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Visual Analytics for Fine-grained Text Classification Models and Datasets
As a consequence, the semantic structures of datasets have become more complex, and model decisions more difficult to explain.
Reclaiming the Horizon: Novel Visualization Designs for Time-Series Data with Large Value Ranges
It focuses on four main tasks commonly employed in the analysis of time-series and large value ranges visualization: identification, discrimination, estimation, and trend detection.
Color Coding of Large Value Ranges Applied to Meteorological Data
We focus on meteorological data, where the presence of large value ranges is common.
The Development of Visualization Psychology Analysis Tools to Account for Trust
Defining trust is an important endeavor given its applicability to assessing public mood to much of the innovation in the newly formed autonomous industry, such as artificial intelligence (AI), medical bots, drones, autonomous vehicles, and smart factories [19]. Through developing a reliable index or means to measure trust, this may have wide impact from fostering acceptance and adoption of smart systems to informing policy makers about the public atmosphere and willingness to adopt innovate change, and has been identified as an important indicator in a recent UK policy brief [8]. In this paper, we reflect on the importance and potential impact of developing Visualization Psychology in the context of solving definitions and policy decision making problems for complex constructs such as "trust".
Towards Providing Explanations for AI Planner Decisions
In order to engender trust in AI, humans must understand what an AI system is trying to achieve, and why.
