69,789 research outputs found
Natural Language Generation enhances human decision-making with uncertain information
Decision-making is often dependent on uncertain data, e.g. data associated
with confidence scores or probabilities. We present a comparison of different
information presentations for uncertain data and, for the first time, measure
their effects on human decision-making. We show that the use of Natural
Language Generation (NLG) improves decision-making under uncertainty, compared
to state-of-the-art graphical-based representation methods. In a task-based
study with 442 adults, we found that presentations using NLG lead to 24% better
decision-making on average than the graphical presentations, and to 44% better
decision-making when NLG is combined with graphics. We also show that women
achieve significantly better results when presented with NLG output (an 87%
increase on average compared to graphical presentations).Comment: 54th annual meeting of the Association for Computational Linguistics
(ACL), Berlin 201
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Weather, climate, and hydrologic forecasting for the US Southwest: A survey
As part of a regional integrated assessment of climate vulnerability, a survey was conducted from June 1998 to May 2000 of weather, climate, and hydrologic forecasts with coverage of the US Southwest and an emphasis on the Colorado River Basin. The survey addresses the types of forecasts that were issued, the organizations that provided them, and techniques used in their generation. It reflects discussions with key personnel from organizations involved in producing or issuing forecasts, providing data for making forecasts, or serving as a link for communicating forecasts. During the survey period, users faced a complex and constantly changing mix of forecast products available from a variety of sources. The abundance of forecasts was not matched in the provision of corresponding interpretive materials, documentation about how the forecasts were generated, or reviews of past performance. Potential existed for confusing experimental and research products with others that had undergone a thorough review process, including official products issued by the National Weather Service. Contrasts between the state of meteorologic and hydrologic forecasting were notable, especially in the former's greater operational flexibility and more rapid incorporation of new observations and research products. Greater attention should be given to forecast content and communication, including visualization, expression of probabilistic forecasts and presentation of ancillary information. Regional climate models and use of climate forecasts in water supply forecasting offer rapid improvements in predictive capabilities for the Southwest. Forecasts and production details should be archived, and publicly available forecasts should be accompanied by performance evaluations that are relevant to users
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Factors affecting seasonal forecast use in Arizona water management: A case study of the 1997-98 El Niño
The 1997-98 El Niño was exceptional, not only because of its magnitude, but also because of the visibility and use of its forecasts. The 3 to 9 mo advance warning of a wet winter with potential flooding in the US Southwest, easily accessible by water management agencies, was unprecedented. Insights about use of this information in operational water management decision processes were developed through a series of semi-structured in-depth interviews with key personnel from a broad array of agencies responsible for emergency management and water supply, with jurisdictions ranging from urban to rural and local to regional. Interviews investigated where information was acquired, how it was interpreted and how it was incorporated into specific decisions and actions. In addition, technical and institutional barriers to forecast use are explored. Study findings emphasize (1) the need for special handling of tailored forecast products on a regional scale, (2) the need for systematic regional forecast evaluation and (3) the potential for climate information to directly affect water management decisions through integrating climate forecasts into water supply outlooks where appropriate
Weather and Climate Information for Tourism
The tourism sector is one of the largest and fastest growing global industries and is a significant contributor to national and local economies around the world. The interface between climate and tourism is multifaceted and complex, as climate represents both a vital resource to be exploited and an important limiting factor that poses risks to be managed by the tourism industry and tourists alike. All tourism destinations and operators are climate-sensitive to a degree and climate is a key influence on travel planning and the travel experience. This chapter provides a synopsis of the capacities and needs for climate services in the tourism sector, including current and emerging applications of climate services by diverse tourism end-users, and a discussion of key knowledge gaps, research and capacity-building needs and partnerships that are required to accelerate the application of climate information to manage risks to climate variability and facilitate successful adaptation to climate change
Short interval control for the cost estimate baseline of novel high value manufacturing products – a complexity based approach
Novel high value manufacturing products by default lack the minimum a priori data needed for forecasting cost variance over of time using regression based techniques. Forecasts which attempt to achieve this therefore suffer from significant variance which in turn places significant strain on budgetary assumptions and financial planning. The authors argue that for novel high value manufacturing products short interval control through continuous revision is necessary until the context of the baseline estimate stabilises sufficiently for extending the time intervals for revision. Case study data from the United States Department of Defence Scheduled Annual Summary Reports (1986-2013) is used to exemplify the approach. In this respect it must be remembered that the context of a baseline cost estimate is subject to a large number of assumptions regarding future plausible scenarios, the probability of such scenarios, and various requirements related to such. These assumptions change over time and the degree of their change is indicated by the extent that cost variance follows a forecast propagation curve that has been defined in advance. The presented approach determines the stability of this context by calculating the effort required to identify a propagation pattern for cost variance using the principles of Kolmogorov complexity. Only when that effort remains stable over a sufficient period of time can the revision periods for the cost estimate baseline be changed from continuous to discrete time intervals. The practical implication of the presented approach for novel high value manufacturing products is that attention is shifted from the bottom up or parametric estimation activity to the continuous management of the context for that cost estimate itself. This in turn enables a faster and more sustainable stabilisation of the estimating context which then creates the conditions for reducing cost estimate uncertainty in an actionable and timely manner
Weather and Climate Information for Tourism
The tourism sector is one of the largest and fastest growing global industries and is a significant contributor to national and local economies around the world. The interface between climate and tourism is multifaceted and complex, as climate represents both a vital resource to be exploited and an important limiting factor that poses risks to be managed by the tourism industry and tourists alike. All tourism destinations and operators are climate-sensitive to a degree and climate is a key influence on travel planning and the travel experience. This chapter provides a synopsis of the capacities and needs for climate services in the tourism sector, including current and emerging applications of climate services by diverse tourism end-users, and a discussion of key knowledge gaps, research and capacity-building needs and partnerships that are required to accelerate the application of climate information to manage risks to climate variability and facilitate successful adaptation to climate change
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