Visualizations for an Explainable Planning Agent

In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making. Imposing transparency and explainability requirements on such agents is especially important in order to establish trust and common ground with the end-to-end automated planning system. Visualizing the agent's internal decision-making processes is a crucial step towards achieving this. This may include externalizing the "brain" of the agent -- starting from its sensory inputs, to progressively higher order decisions made by it in order to drive its planning components. We also show how the planner can bootstrap on the latest techniques in explainable planning to cast plan visualization as a plan explanation problem, and thus provide concise model-based visualization of its plans. We demonstrate these functionalities in the context of the automated planning components of a smart assistant in an instrumented meeting space.Comment: PREVIOUSLY Mr. Jones -- Towards a Proactive Smart Room Orchestrator (appeared in AAAI 2017 Fall Symposium on Human-Agent Groups

Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making

Today, AI is being increasingly used to help human experts make decisions in high-stakes scenarios. In these scenarios, full automation is often undesirable, not only due to the significance of the outcome, but also because human experts can draw on their domain knowledge complementary to the model's to ensure task success. We refer to these scenarios as AI-assisted decision making, where the individual strengths of the human and the AI come together to optimize the joint decision outcome. A key to their success is to appropriately \textit{calibrate} human trust in the AI on a case-by-case basis; knowing when to trust or distrust the AI allows the human expert to appropriately apply their knowledge, improving decision outcomes in cases where the model is likely to perform poorly. This research conducts a case study of AI-assisted decision making in which humans and AI have comparable performance alone, and explores whether features that reveal case-specific model information can calibrate trust and improve the joint performance of the human and AI. Specifically, we study the effect of showing confidence score and local explanation for a particular prediction. Through two human experiments, we show that confidence score can help calibrate people's trust in an AI model, but trust calibration alone is not sufficient to improve AI-assisted decision making, which may also depend on whether the human can bring in enough unique knowledge to complement the AI's errors. We also highlight the problems in using local explanation for AI-assisted decision making scenarios and invite the research community to explore new approaches to explainability for calibrating human trust in AI

Is Domestic Abuse an Adult Social Work Issue?

Within a global profession with a stated definition that includes ‘promoting social change and development, social cohesion and the empowerment and liberation of people’ (online), it would be expected that the issue of domestic abuse would be integral to the training and role of all social workers. This article reports on research, which highlighted both a lack of understanding of the role of adult social worker within cases of domestic abuse and also a desire for further training around the issue. However, this article sets out how the current UK (in particular, English) context of social work marginalises the issue of domestic abuse within practice with adults. This marginalisation has been achieved through the construction of domestic abuse as a children and families issue and limited duties, powers and resources within statutory work to support victims/survivors in their own right, rather than as ‘failing’ parents. However, the article argues that the role of social work education should be wider than teaching to the current policy or procedures and instead encourage a wider appreciation of the social, historical and political context. The article concludes with tentative suggestions for how domestic abuse could be considered within the social work curriculum for adult practitioners. This is in acknowledgement that social workers can be well positioned for the detection, investigation and support of those experiencing abuse

Hurricane Ridge downhill ski area improvement plan proposal: environmental impact assessment

1.1 Purpose This Environmental Impact Assessment (EIA) aims to evaluate the potential impacts of updating the infrastructure of Hurricane Ridge Ski and Snowboard Area in Olympic National Park. The Hurricane Ridge Winter Sports Club (HRWSC) means to replace the current lifts, which have been in service more than 50 years, and are on the end of their service lives. In this document, the proposed action and an alternative are investigated for potential impacts on the National Park land and surrounding communities; the future prospects of removing the Ski Area\u27s lifts are likewise considered. Both action alternatives replace the current POMA lift and rope tows with a Magic Carpet lift, a new rope tow, and a similar surface lift, all powered by electricity produced by a central diesel generator, rather than the current system of gasoline powered, mechanically driven lifts. No action would involve removing the lift systems once they have deprecated beyond repair. 1.2 Site Hurricane Ridge Ski and Snowboard Area is the westernmost lift-­‐operated ski area in the Lower 48, one of 3 located within National Park lands, and the only one on the Olympic Peninsula. Seventeen miles up Heart O\u27 the Hills Road from Port Angeles, Hurricane Ridge provides downhill and cross-­‐country skiing, snowboarding, and snowshoeing opportunities to residents of the Olympic and Kitsap Peninsulas. With two rope tows and one surface lift, the Ski and Snowboard Area aims to serve some 5,500 people each winter, depending on weather conditions. The POMA surface lift is dependent on snow accumulation to open, often pushing back its first day of operation to the end of January. The rope tows tend to begin operation a couple weeks prior to the POMA lift opening. Cross-­‐country skiers and snowshoers typically see their season start in December. The Winter Sports Club provides lessons and hosts some events each season, which tend to last until April. Hurricane Ridge has a base elevation of approximately 4,800 feet, with a peak of 5,500. The Ski Area installation predated the National Environmental Protection Act, so no Environmental Impact Statement was required at the time it was built. 1.3 Problem Hurricane Ridge Ski and Snowboard Area is no longer eligible for or capable of repairs – the manufacturer will not issue parts for liability reasons related to the age of the equipment. In order to preserve skiing in the Olympics for the future, Hurricane Ridge Winter Sports Club wants to replace the lifts with modern equipment. 1.3.1 Proposed Action The proposed action is to replace the POMA lift with a modern surface lift, the beginner rope tow with a Magic Carpet surface lift, and a new rope tow on the intermediate rope tow. All three lifts will be powered by electricity produced by a central diesel power generator rather than the current three independent gasoline motors mechanically driving the lifts. The new surface lift in the POMA bowl would include filling gullies to allow for an earlier opening of the POMA lift, therefore increasing the length of the viable ski season. 1.3.2 Alternative Action The alternative course of action proposed is identical to the initial proposal, except for filling the gullies in the POMA bowl. The alternative proposal is to build a bridge-­‐type structure above the gullies, which would allow the lift to open earlier but also permit melt water runoff to drain into the gullies and down into the Elwha watershed. The alternative action aims to mimic the benefit of bumping up opening day for the HRSSA by effectively leveling the gullies under snowfall, but in a way sensitive to hydrology present in the landscape. All other upgrades to the lifts remain the same as the initial proposal. 1.3.3 No Action Alternative No action on the HRSSA would lead to inevitable closure due to the lifts falling into disrepair within five years, as estimated by the Winter Sports Club. Once all three lifts are unusable they would be removed, and the landscape of Hurricane Ridge would restore itself to its natural condition. No lifts would operate on the Olympic Peninsula. 1.4 Recommendation The recommended action is to follow the alternative action because it reflects the benefits of the proposed action, while minimizing the impacts that would result from gully fill. By creating a structure that would permit runoff and melt water to pass down the slope, erosion would remain in its natural state. Filling the gullies would alter the hydrology, and likely be eroded swiftly if too soft or not anchored with plant life, thus impacting the watershed of the Elwha River. Fill may also be sourced from a location that would not match the soil profile of the lift path or may be contaminated. These risks can be avoided by installing permanent structures, which would fix the path of the T-­‐bar lift in the ski season while not interrupting natural hydrological processes

The effect of ambient sounds on decision-making and heart rate variability in autism.

Many autistic people report difficulties making decisions during everyday tasks, such as shopping. To examine the effect of sounds on decision-making, we developed a supermarket task where people watched a film shown from the shopper's perspective and were asked to make decisions between different products. The task was divided into three sections and participants completed each section in a different auditory environment: (1) no sounds, (2) non-social sounds (e.g. fridges humming) and (3) social sounds (e.g. people talking). Thirty-eight autistic and 37 neurotypical adults took part. We measured decision-making by examining how long it took to make a decision and how consistent people were with their decisions. We also measured heart rate variability because this biological response provides a measure of anxiety. After the supermarket shopping task, participants told us in their own words about their experiences. Autistic participants said that they found the non-social and social sound conditions more difficult than the no sound condition, and autistic participants found the social sound condition more negative than neurotypical participants. However, decision-making and heart rate variability were similar for autistic and neurotypical participants across the sound conditions, suggesting that these measures may not have been sensitive enough to reflect the experiences the autistic participants reported. Further research should consider alternative measures to explore the experiences reported by autistic people to help us understand which specific aspects of the environment autistic people are sensitive to. This, in turn, may enable more specific and evidence-based autism-friendly changes to be made.Anonymous donatio

Bootstrapping Conversational Agents With Weak Supervision

Many conversational agents in the market today follow a standard bot development framework which requires training intent classifiers to recognize user input. The need to create a proper set of training examples is often the bottleneck in the development process. In many occasions agent developers have access to historical chat logs that can provide a good quantity as well as coverage of training examples. However, the cost of labeling them with tens to hundreds of intents often prohibits taking full advantage of these chat logs. In this paper, we present a framework called \textit{search, label, and propagate} (SLP) for bootstrapping intents from existing chat logs using weak supervision. The framework reduces hours to days of labeling effort down to minutes of work by using a search engine to find examples, then relies on a data programming approach to automatically expand the labels. We report on a user study that shows positive user feedback for this new approach to build conversational agents, and demonstrates the effectiveness of using data programming for auto-labeling. While the system is developed for training conversational agents, the framework has broader application in significantly reducing labeling effort for training text classifiers.Comment: 6 pages, 3 figures, 1 table, Accepted for publication in IAAI 201