March 7, 2022

Longitudinal Social Impacts of HRI

over Long-Term Deployments

Workshop Objective

This workshop seeks to grow the study of how real-world, deployed robot systems impact the people who interact with them and the social structure of the places that they inhabit. As the world sees robots begin to inhabit places designed for people - delivery robots on city streets, and robots with jobs in airports, shopping malls, and in the home - we expect the importance of understanding these impacts to grow. By bringing together researchers interested in longitudinal studies on real-world human-interactive long-term deployments, we hope to arrive at a clearer vision of how best to study these systems.

Workshop Audience

We invite technical and/or social science researchers whose work incorporates longitudinal studies, real-world deployments, long-term deployments, ethics and social impacts, and general human-robot interaction for a day of talks and discussions regarding objectives, metrics, hypotheses, and best practices.

Workshop Details

The event will contain multiple virtual sessions including invited talks, oral paper presentations, poster presentations, and panel discussions. After the day’s presentations, there will be hosted breakout discussions intended to aid in the formation of collaborations and the synthesis of ideas. In the evening there will be a virtual social event to form and deepen connections amongst this research community.

Invited Speakers

Reid Simmons

Carnegie Mellon University

Maja Mataric

University of Southern California

Stefanie Tellex

Brown University

Selma Sabanovic

Indiana University

Invited Talks

Stefanie Tellex

Towards Complex Language in Partially Observed Environments

[9:00 - 9:45]

Abstract: Robots can act as a force multiplier for people, whether a robot assisting an astronaut with a repair on the International Space station, a UAV taking flight over our cities, or an autonomous vehicle driving through our streets. Existing approaches use action-based representations that do not capture the goal-based meaning of a language expression and do not generalize to partially observed environments. The aim of my research program is to create autonomous robots that can understand complex goal-based commands and execute those commands in partially observed, dynamic environments. I will describe demonstrations of object-search in a POMDP setting with information about object locations provided by language, and mapping between English and Linear Temporal Logic, enabling a robot to understand complex natural language commands in city-scale environments. These advances represent steps towards robots that interpret complex natural language commands in partially observed environments using a decision theoretic framework.

Bio: Stefanie Tellex is an Associate Professor of Computer Science at Brown University. Her group, the Humans To Robots Lab, creates robots that seamlessly collaborate with people to meet their needs using language, gesture, and probabilistic inference, aiming to empower every person with a collaborative robot. She completed her Ph.D. at the MIT Media Lab in 2010, where she developed models for the meanings of spatial prepositions and motion verbs. Her postdoctoral work at MIT CSAIL focused on creating robots that understand natural language. She has published at SIGIR, HRI, RSS, AAAI, IROS, ICAPs and ICMI, winning Best Student Paper at SIGIR and ICMI, Best Paper at RSS, and an award from the CCC Blue Sky Ideas Initiative. Her awards include being named one of IEEE Spectrum's AI's 10 to Watch in 2013, the Richard B. Salomon Faculty Research Award at Brown University, a DARPA Young Faculty Award in 2015, a NASA Early Career Award in 2016, a 2016 Sloan Research Fellowship, and an NSF Career Award in 2017. Her work has been featured in the press on National Public Radio, BBC, MIT Technology Review, Wired and Wired UK, as well as the New Yorker. She was named one of Wired UK's Women Who Changed Science In 2015 and listed as one of MIT Technology Review's Ten Breakthrough Technologies in 2016.


Reid Simmons

Experiences with Character-Based Robots

[9:50 - 10:35]

Abstract: Over the past nearly 20 years, we have had two character-based robots deployed at Carnegie Mellon, developed in conjunction with the CMU Drama School. The robots, a robot receptionist and Scrabble-playing robot, have interacted with thousands of people, including students, faculty, staff, and visitors. A copy of the receptionist robot was also deployed for several years at the CMU campus in Qatar. The observations and analyses that we have done during this time provide valuable insights into the way people interact with such robots "in the wild", including based on cultural differences. This talk will present the robots that were developed, some of our key findings, and lessons learned.

Bio: Reid Simmons is a Research Professor in Robotics and Computer Science at Carnegie Mellon University. He is also the director of the first-in-the-country undergraduate major in Artificial Intelligence. Dr. Simmons earned his PhD from MIT in 1988 in the field of Artificial Intelligence. Since coming to CMU in 1988, he has focused on developing self-reliant robots that can autonomously operate over extended periods of time in unknown, unstructured environments. Specific research interests include human-robot social interaction, especially non-verbal communication through affect, proxemics, motion, and gesture, task planning under uncertainty, execution monitoring and failure recovery, and coordination of multiple heterogeneous robots.

Over the years, Dr. Simmons has been involved in the development of nearly two dozen autonomous robots. He has published over 200 papers and articles on autonomous robots, human-robot interaction, multi-robot coordination, robot architectures, planning, and probabilistic reasoning. He is an Associate Editor of the Journal of Artificial Intelligence and is on the Editorial Board of International Journal of Social Robots. Dr. Simmons is a Fulbright Scholar (Israel), a Fellow of the Association for the Advancement of Artificial Intelligence, and served as an NSF Program Officer, overseeing the National Robotics Initiative and the Smart and Autonomous Systems program.

