Workshop Program.

We are proud to present the list of participants to the workshop. These are divided into position papers and posters.

Workshop’s schedule

09:00 - Welcome + Introductions

09:15 - Poster Set-Up

09:20 - Poster Madness

09:35 - Panel: Conversations between people and AI

  • Human-AI Collaboration: Towards Socially-Guided Machine Learning - Vera Liao (IBM Research) pdf
  • People and AI See Things Different Implications of Mismatched Perception on HCI for AI Systems - Saleema Amershi (Microsoft Research); Ece Kamar (Microsoft Research); Emre Kiciman (Microsoft Research) pdf
  • A conversational framework for machine learning - Kevin Walker (Royal College of Art) pdf

10:20 - Morning break

10:50 - Panel: Interactive / End-User ML

  • Towards Heuristic Evaluation for Interactive Machine Learning - Eric J Corbett (Georgia Institute of Technology) pdf
  • Two Case Studies of Experience Prototyping Machine Learning Systems in the Wild - Qian Yang (Carnegie Mellon University) pdf
  • Enabling Customer-Driven Learning and Customization Processes for ML-Based Domestic Robots - Fabrice Matulic; Yuta Kikuchi; Jason Naradowsky (Preferred Networks) pdf
  • Design Challenges of Machine Learning from User Interaction in Multi-Model Visual Analytics - John Wenskovitch (Virginia Tech); Chris North (Virginia Tech) pdf

11:50 - Lunch break

13:00 - Panel: Explainable AI

  • Towards Explainable Artificial Intelligence: Structuring the Processes of Explanations - Mennatallah El-Assady; Wolfgang Jentner; Rebecca  Kehlbeck; Udo Schlegel; Rita Sevastjanova; Fabian Sperrle; Thilo Spinner; Daniel Keim (University of Konstanz) pdf
  • On Design and Evaluation of Human-centered Explainable AI systems - Upol Ehsan (Georgia Institute of Technology); Mark Riedl (Georgia Institute of Technology) pdf
  • The Deciders: Envisioning A Future of Pervasive AI - Justin Weisz (IBM Research AI); Maryam Ashoori (IBM Research AI) pdf

13:45 - Panel: Open Challenges and Lessons for HCML

  • Design as a Pillar of Human-Centered Machine Learning - Jodi Forlizzi (Carnegie Mellon University) pdf
  • Supporting Feature Engineering in End-User Machine Learning - Louis McCallum (Goldsmiths); Rebecca Fiebrink (Goldsmiths University of London) pdf
  • Religion for Machines: Introducing Humanism and Dataism as Perspectives to Guide the Design and Evaluation of Machine Learning Systems - Mehmet Aydın Baytaş (Koç University) pdf
  • It Takes a Village to Raise an AI - Claudio Pinhanez (IBM Research, Brazil) pdf

14:45 - Group Activity

15:30 - Afternoon break

16:00 - Group Activity Debrief + Town Hall

17:00 - Workshop Concludes

Workshop Posters

An Interaction Framework for Studying Co-Creative AI - Matthew J Guzdial (Georgia Tech); Mark Riedl (Georgia Institute of Technology) pdf

Challenges for ML-based Emotion Recognition Systems in Medicine. A Human-Centered Approach - Oana Balan (University POLITEHNICA of Bucharest, Faculty of Automatic Control and Computers) pdf

Teaching Chatbots to Show Science: A Study with Museum Guides - Heloisa Candello (IBM Research); Mauro Pichiliani (IBM Research); Claudio Pinhanez (IBM Research); Paulo R Cavalin (IBM-Research, Brazil) pdf

Interactive Exploration of Large Decision Tree Ensembles - Jan Forberg (Technische Universität Dresden); Annett Mitschick (Technische Universität Dresden); Martin Voigt (AI4BD GmbH); Raimund Dachselt (Technische Universität Dresden) pdf

Making Machine Learning Tangible for UX Designers - John Fass (MR); Emily Groves (EPFL+ECAL)

Designing for The Long Tail of Machine Learning - Martin Lindvall (Sectra AB); Jesper Molin (Sectra AB) {: .poster} pdf

Towards Humane Feedback Mechanisms in Exploratory Search - Esben Sørig, Rebecca Fiebrink (Goldsmiths, University of London); Nicolas Collignon (University of Edinburgh); Noriko Kando (National Institute of Informatics Tokyo) pdf

Collaborative Systems for Ideation: Collecting visual Inspiration with AI’s - Janin Koch (Aalto University) pdf

PreCall: A Visual Interface for Threshold Optimization in ML Model Selection - Christoph Kinkeldey (Freie Universität Berlin); Claudia Müller-Birn (Freie Universität Berlin); Tom Gülenman (Freie Universität Berlin); Jesse Josua Benjamin (Freie Universität Berlin); Aaron Halfaker (Wikimedia Foundation) pdf

Unfairness towards subjective opinions in Machine Learning - Agathe Balayn (TU Delft, IBM CAS); Alessandro  Bozzon (Delft University of Technology); Zoltán Szlávik (IBM Center for Advanced Studies) pdf

Feedback Channels & the Effect of Human Learning in Interactive Machine Learning - Michael Zbyszynski (Goldsmiths University of London); Balandino Di Donato (Goldsmiths University of London); Atau Tanaka (Goldsmiths University of London) pdf

Why should we teach machines to read charts made for humans? - Jorge H  Piazentin Ono (NYU) pdf

(Machine) Learning through making and using. Building sensitivity by negotiating agency. - Agnieszka Billewicz (Malmo University) pdf

Disseminating Machine Learning to Domain Experts: Understanding Challenges and Opportunities in Supporting a Model Building Process - Ray Hong (New York University); Jorge H  Piazentin Ono (NYU); Juliana  Freire  (New York University); Enrico Bertini (New York University, NY, USA) pdf