The COoKIE Group
Communication, Organization of Knowledge, Information Ecosystems
What we Do
The COoKIE is an interdisciplinary Human-Computer Interaction research group focusing on Human-AI communication and collaboration.
Our recent work touches on diverse technologies, including conversational agents, large language models, generative AI systems, and AI-based decision support systems. Seeking to advance Human-AI interaction design, we explore mechanisms driving the perceptions of different types of AI systems, such as trust, anthropomorphization, or perceived reliability to inform the system and algorithm design requirements for effective, efficient, and ethical AI.
Our Work is Supported by:
The Natural Sciences and Engineering Research Council of Canada (NSERC)
The Social Sciences and Humanities Research Council of Canada (SSHRC)
The Naver Corporation,
South Korea
The Faculty of Information,
University of Toronto, Canada
Data Sciences Institute,
University of Toronto, Canada
Current Research Areas
Human-Agent Communication
The growing complexity of intelligent systems creates a promising environment for the shift in a user experience paradigm: from pure human-system interaction to human-system communication and collaboration. This is further amplified by the increased popularity of entity-based system interfaces (artificial agents) and the integration of conversational user interfaces (CUI). The human-agent communication paradigm opens exciting opportunities to exploit a computer's unique abilities to complement humans. However, first, we need to understand the specifics of human-agent communication.
AI-Based Decision Support Systems (ADS)
AI-integrated decision-making support systems allow to augment and extend human capabilities, improving the quality and efficiency of decisions. These systems use AI to learn, remember, analyze, and reason based on large amounts of often complex data. The successful use of these features requires an understanding of how they can appropriately complement human processes. To address these questions, we explore what aspects of augmentation are required in different scenarios, how the outcomes should be communicated and explained (xAI), and how to properly calibrate and, if needed, repair trust in systems' performance.
Information Architecture for Conversational UI
The intuitive nature of Conversational User Interfaces (CUI), fashioned after natural human conversation, allows for convenient and fast input and can serve as a single-channel input for multiple services, devices, applications, and even environments. However, due to the absence of visual clues, affordances, and spatial organization, the use of CUI is associated with a decreased sense of control over the information dynamics. We explore the perceived “locations”, “structure“, and “paths” of the information shared through CUI, to inform the required information architecture.
Meet the Team
Anastasia Kuzminykh
Assistant Professor,
Faculty of Information, UofT
Director of The COoKIE Group and the Toronto Human-AI Interaction Research School (THAI RS)
Anshuta Kulkarni
Master's Thesis Student,
Faculty of Information, UofT
Social Dynamics in Human-Agent Interaction
Paula Aoyagui
Research Assistant, Previously Master's Student, Faculty of Information, UofT
Explainable AI Strategies in Non-Ground-Truth Cases
Dakshata Shukla
Master's Read. Student,
Faculty of Information, UofT
Conversational Agents For Supporting Female Health in Global South
Christina Wei
Ph.D. Student, THAI RS'22,
Faculty of Information, UofT
Conversation Architecture for Artificial Agents
Fatima Zohra
Master's Thesis Student,
Faculty of Information, UofT
Accuracy Preserving Fairness Techniques for Financial Models
Shradha Anand
Master's Research Assistant,
Faculty of Information, UofT
Document Exploration Through Conversational Interfaces
Janna Cameron
Master's Read. Student,
Faculty of Information, UofT
Types of Trust in Human-AI Collaboration
Rezvan Boostani
Ph.D. Student,
Faculty of Information, UofT
Artificial Agents for Financial Assistants for Older Adults
Janet Lu
Master's Thesis Student,
Faculty of Information, UofT
Conversational Agents for Co-Design Assistance
Rimsha Rizvi
Master's Research Assist., Faculty of Information, UofT
Fairness and Explainability in Human-AI Collaboration
Yihui Lu
Mitacs Globalink Research Intern, 2023, Faculty of Information, UofT
Conversational Agents for Psychological Therapy
Senjuti Dutta
Ph.D. Student, Electrical Eng. & Computer Science, UTK
Intelligent Systems to Support Crowdwork Flexibility
Dr. Angeline Tsui
Research Assistant, Faculty of Information, UofT
Effects of AI Explainability on Human-AI Performance
Omer Imran
Master's Read.Student,
Faculty of Information, UofT
Bias Mitigation Techniques in ML
Yaqing Yang
Mitacs Globalink Research Intern, 2023, Faculty of Information, UofT
The Effects of Modality on The Structure of Prompts for Art Generative AI Models
Manveer Kalirai
Ph.D. Student, THAI RS'22, Faculty of Information, UofT
Information Architecture for Smart Homes
Nazar Ponochevnyi
Research Assistant,
Faculty of Information, UofT
Developing Voice Interface for Chart Creation
Amy Wang
Master's Read. Student,
Faculty of Information, UofT
Supporting Attention Flow Through Conversational Agents
Yuxin Xu
Master's Thesis Student,
Faculty of Information, UofT
Conversational Agent for Picture Book Co-Reading
Sharon Ferguson
PhD Research Assistant, THAI RS'21, Mechanical and Industrial Engineering, UofT
AI Explanations of Subjective Cases
Janna Cameron
Master's Read. Student,
Faculty of Information, UofT
Types of Trust in Human-AI Collaboration
Alumni
Nabila Chowdhury
PhD Research Assistant,
THAI RS'22, Faculty of Information, UofT
Promt-Based Bias in AI Generated Art
Deepak Surya
Mitacs Globalink Intern, 2022, Faculty of Information, UofT. Text-to-Voice Conversation Style Transformation
Ashvanth Rathinavel
Mitacs Globalink Research Intern, 2023, Faculty of Information, UofT
The Role of Modality in Human-AI Conversation
Kusum Grandhi
Mitacs Globalink Research, 2022, Faculty of Information, UofT. Modality-Dependant Decision Effects of AI Explanations
Olha Liuba
Research Intern, 2023,
Faculty of Information, UofT
Supporting Equal Participation in Group Discussions
Kelly McConvey
Ph.D. Research Assistant,
Faculty of Information, UofT
Collaboration with AI Models in Education
Marianna Kovalova
Research Intern, 2023,
Faculty of Information, UofT
The Effects of Explanation Format on The Perceived Trustworthiness
Bill Than
NSERC USRA, BI student,
Faculty of Information, UofT
Engagement in Teleconferencing Classrooms During Covid-19
M. Elkhechen
Research Assistant,
Faculty of Information, UofT
Psychological Ownership in Human-AI Collaboration
Mona Abou Swaid
Master's Research Assistant,
Faculty of Information, UofT
Sense of Ownership Over Digital Artifacts
Tanisha Amarakoon
Research Assistant,
Faculty of Information, UofT
Psychological Ownership in Human-AI Collaboration
Akriti Kaur
Master's Research Assistant,
Faculty of Information, UofT
Document Exploration Through Conversational Interfaces
Hidaya Ismail
Research Assistant,
Faculty of Information, UofT
Psychological Ownership in Human-AI Collaboration
Mujgan Ozceylan
Master's Research Assistant, Reading Student, THAI RS'21
Faculty of Information, UofT
AI Explanations of Subtle Sexism
Juan Antonio Nelson
Research Assistant,
Faculty of Information, UofT
Speech Detection of Caribbean Dialects
Past Reading/Research Course Students:
Dakshata Shukla - Master's Reading Student, Faculty of Information, UofT. Conversational Agents For Women in Global South | S2023
Janna Cameron - Master's Reading Student, Faculty of Information, UofT. Types of Trust in Human-AI Collaboration | S2023
Omer Imran - Master's Reading Student, Faculty of Information, UofT. Bias Mitigation Techniques in ML | S2023
Amy Wang- Master's Reading Student, Faculty of Information, UofT. Attention Support Through Conversational Agent | S2023
Rimsha Rizvi - Master's Reading Student, Faculty of Information, UofT. Fairness and Explainability in Human-AI Collaboration | S2023
Fatima Zohra - Master's Reading Student, Faculty of Information, UofT. Accuracy Preserving Fairness Techniques for Financial Models| S2023
Anshuta Kulkarni - Master's Reading Student, Faculty of Information, UofT. Social Dynamics in Human-Agent Interaction | S2023
Janet Lu - Master's Reading Student, Faculty of Information, UofT. Conversational Agents for Co-Design Assistance | S2023
Kshitij Anand - Master's Reading Student, Faculty of Information, UofT. Conversation in Human-AI Collaborative Tasks | S2023
Batool Fatima - Master's Reading Student, Faculty of Information, UofT. Trust Mechanisms in Human-AI Collaboration | S2023
Lakshya - Master's Reading Student, Faculty of Information, UofT. Designing Human-AI Conversation | S2022
Mohammed Elkhechen - Master's Reading Student, Faculty of Information, UofT. Human-AI Teams | S2022
Lakshya - Master's Reading Student, Faculty of Information, UofT. Designing Human-AI Conversation | S2022
Shradha Anand - Master's Reading Student, Faculty of Information, UofT. Exploration of Documents Through Conversational Interfaces | S2022
Jinchi Lin - Master's Reading Student, Faculty of Information, UofT. Personalization of Disembodied Intelligent Agents | S2022
Lizhen Ying - Master's Reading Student, Faculty of Information, UofT. Anthropomorphization of Disembodied Agents | W2022
Paula Akemi - Master's Reading Student, Faculty of Information, UofT. Designing Technology for Older Adults | F2021
Manveer Kalirai - Master's Reading Student, Faculty of Information, UofT. The Adoption of Smart Home Technology in Everyday Use | S2021
Julia Gil - Undergrad Reading Student, Faculty of Information, UofT. User Communication with Conversational Agents | S2021
Ruijia Yang - Undergrad Reading Student, Computer Science, UofT. Simulation As a Research Method in HCI | W2021
Join the Team
PostDocs
We would be happy to consider applications from potential postdoc candidates. Typically, a postdoc contract is offered for a year with a potential consequent extension for another year. Currently, we are looking for postdoc candidates, broadly interested in Human-AI Collaboration with a particular focus on conversational interactions. If you are interested in a postdoc in our group, please send your CV, writing samples, and a brief statement of research interest to Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca).
Ph.D. Program
We invite applications from candidates with a Master's degree in Computer Science, Systems Design Engineering, Data Science, Psychology, Communication Studies, or similar fields. Research experience is expected, academic publications are a plus. The application period is typically open September-November, with entry into the program once a year, in September. Please review the admission requirements to the Ph.D. in Information. It is highly recommended to contact your potential supervisor and have a discussion about your research plans and interests. If you are interested in a Ph.D. in our group, please send your CV, writing samples, and a brief statement of research interest to Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca).
Master's Thesis
The Master's Thesis option at the COoKIE group is available to students, enrolled in the Master's of Information program at the iSchool, University of Toronto. Please review the pre-requisites and eligibility for the master's thesis. To inquire about the reading course and/or the thesis work at the COoKIE Group, please send your CV and a brief statement of research interest to Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca). If applicable, please mention any relevant experience, including prior research experience and/or reading courses taken in the past.
RAship
In most of the academic terms (September-December, January-April, May-August), the COoKIE Group has 1-2 Research Assistantship positions available for Master's or undergraduate level students. While typically we hire students from the University of Toronto, external applications can occasionally be considered. The standard RA contract in our group includes 12 weeks, 5-6 hours per week, working on an individual or a group project. To inquire about open positions and to apply for RAship, please contact Prof. Anastasia Kuzminykh (anastasia.kuzminykh@utoronto.ca) no later than a week before the beginning of an academic term. Please include your CV and a brief statement of research interest.
