IBM Research @ CHI 2021     


IBM Research @ CHI 2021 - overview

By Vera Liao, Research Staff Member

The ACM CHI Conference on Human Factors in Computing Systems is the premier venue for publishing research work in human-computer interaction (HCI). This post highlights a strong body of works from IBM Research that will be presented at CHI 2021, held virtually on May 8-13 2021.  They span the topics of democratizing and augmenting AI development, explainable AI, AI for marginalized groups, and human-agent communication, including 6 full papers, 2 co-organized workshops, 2 courses, 1 Special Interest Groups (SIG) meeting, and 5 workshop papers. Among them, one paper received the prestigious CHI Best Paper Honorable Mention Award [4]. We are also proud to have a long-time IBMer, John T. Richards, receiving SIGCHI Lifetime Practice Award [20], one of the highest awards in the HCI community. This year the CHI conference keynote [21] will be given by Chieko Asakawa, an IBM Fellow and IBM Distinguished Service Professor at Carnegie Mellon University.

Also check out career opportunites at IBM Research and ways to connect for future opportunities at the end of this post!


Democratizing and Augmenting AI Development

IBM Research is actively working on new technologies to make developing Machine Learning (ML) models more effective, efficient, and accessible to all.  

IBM AutoAI speeds up the process and allows citizen data scientists to get started by automating multiple steps in model development. To ensure human control and a satisfying user experience with AutoAI, HCI researchers at IBM pursue a human-centered approach to designing and evaluating AutoAI. This paper [1]  found that AutoAI system enabled data scientists to build models three time faster than by hand with higher accuracy, and discusses design implications for enhancing user trust in AutoAI systems.

Ground-truth labeling is a critical step in ML development. As one of the first studies examining how domain experts work on data labeling, this paper [2] provides a detailed account of domain experts' labeling practices, experience of labeling, collaborative activities, and quality issues, highlighting the needs to better support the human and social aspects in data labeling work. 

In another paper [3], focusing on the simultaneous use of code and documentation by machines, IBM researchers demonstrate the use of informal knowledge from curators of conversational AI systems, embedded as symbolic meta-knowledge in the documentation, to improve the performance of typical text classification ML algorithms, enhanced by a new neuro-symbolic approach.


Explainable AI

Explainability and transparency of AI systems is the foundation for users to better understand the systems to form appropriate trust and interact effectively. HCI researchers at IBM advocate for human-centered perspectives in advancing explainable AI (XAI) by developing novel concepts, explanation mechanisms and design methods for XAI.

In a paper that received a Best Paper Honorable Mention Award [4], IBM researchers highlight that people's understanding of AI is socially situated and consequential AI systems are often embedded in specific socio-organizational contexts, and propose to expand the conceptual and design space of XAI by making visible the social contexts. To do so, they proposed and evaluated a design framework that presents past users' interactions with AI systems and their reasoning around the interactions to enable a holistic explainability.

IBM researchers are also co-organizing and participating in CHI Workshop on Operationalizing Human-Centered Explainable AI [7], where they will discuss how to operationalize discussions about XAI opportunities among designers and developers of AI and its end-users [10], and a multi-stakeholder approach for evaluating AI transparency [11].


AI for Marginalized Groups

HCI researchers at IBM Research have a long history of developing inclusive and accessible technologies for marginalized user groups. In this paper [5], accessibility researchers developed an assistive system LineChaser to help blind users navigate waiting lines in public spaces, using smartphone camera to detect nearby pedestrians and sensors to estimate the position. 

IBM Researchers are also co-organizing a "Queer in HCI" Special Interest Groups (SIG) meeting [9], and participating in the Workshop on Artificially Intelligent Technology for the Margins, to share work with IBM Design to re-center design on marginalized populations and their needs [12], and exploration of using AI technology to support small business owners' financial practices in underrepresented communities [13]. Two other researchers will be sharing their work at the Workshop on Designing Interactions for the Ageing Populations on helping the elderly combat computer anxiety as they transition to mobile technologies [15].

We are also very proud to have Chieko Asakawa, IBM Fellow, delivering a CHI Keynote on her foundational work in accessibility research supporting people with visual impairments, titled See What I Mean: Making Waves with the Blind [21].


Human-Agent Communication

IBM Researchers also study communication design of AI agents. The Workshop on Putting Conversational User Interface Design into Practice is co-organized by two IBMers who work on the design and user experience of conversational agents.

In another paper [6], IBM researchers created a human-agent cooperative word guessing game and studied how communication directionality--whether humans have to interpret AI's actions or vice versa--affect people's social perception of the agent. Based on the findings, they make design recommendations for human-AI collaborative technologies.

See below for the full list of works from IBM Research. You can find the schedule in the conference program. See you at virtual CHI 2021!





1. Dakuo Wang, Josh Andres, Justin Weisz, Erick Oduor, and Casey Dugan. AutoDS: Towards Human-Centered Automation of Data Science
2. Claudio S. Pinhanez, Heloisa C. Candello, Paulo Cavalin, Mauro C. Pichiliani, Ana P. Appel, Victor HA Ribeiro, Julio Nogima, Henrique Ferreira Dos Santos, Gabriel Louzada Malfatti. Integrating Machine Learning Data with Symbolic Knowledge from Collaboration Practices of Curators to Improve Conversational Systems
3. Michael Muller, Christine Wolf, Josh Andres, Michael Desmond, Narendra Nath Joshi, Zahra Ashktorab, Aabhas Sharma. Narendra Nath Joshi, Josh Andres, Qian Pan, Christine Wolf, Michael Desmond , Krissy Brimijoin. Designing Ground Truth and the Social Life of Labels
4. Upol Ehsan, Q. Vera Liao, Michael Muller, Mark Riedl, Justin Weisz. Expanding Explainability: Towards Social Transparency in AI systems  (Best Paper Honorable Mention Award)
5. Masaki Kuribayashi, Seita Kayukawa, Hironobu Takagi, Chieko Asakawa, and Shigeo Morishima. LineChaser: A Smartphone-Based Navigation System for Blind People to Stand in Lines
6. Zahra Ashktorab, Casey Dugan, James Johnson, Qian Pan, Wei Zhang, Sadhana Kumaravel, and Murray Campbell. Effects of Communication Directionality and AI Agent Differences in Human-AI Interaction



Special Interest Groups (SIG) meeting

9. Michael Muller. Queer in HCI: Strengthening the Community of LGBTQIA+ Researchers and Research

Workshop papers

10. Juliana Jansen Ferreira, Mateus De Souza Monteiro. Designer-User Communication for XAI: An epistemological approach to discuss XAI design. Workshop on Operationalizing Human-Centered Perspectives in Explainable AI
11. Q. Vera Liao. A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms. Workshop on Operationalizing Human-Centered Perspectives in Explainable AI
12. Andrea M. Barbarin ,Allison Biesboer, Claudia Matteo, Michael Muller, Rob Pierce, Joelle Williams. Bringing the Margins toward the Center: IBM Design’s Call to Action for Racial Equity. Workshop on Artificially Intelligent Technology for the Margins
13. Heloisa Candello, Andrea Britto Mattos, Q. Vera Liao, Claudio Pinhanez, Rogerio de Paula, Marcelo Carpinete Grave. Microbanking: Bringing Credit to low-wage communities by Enhancing Informal Financial Practices with AI. Workshop on Artificially Intelligent Technology for the Margins
15. Thiago Donizetti Dos Santos, Vagner Figueredo De Santana. Computer Anxiety: Supporting the Transition from Desktop to Mobile. Workshop on Designing Interactions for the Ageing Populations – Addressing Global Challenges

Late-Breaking Work Paper

16. April Yi Wang, Dakuo Wang, Jaimie Drozdal, Xuye Liu, Soya Park, Steve Oney, Christopher Brooks. What Makes a Well Documented Notebook? A Case Study of Data Scientists’ Documentation Practices in Kaggle Notebooks


17. Vera Liao, Moninder Singh, Yunfeng Zhang,Rachel Bellamy. Introduction to AI Explainability
18. Yunfeng Zhang, Rachel Bellamy, Moninder Singh,Vera Liao. Introduction to AI Fairness


19. Dakuo Wang,Pattie Maes,Xiangshi Ren,Ben Shneiderman,Yuanchun Shi,Qianying Wang. Designing AI to Work WITH or FOR People?

Award Talk

20. John Richards. SIGCHI Lifetime Practice Award Talk: Usability Barriers and How to Overcome Them

CHI Keynote


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