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The Challenge of Crafting Intelligible Intelligence

The Challenge of Crafting Intelligible Intelligence

9 March 2018
Daniel S. Weld
Gagan Bansal
ArXivPDFHTML

Papers citing "The Challenge of Crafting Intelligible Intelligence"

20 / 20 papers shown
Title
What Do People Want to Know About Artificial Intelligence (AI)? The Importance of Answering End-User Questions to Explain Autonomous Vehicle (AV) Decisions
What Do People Want to Know About Artificial Intelligence (AI)? The Importance of Answering End-User Questions to Explain Autonomous Vehicle (AV) Decisions
Somayeh Molaei
Lionel P. Robert
Nikola Banovic
26
0
0
09 May 2025
The explanation dialogues: an expert focus study to understand requirements towards explanations within the GDPR
The explanation dialogues: an expert focus study to understand requirements towards explanations within the GDPR
Laura State
Alejandra Bringas Colmenarejo
Andrea Beretta
Salvatore Ruggieri
Franco Turini
Stephanie Law
AILaw
ELM
43
0
0
10 Jan 2025
BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with
  Neurosymbolic Programming
BANSAI: Towards Bridging the AI Adoption Gap in Industrial Robotics with Neurosymbolic Programming
Benjamin Alt
Julia Dvorak
Darko Katic
Rainer Jäkel
Michael Beetz
Gisela Lanza
23
2
0
21 Apr 2024
InterroLang: Exploring NLP Models and Datasets through Dialogue-based
  Explanations
InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations
Nils Feldhus
Qianli Wang
Tatiana Anikina
Sahil Chopra
Cennet Oguz
Sebastian Möller
32
9
0
09 Oct 2023
A User Study on Explainable Online Reinforcement Learning for Adaptive
  Systems
A User Study on Explainable Online Reinforcement Learning for Adaptive Systems
Andreas Metzger
Jan Laufer
Felix Feit
Klaus Pohl
OffRL
OnRL
24
1
0
09 Jul 2023
Reason to explain: Interactive contrastive explanations (REASONX)
Reason to explain: Interactive contrastive explanations (REASONX)
Laura State
Salvatore Ruggieri
Franco Turini
LRM
30
1
0
29 May 2023
In Search of Verifiability: Explanations Rarely Enable Complementary
  Performance in AI-Advised Decision Making
In Search of Verifiability: Explanations Rarely Enable Complementary Performance in AI-Advised Decision Making
Raymond Fok
Daniel S. Weld
24
61
0
12 May 2023
Retrospective End-User Walkthrough: A Method for Assessing How People
  Combine Multiple AI Models in Decision-Making Systems
Retrospective End-User Walkthrough: A Method for Assessing How People Combine Multiple AI Models in Decision-Making Systems
Vagner Figuerêdo de Santana
Larissa Monteiro Da Fonseca Galeno
E. V. Brazil
A. Heching
Renato F. G. Cerqueira
14
0
0
12 May 2023
Renormalization in the neural network-quantum field theory
  correspondence
Renormalization in the neural network-quantum field theory correspondence
Harold Erbin
Vincent Lahoche
D. O. Samary
37
7
0
22 Dec 2022
Why we do need Explainable AI for Healthcare
Why we do need Explainable AI for Healthcare
Giovanni Cina
Tabea E. Rober
Rob Goedhart
Ilker Birbil
30
14
0
30 Jun 2022
Mediators: Conversational Agents Explaining NLP Model Behavior
Mediators: Conversational Agents Explaining NLP Model Behavior
Nils Feldhus
A. Ravichandran
Sebastian Möller
30
16
0
13 Jun 2022
A Computational Inflection for Scientific Discovery
A Computational Inflection for Scientific Discovery
Tom Hope
Doug Downey
Oren Etzioni
Daniel S. Weld
Eric Horvitz
AI4CE
16
32
0
04 May 2022
Explainability Is in the Mind of the Beholder: Establishing the
  Foundations of Explainable Artificial Intelligence
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence
Kacper Sokol
Peter A. Flach
36
20
0
29 Dec 2021
Trustworthy AI: From Principles to Practices
Trustworthy AI: From Principles to Practices
Bo-wen Li
Peng Qi
Bo Liu
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
119
355
0
04 Oct 2021
Nonperturbative renormalization for the neural network-QFT
  correspondence
Nonperturbative renormalization for the neural network-QFT correspondence
Harold Erbin
Vincent Lahoche
D. O. Samary
41
30
0
03 Aug 2021
On Efficiently Explaining Graph-Based Classifiers
On Efficiently Explaining Graph-Based Classifiers
Xuanxiang Huang
Yacine Izza
Alexey Ignatiev
Sasha Rubin
FAtt
24
37
0
02 Jun 2021
Right for the Right Concept: Revising Neuro-Symbolic Concepts by
  Interacting with their Explanations
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations
Wolfgang Stammer
P. Schramowski
Kristian Kersting
FAtt
14
107
0
25 Nov 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on
  Complementary Team Performance
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Gagan Bansal
Tongshuang Wu
Joyce Zhou
Raymond Fok
Besmira Nushi
Ece Kamar
Marco Tulio Ribeiro
Daniel S. Weld
33
578
0
26 Jun 2020
Crowdsourcing the Perception of Machine Teaching
Crowdsourcing the Perception of Machine Teaching
Jonggi Hong
Kyungjun Lee
June Xu
Hernisa Kacorri
HAI
LRM
25
29
0
05 Feb 2020
Questioning the AI: Informing Design Practices for Explainable AI User
  Experiences
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
Q. V. Liao
D. Gruen
Sarah Miller
52
703
0
08 Jan 2020
1