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LEx: A Framework for Operationalising Layers of Machine Learning Explanations
Several social factors impact how people respond to AI explanations used...
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Conceptualising Contestability: Perspectives on Contesting Algorithmic Decisions
As the use of algorithmic systems in high-stakes decision-making increas...
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Fair and Responsible AI: A Focus on the Ability to Contest
As the use of artificial intelligence (AI) in high-stakes decision-makin...
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Designing for Contestation: Insights from Administrative Law
A paper presented at the Workshop on Contestability in Algorithmic Syste...
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Deceptive Reinforcement Learning for Privacy-Preserving Planning
In this paper, we study the problem of deceptive reinforcement learning ...
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Directive Explanations for Actionable Explainability in Machine Learning Applications
This paper investigates the prospects of using directive explanations to...
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Good proctor or "Big Brother"? AI Ethics and Online Exam Supervision Technologies
This article philosophically analyzes online exam supervision technologi...
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Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI
Trust is a central component of the interaction between people and AI, i...
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Improving Interpretability of CNN Models Using Non-Negative Concept Activation Vectors
Convolutional neural network (CNN) models for computer vision are powerf...
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Federated pretraining and fine tuning of BERT using clinical notes from multiple silos
Large scale contextual representation models, such as BERT, have signifi...
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Distal Explanations for Explainable Reinforcement Learning Agents
Causal explanations present an intuitive way to understand the course of...
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Improving Performance of Multiagent Cooperation Using Epistemic Planning
In most multiagent applications, communication is essential among agents...
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Let's Make It Personal, A Challenge in Personalizing Medical Inter-Human Communication
Current AI approaches have frequently been used to help personalize many...
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Explainable Reinforcement Learning Through a Causal Lens
Prevalent theories in cognitive science propose that humans understand a...
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What you get is what you see: Decomposing Epistemic Planning using Functional STRIPS
Epistemic planning --- planning with knowledge and belief --- is essenti...
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A Grounded Interaction Protocol for Explainable Artificial Intelligence
Explainable Artificial Intelligence (XAI) systems need to include an exp...
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Contrastive Explanation: A Structural-Model Approach
The topic of causal explanation in artificial intelligence has gathered ...
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Emotionalism within People-Oriented Software Design
In designing most software applications, much effort is placed upon the ...
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Towards a Grounded Dialog Model for Explainable Artificial Intelligence
To generate trust with their users, Explainable Artificial Intelligence ...
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Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences
In his seminal book `The Inmates are Running the Asylum: Why High-Tech P...
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Explanation in Artificial Intelligence: Insights from the Social Sciences
There has been a recent resurgence in the area of explainable artificial...
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Social planning for social HRI
Making a computational agent 'social' has implications for how it percei...
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