Maja Mataric

From Single Sessions to Six-Month Deployments: Lessons from 18 Years of HRI and SAR In the Wild

[12:00 - 12:45]

Abstract: Socially assistive robotics (SAR) emerged in the early 2000s as an area of HRI specifically focused on systems capable of measurably assisting people in the contexts of health (therapy, rehabilitation) and learning/training. Proper SAR system evaluation requires deployments in settings where users can engage in realistic activities and interactions. Simulating SAR users—stroke patients, individuals on the autism spectrum, elderly with Alzheimer’s Disease, etc.—is not a productive endeavor. Therefore, SAR researchers are challenged to get their algorithms, systems, and methods out into real-world settings in order to gain meaningful insights. This talk will review 18 years of our SAR research that has involved multi-modal interaction and expressive and persuasive robot behavior for monitoring, coaching, and motivating users to engage in health, wellness, education and training activities, starting in single-session studies in controlled settings and growing into multi-week interactions in schools, month-long and longer deployments in homes, and a 6-month deployment in a memory care center/nursing home. Beyond HRI contributions to a broad spectrum of topics (user modeling, engagement, personality, motivation, adherence, long-term adaptation), such deployments generate key insights about the real challenges of robotics in the wild. The talk will discuss a range of studies and long-term deployments, settings (schools, hospitals, homes), users (children, adults, typically developing, autism, stroke, Alzheimer’s disease), and commercial implications.

Bio: Maja Matarić is Chan Soon-Shiong Distinguished Professor of Computer Science, Neuroscience, and Pediatrics at USC, founding director of the Robotics and Autonomous Systems Center and her Interaction Lab. Her past administrative roles include serving as Interim Vice President of Research (2020-21) and Vice Dean of Research in the Viterbi School of Engineering (2006-2019), and she leads the Viterbi K-12 STEM Center. Her PhD and MS are from MIT, and BS from Kansas University. She is Fellow of AAAS, IEEE, AAAI, and ACM, recipient of the Presidential Award for Excellence in Science, Mathematics & Engineering Mentoring (from President Obama), Anita Borg Institute Women of Vision for Innovation, NSF Career, MIT TR35 Innovation, and IEEE RAS Early Career Awards. She is recognized for her K-12 STEM outreach efforts and for mentoring of women and other underrepresented groups in STEM. She authored "The Robotics Primer”, MIT Press. Her research is developing socially assistive robots for convalescence, rehabilitation, training, and education for children with autism spectrum disorders, stroke and traumatic brain injury survivors, and individuals with Alzheimer's Disease, as well as individuals suffering from anxiety and depression. She is also co-founder of Embodied, Inc.

Selma Sabanovic

Before and After: Building long-term research relationships for HRI studies

[12:50 - 13:35]

Paper Topics

Contributions are invited on all topics relevant to longitudinal social impacts of HRI over long-term deployments and topics that can help to inform this core idea, including (but not limited to):

  • Longitudinal studies of HRI over real-world large-scale deployments

  • Interdisciplinary approaches and long-term autonomy

  • Methodological and technical challenges for longitudinal studies

  • Social impacts of HRI over long-term deployments

  • Social effects such as safety, privacy, and inclusion

  • New opportunities for HRI and HR teaming

  • Demonstrations of long-term deployments

  • Hardware and devices for human-robot interaction

  • New sensors, biological signals for longitudinal HRI

Social Science and Technical Review Tracks

While the event itself will be single track, all submissions will select at least one review track for their paper: either social science or technical. These tracks are to ensure the relevance of reviews, and submissions which are a blend of each are welcome. Each corresponding author will be asked to briefly review up to two other submissions per submitted papers, and to select at least one review track for which they’d be comfortable reviewing. Author reviews will be coordinated by a workshop program committee, which will request additional reviews as needed and generally ensure the formation of a compelling workshop program.

To Choose Your Track

  1. Submit the paper

  2. EasyChair will assign it an ID #

  3. Email Justin Hart ( the ID # and the track for your paper.

Submission types

Submission types for this workshop include:

  • short work-in-progress and position papers (2-4 pages)

  • long-format integration and experimental papers (4-6 pages).

All papers are to be considered for both oral presentations and posters, with final format to be indicated along with acceptance.

Reviewing will be single-blind. You do not need to anonymize your paper.

To encourage participation, 1-2 page extended abstracts describing the research interests of participants will also be accepted and featured on the workshop's website.

Early Submission: January 17, 2022

Early Decisions: February 7, 2022

Late Submission: February 14, 2022

Late Decisions: March 1, 2022


Justin Hart -

Elliot Hauser -

Samuel Baker -

Joydeep Biswas -

Junfeng Jiao -

Luis Sentis -