More Web Proxy on the site http://driver.im/

research-article

Public Access

Laila is in a Meeting: Design and Evaluation of a Contextual Auto-Response Messaging Agent

Authors:

Adam J. LeeAuthors Info & Claims

DIS '22: Proceedings of the 2022 ACM Designing Interactive Systems Conference

Pages 1457 - 1471

https://doi.org/10.1145/3532106.3533493

Published: 13 June 2022 Publication History

All formats PDF

Abstract

The ease of smartphone communications has created an expectation of constant connectivity. While the adoption of virtual assistants has improved, their capabilities for handling proactive communication tasks remain underexplored. We present the design, implementation, and evaluation of a Contextual Auto-Response agent to communicate users’ situational awareness. The agent creates auto-responses by modeling availability using smartphone sensors and sharing contextual information on behalf of the user. In a two-week study with 12 participants, we evaluated the perception of this agent and its impact on device usage behavior. Many participants found the agent useful for signaling unavailability, with some caveats. Participants also reported altering device and agent usage based on their understanding of its functions. Our findings indicate the importance of transparency in proactive agent designs and the need for personalization to enable an enhanced and cooperative human-agent interaction.

References

[1]

Ashraf Abdul, Jo Vermeulen, Danding Wang, Brian Y. Lim, and Mohan Kankanhalli. 2018. Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–18. https://doi.org/10.1145/3173574.3174156

Digital Library

[2]

Daniel Avrahami and Scott E. Hudson. 2006. Responsiveness in Instant Messaging: Predictive Models Supporting Inter-Personal Communication. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Montréal, Québec, Canada) (CHI ’06). Association for Computing Machinery, New York, NY, USA, 731–740. https://doi.org/10.1145/1124772.1124881

Digital Library

[3]

Brian P Bailey, Joseph A Konstan, and John V Carlis. 2001. The Effects of Interruptions on Task Performance, Annoyance, and Anxiety in the User Interface. In Human-Computer Interaction: IFIP TC13 International Conference on Human-Computer Interaction, July 9-13 (Tokyo, Japan) (INTERACT ’01). IOS Press, 593–601. https://doi.org/10.1145/3025453.3025946

Digital Library

[4]

João Balsa, Isa Félix, Ana Paula Cláudio, Maria Beatriz Carmo, Isabel Costa e Silva, Ana Guerreiro, Maria Guedes, Adriana Henriques, and Mara Pereira Guerreiro. 2020. Usability of an intelligent virtual assistant for promoting behavior change and self-care in older people with type 2 diabetes. Journal of Medical Systems 44, 7 (2020), 1–12.

Digital Library

[5]

Linas Baltrunas, Karen Church, Alexandros Karatzoglou, and Nuria Oliver. 2015. Frappe: Understanding the Usage and Perception of Mobile App Recommendations In-The-Wild. https://doi.org/10.48550/ARXIV.1505.03014

[6]

James ”Bo” Begole, Nicholas E. Matsakis, and John C. Tang. 2004. Lilsys: Sensing Unavailability. In Proceedings of the 2004 ACM Conference on Computer Supported Cooperative Work (Chicago, Illinois, USA) (CSCW ’04). Association for Computing Machinery, New York, NY, USA, 511–514. https://doi.org/10.1145/1031607.1031691

Digital Library

[7]

V. Braun and V. Clarke. 2013. Successful Qualitative Research: A Practical Guide for Beginners. SAGE Publications. https://books.google.com/books?id=nYMQAgAAQBAJ

[8]

Andreas Buchenscheit, Bastian Könings, Andreas Neubert, Florian Schaub, Matthias Schneider, and Frank Kargl. 2014. Privacy Implications of Presence Sharing in Mobile Messaging Applications. In Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia (Melbourne, Victoria, Australia) (MUM ’14). Association for Computing Machinery, New York, NY, USA, 20–29. https://doi.org/10.1145/2677972.2677980

Digital Library

[9]

Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A Scalable Tree Boosting System. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (San Francisco, California, USA) (KDD ’16). Association for Computing Machinery, New York, NY, USA, 785–794. https://doi.org/10.1145/2939672.2939785

Digital Library

[10]

Hyunsung Cho, Jinyoung Oh, Juho Kim, and Sung-Ju Lee. 2020. I Share, You Care: Private Status Sharing and Sender-Controlled Notifications in Mobile Instant Messaging. Proc. ACM Hum.-Comput. Interact. 4, CSCW1, Article 34 (may 2020), 25 pages. https://doi.org/10.1145/3392839

Digital Library

[11]

Karen Church and Rodrigo de Oliveira. 2013. What’s up with Whatsapp? Comparing Mobile Instant Messaging Behaviors with Traditional SMS. In Proceedings of the 15th International Conference on Human-Computer Interaction with Mobile Devices and Services (Munich, Germany) (MobileHCI ’13). Association for Computing Machinery, New York, NY, USA, 352–361. https://doi.org/10.1145/2493190.2493225

Digital Library

[12]

Drew Clinkenbeard, Jennifer Clinkenbeard, Guillaume Faddoul, Heejung Kang, Sean Mayes, Alp Toygar, and Samir Chatterjee. 2014. What’s Your 2%? A Pilot Study for Encouraging Physical Activity Using Persuasive Video and Social Media. In Persuasive Technology, Anna Spagnolli, Luca Chittaro, and Luciano Gamberini (Eds.). Springer International Publishing, Cham, 43–55.

[13]

Justin Cranshaw, