IAW 2019
Interpretable AI for Well-being: Understanding Cognitive Bias and Social Embeddedness

Table of Contents

Session 1: Overview

• The Challenges for Interpretable AI for Well-being (opening talk)
  Takashi Kido , Keiki Takadama
• What Makes It Difficult To Apply AI Into Well-being and Its Solution: An Example of Sleep Apnea Syndrome (text not included)
  Keiki Takadama

Session 2: Explainable AI

• Treat Everyone Fairly: A Model of Unbiased and Explainable Algorithmic Decision Making (text not included)
  Amy Ding
• Diagnostic Model Explanations: A Medical Narrative
  Umang Bhatt , Brian Davis , Jose M.F. Moura

Session 3: Interpretable AI

• Open Affect-Responsive Systems: Toward Personalized AI to Beat Back the Waves of Technostress
  David Agogo , Leona Chandra Kruse
• A Study of Basis on AI-based Information Systems: The Case of Shogi AI System "Ponanza"
  Yuichi Yoda , Kosuke Mizokushi , Seiichiro Honjo
• TGIF!: Selecting the most healing TNT by optical flow
  Changeun Yang , Pujana Paliyawan , Ruck Thawonmas , Tomohiro Harada
• Framework for interaction between expert users and Machine Learning Systems
  Saveli Goldberg , Boris Galitsky , Ben Weisburd
• Interpretable AI as Curation
  Akinori Abe

Session 4: Well-being AI

• Fall Risk Detection for the Elderly using Contactless Sensors
  Takeshi Konno , Hiroaki Kingetsu , Daisuke Fukuda , Toshihiro Sonoda
• Toward Good Circadian Rhythm through an valuate of Stress Condition
  Ryo Takano , Sho Kajihara , Satoshi Hasegawa , Eiki Kitajima , Keiki Takadama , Toru Shimuta , Toru Yabe , Hideo Matsumoto
• WAKE Detection During Sleep using Random Forest for Apnea Syndrome Patients
  Iko Nakari , Yusuke Tajima , Akari Tobaru , Keiki Takadama
• Sleep Stage Estimation using Heart Rate Variability divided by Sleep Cycle with Relative Evaluation
  Akari Tobaru , Yusuke Tajima , Keiki Takadama
• Measuring Functional Independence of an Aged Person with a Combination of Machine Learning and Logical Reasoning
  Nobuyuki Oishi , Masayuki Numao

Session 5: Social Embeddedness

• Are Robot Tax, Basic Income or Basic Property Solutions to the Social Problems of Automation?
  Oliver Bendel
• Context-based Network Analysis of Structured Knowledge for Data Utilization
  Teruaki Hayashi , Yukio Ohsawa
• Extended Mind, Embedded AI, and "the Barrier of Meaning"
  Sadeq Rahimi
• Concept of Future Prototyping Methodology to Enhance Value Creation within Future Contexts
  Miwa Nishinaka , Yusuke Kishita , Hisashi Masuda , Kunio Shirahada
• Maintaining Knowledge Distribution System's Sustainability Using Common Value Auctions
  Anas Al-Tirawi , Robert G. Reynolds

Session 6: Cognitive Bias

• Estimating the Political Orientation of Twitter Users in Homophilic Networks
  Morteza Shahrezaye , Orestis Papakyriakopoulos , Juan Carlos Medina Serrano , Simon Hegelich
• A Cross-lingual Analysis on Culinary Perceptions to Understand the Cross-cultural Difference
  Xuehui Leng , Masanao Ochi , Takeshi Sakaki , Junichiro Mori , Ichiro Sakata
• Evaluating Cognitive Bias in Two-Party and Multi-Party Spoken Interactions
  Christina Alexandris

Session 7: Invited Talks

• What is Causal Inference? (text not included)
  Judea Pearl
• DeepVariant: Deep Learning for Genomic Variant Calling (text not included)
  Sidharth Goel
• Identifying and exploiting influential training examples (text not included)
  Pang Wei Koh
• Interpretable AI for Well-Being Using Mobile Health
  Peter Pirolli
• Suggested Best Practices for Interpreting Deep Learning Models via Input-Level Importance Scores (text not included)
  Avanti Shrikumar

Session 8: Poster and Demonstration

• What Makes a Good Diagnosis: An Algorithm to Detect Biased Training Data (text not included)
  Madeleine Schneider , Robert Thomsons
• Future Prototyping Methodology: What is a well-being for the Future Society and how AI handles "appropriateness (text not included)
  Miwa Nishinaka
• Sleep Stage Estimation Through Mattress Sensor (text not included)
  Ryo Takano , Akari Tobaru , Iko Nakari , Keiki Takadama