Subscribe: cs.CY updates on
Added By: Feedage Forager Feedage Grade A rated
Language: English
arxiv  china studies  journal  knowledge work  knowledge  machine  mainland china  shared control  shared  studies  study  topics  work 
Rate this Feed
Rate this feedRate this feedRate this feedRate this feedRate this feed
Rate this feed 1 starRate this feed 2 starRate this feed 3 starRate this feed 4 starRate this feed 5 star

Comments (0)

Feed Details and Statistics Feed Statistics
Preview: cs.CY updates on

cs.CY updates on

Computer Science -- Computers and Society (cs.CY) updates on the e-print archive

Published: 2018-03-20T20:30:00-05:00


Mechanisms for producing a working knowledge: Enacting, orchestrating and organizing. (arXiv:1803.07153v1 [cs.CY])

Given that knowledge (intensive) work takes place immersed in truly heterogenous networks of knowledge representations (codified, narrative, embedded in routines, inscribed in artefacts), our analysis is geared towards how the transformation of these resources are enacted in the practise of everyday, knowledge work. First, we discuss the work, strategies and mechanisms implied in rendering knowledge as credible, trustworthy and relevant. Second, we analyse how sediments of historically superimposed layers of knowledge representations need to be enacted through selective repetitions, omittance and highlighting to preserve it as living knowledge. Third, supplementing the more cognitivelly oriented aspects of knowledge work, we discuss how codified knowledge representations organise, coordinate and delegate work. Empirically, we study clinical work in large hospitals, a type of work, we argue, that unduely has been left out of traditional listings of knowledge work

The nested materiality of environmental monitoring. (arXiv:1803.07157v1 [cs.CY])

Present knowledge about the marine ecosystem on the Norwegian Continental Shelf towards the Arctic is sparse. These areas are vast, remote and subject to harsh weather conditions. We report from a three-year case study of an ongoing effort for real-time, subsea environmental monitoring by an oil and gas operator. The facts about the subsea environment are anything but neutral; they are intrinsically caught up with the material means by which they are known. The marine ecosystem is monitored through a network of sensors, communication links, visualisation and analysis tools. Our concept of nested materiality draws heavily on perspectives in sociomateriality but highlights (i) the distributed and interconnected infrastructure of the material means (as opposed to artefact-centric) and (ii) in-the-making (as opposed to black-boxed) technology.

Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation. (arXiv:1803.07170v1 [cs.AI])

When a semi-autonomous car crashes and harms someone, how are blame and causal responsibility distributed across the human and machine drivers? In this article, we consider cases in which a pedestrian was hit and killed by a car being operated under shared control of a primary and a secondary driver. We find that when only one driver makes an error, that driver receives the blame and is considered causally responsible for the harm, regardless of whether that driver is a machine or a human. However, when both drivers make errors in cases of shared control between a human and a machine, the blame and responsibility attributed to the machine is reduced. This finding portends a public under-reaction to the malfunctioning AI components of semi-autonomous cars and therefore has a direct policy implication: a bottom-up regulatory scheme (which operates through tort law that is adjudicated through the jury system) could fail to properly regulate the safety of shared-control vehicles; instead, a top-down scheme (enacted through federal laws) may be called for.

Closing the AI Knowledge Gap. (arXiv:1803.07233v1 [cs.CY])

AI researchers employ not only the scientific method, but also methodology from mathematics and engineering. However, the use of the scientific method - specifically hypothesis testing - in AI is typically conducted in service of engineering objectives. Growing interest in topics such as fairness and algorithmic bias show that engineering-focused questions only comprise a subset of the important questions about AI systems. This results in the AI Knowledge Gap: the number of unique AI systems grows faster than the number of studies that characterize these systems' behavior. To close this gap, we argue that the study of AI could benefit from the greater inclusion of researchers who are well positioned to formulate and test hypotheses about the behavior of AI systems. We examine the barriers preventing social and behavioral scientists from conducting such studies. Our diagnosis suggests that accelerating the scientific study of AI systems requires new incentives for academia and industry, mediated by new tools and institutions. To address these needs, we propose a two-sided marketplace called TuringBox. On one side, AI contributors upload existing and novel algorithms to be studied scientifically by others. On the other side, AI examiners develop and post machine intelligence tasks designed to evaluate and characterize algorithmic behavior. We discuss this market's potential to democratize the scientific study of AI behavior, and thus narrow the AI Knowledge Gap.

How the Taiwanese Do China Studies: Applications of Text Mining. (arXiv:1801.00912v2 [cs.DL] UPDATED)

With the rapid evolution of cross-strait situation, "Mainland China" as a subject of social science study has evoked the voice of "Rethinking China Study" among intelligentsia recently. This essay tried to apply an automatic content analysis tool (CATAR) to the journal "Mainland China Studies" (1998-2015) in order to observe the research trends based on the clustering of text from the title and abstract of each paper in the journal. The results showed that the 473 articles published by the journal were clustered into seven salient topics. From the publication number of each topic over time (including "volume of publications", "percentage of publications"), there are two major topics of this journal while other topics varied over time widely. The contribution of this study includes: 1. We could group each "independent" study into a meaningful topic, as a small scale experiment verified that this topic clustering is feasible. 2. This essay reveals the salient research topics and their trends for the Taiwan journal "Mainland China Studies". 3. Various topical keywords were identified, providing easy access to the past study. 4. The yearly trends of the identified topics could be viewed as signature of future research directions.