Q Vera Liao

is this you? claim profile

∙ 0 followers
ibm

Featured Co-authors

Maarten de Rijke
118 publications
Pin-Yu Chen
108 publications
Kush R. Varshney
54 publications
Adrian Weller
50 publications
Karthikeyan Shanmugam
38 publications
Karthikeyan Natesan Ramamurthy
36 publications
Mark O. Riedl
33 publications
Prasanna Sattigeri
31 publications
Yunfeng Zhang
25 publications
Dennis Wei
25 publications
Amit Dhurandhar
23 publications

The Who in Explainable AI: How AI Background Shapes Perceptions of AI Explanations

Explainability of AI systems is critical for users to take informed acti...
07/28/2021 ∙ by Upol Ehsan, et al. ∙ 8 ∙ share

read it
Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI

In this paper, we describe an open source Python toolkit named Uncertain...
06/02/2021 ∙ by Soumya Ghosh, et al. ∙ 107 ∙ share

read it
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML

Automated Machine Learning (AutoML) is a rapidly growing set of technolo...
04/09/2021 ∙ by Shweta Narkar, et al. ∙ 6 ∙ share

read it
Question-Driven Design Process for Explainable AI User Experiences

A pervasive design issue of AI systems is their explainability–how to pr...
04/08/2021 ∙ by Q Vera Liao, et al. ∙ 8 ∙ share

read it
A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms

Given that there are a variety of stakeholders involved in, and affected...
03/27/2021 ∙ by Ana Lucic, et al. ∙ 0 ∙ share

read it
Facilitating Knowledge Sharing from Domain Experts to Data Scientists for Building NLP Models

Data scientists face a steep learning curve in understanding a new domai...
01/29/2021 ∙ by Soya Park, et al. ∙ 21 ∙ share

read it
Expanding Explainability: Towards Social Transparency in AI systems

As AI-powered systems increasingly mediate consequential decision-making...
01/12/2021 ∙ by Upol Ehsan, et al. ∙ 27 ∙ share

read it
How Much Automation Does a Data Scientist Want?

Data science and machine learning (DS/ML) are at the heart of the recent...
01/07/2021 ∙ by Dakuo Wang, et al. ∙ 54 ∙ share

read it
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty

Transparency of algorithmic systems entails exposing system properties t...
11/15/2020 ∙ by Umang Bhatt, et al. ∙ 6 ∙ share

read it
Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation

We propose a new active learning (AL) framework, Active Learning++, whic...
09/06/2020 ∙ by Bhavya Ghai, et al. ∙ 12 ∙ share

read it
Measuring Social Biases of Crowd Workers using Counterfactual Queries

Social biases based on gender, race, etc. have been shown to pollute mac...
04/04/2020 ∙ by Bhavya Ghai, et al. ∙ 1 ∙ share

read it
Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience

Active Learning (AL) is a human-in-the-loop Machine Learning paradigm fa...
01/24/2020 ∙ by Bhavya Ghai, et al. ∙ 43 ∙ share

read it
Questioning the AI: Informing Design Practices for Explainable AI User Experiences

A surge of interest in explainable AI (XAI) has led to a vast collection...
01/08/2020 ∙ by Q Vera Liao, et al. ∙ 0 ∙ share

read it
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 decision...
01/07/2020 ∙ by Yunfeng Zhang, et al. ∙ 0 ∙ share

read it
Enabling Value Sensitive AI Systems through Participatory Design Fictions

Two general routes have been followed to develop artificial agents that ...
12/13/2019 ∙ by Q Vera Liao, et al. ∙ 0 ∙ share

read it
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

As artificial intelligence and machine learning algorithms make further ...
09/06/2019 ∙ by Vijay Arya, et al. ∙ 36 ∙ share

read it
Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys

The rise of increasingly more powerful chatbots offers a new way to coll...
05/25/2019 ∙ by Ziang Xiao, et al. ∙ 0 ∙ share

read it
Explaining Models: An Empirical Study of How Explanations Impact Fairness Judgment

Ensuring fairness of machine learning systems is a human-in-the-loop pro...
01/23/2019 ∙ by Jonathan Dodge, et al. ∙ 0 ∙ share

read it
Bootstrapping Conversational Agents With Weak Supervision

Many conversational agents in the market today follow a standard bot dev...
12/14/2018 ∙ by Neil Mallinar, et al. ∙ 0 ∙ share

read it
A Measure for Dialog Complexity and its Application in Streamlining Service Operations

Dialog is a natural modality for interaction between customers and busin...
08/04/2017 ∙ by Q Vera Liao, et al. ∙ 0 ∙ share

read it