bounds of the electric potentials of the photoelectron sheaths near the lunar surface”--Abstract, page iv

The Consensus Rule: A New Approach to Scientific Evidence

Founded on good intentions but unrealistic expectations, the dominant Daubert framework for handling expert and scientific evidence should be scrapped. Daubert asks judges and jurors to make substantively expert determinations, a task they are epistemically incompetent to perform as laypersons. As an alternative, this Article proposes a new framework for handling expert evidence. It draws from the social and philosophical literature on expertise and begins with a basic question: How can laypersons make intelligent decisions about expert topics? From there, it builds its evidentiary approach, which ultimately results in an inference rule focused on expert communities. Specifically, when dealing with factual issues involving expertise, the legal system should not ask factfinders the actual substantive questions, but instead should reframe its questions to be deferential to the relevant expert community. To satisfy the requirement of proving causation in a toxic tort case, the question should not be: Does drug A cause disease X? The more appropriate question is: Does the scientific community believe that drug A causes disease X? This deferential approach solves the epistemic competency problem, repairs many of the unintended structural distortions created by Daubert, and ultimately reflects a better understanding of science

Developing Learning Analytics for Epistemic Commitments in a Collaborative Information Seeking Environment

Learning analytics sits at the confluence of learning, information, and computer sciences. Using a distinctive account of learning analytics as a form of assessment, I first argue for its potential in pedagogically motivated learning design, suggesting a particular construct – epistemic cognition in literacy contexts – to probe using learning analytics. I argue for a recasting of epistemic cognition as ‘epistemic commitments’ in collaborative information tasks drawing a novel alignment between information seeking and multiple document processing (MDP) models, with empirical and theoretical grounding given for a focus on collaboration and dialogue in such activities. Thus, epistemic commitments are seen in the ways students seek, select, and integrate claims from multiple sources, and the ways in which their collaborative dialogue is brought to bear in this activity. Accordingly, the empirical element of the thesis develops two pedagogically grounded literacy based tasks: a MDP task, in which pre-selected documents were provided to students; and a collaborative information seeking task (CIS), in which students could search the web. These tasks were deployed at scale (n > 500) and involved writing an evaluative review, followed by a pedagogically supported peer assessment task. Assessment outcomes were analysed in the context of a new epistemic commitments-oriented set of trace data, and psychometric data regarding the participants’ epistemic cognition. Demonstrating the value of the methodological and conceptual approach taken, qualitative analyses indicate clear epistemic activity, and stark differences in behaviour between groups, the complexity of which is challenging to model computationally. Despite this complexity, quantitative analyses indicate that up to 30% of variance in output scores can be modelled using behavioural indicators. The explanatory potential of behaviourally-oriented models of epistemic commitments grounded in tool-interaction and collaborative dialogue is demonstrated. The thesis provides an exemplification of theoretically positioned analytic development, drawing on interdisciplinary literatures in addressing complex learning contexts

The Comparative Sociology Of Disabled Masculinities: A Bourdieusian Analysis Of Autobiographies By Men With Spinal Cord Injuries and Autism Spectrum Conditions

Sociological examinations of the intersection between disability and masculinity remain underdeveloped. While insightful analyses have considered the mechanisms through which impairments may interrupt socially valued performances of masculinity, a number of key limitations persist. Extant work within the field has not considered in sufficient depth and complexity: the comparative diversity of the gender/disability intersection; the role(s) of affective embodiment; and the generative interaction between distinct impairment forms and strategic enactments of masculinity. Employing forty published autobiographies from men with Spinal Cord Injuries and Autism Spectrum Conditions, this thesis uses Bourdieusian social theory to conceptualise the dynamic interaction between corporeality and overlapping experiences of privilege/exclusion. Spinal Cord Injuries are conceived of as radically disrupting possessed and anticipated gendered resources, alongside a relative stability of culturally normative, internalised prisms of masculine self-evaluation. Yet, narrators within this group negotiated the encompassing social environment with a knowing, gendered fluidity, through narrative practices of rugged heroism, the privileging of the cerebral, and participation within masculinising interdependencies. Autism Spectrum Conditions were, similarly, conceptualised as involving limited access to valued gendered resources; yet, a phenomenologically disjunctured embodiment of taken-for-granted meaning appeared to interrupt dialectics between internalised and externalised modes of self-evaluation. This group’s “alien” habitus could motivate scholastic forms of learning designed to develop “social skills”, often fostering gendered practices that were recognisably “masculine”, but lacking in interpersonal/cultural fluidity. The thesis concludes with a comparative examination of the two groups under consideration, contending that, alongside significant points of resonance, their experiences were tremendously distinctive in terms of gendered embodiment, temporality, the habitus, social/biomedical interventions, and the “feel for the game”

The Death of the Legal Subject

The law is often engaged in prediction. In the calculation of tort damages, for example, a judge will consider what the tort victim’s likely future earnings would have been, but for their particular injury. Similarly, when considering injunctive relief, a judge will assess whether the plaintiff is likely to suffer irreparable harm if a preliminary injunction is not granted. And for the purposes of a child custody evaluation, a judge will consider which parent will provide an environment that is in the best interests of the child. Relative to other areas of law, criminal law is oversaturated with prediction. Almost every decision node in the criminal justice system demands a prediction of individual behavior: does the accused present a flight risk, or a danger to the public (pre-trial detention); is the defendant likely to recidivate (sentencing); and will the defendant successfully reenter society (parole)? Increasingly, these predictions are made by algorithms, many of which display racial bias, and are hidden from public view. Existing scholarship has focused on de-biasing and disclosing algorithmic models, but this Article argues that even a transparent and unbiased algorithm may undermine the epistemic legitimacy of a judicial decision. Law has historically generated truth claims through discursive and dialogic practices, using shared linguistic tools, in an environment characterized by proximity and reciprocity. In contrast, the truth claims of data science are generated from data processing of such scale and complexity that it is not commensurable with, or reversible to, human reasoning. Data science excludes the individual from the production of knowledge about themselves on the basis that “unmediated” behavioral data (not self-reported or otherwise subject to conscious manipulation by the data subject) offers unrivaled predictive accuracy. Accordingly, data science discounts the first-person view of reality that has traditionally underwritten legal processes of truth-making, such as individual testimony. As judges turn to algorithms to guide their decision making, knowledge about the legal subject is increasingly algorithmically produced. Statistical predictions about the legal subject displace qualitative knowledge about their intentions, motivations, and moral capabilities. The reasons why a particular defendant might refrain from recidivism, for example, become less important than the statistical features they share with historical recidivists. This displacement of individual knowledge with algorithmic predictions diminishes the participation of the legal subject in the epistemic processes that determine their fundamental liberties. This produces the death of the legal subject, or the emergence of new, algorithmic practices of signification that no longer require the input of the underlying individual

神経回路網における無意識的推論 : 電気生理と学習理論

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 神保 泰彦, 東京大学教授 鳥居 徹, 理化学研究所客員教授 深井 朋樹, 東京大学准教授 小谷 潔, 東京大学講師 高橋 宏知University of Tokyo(東京大学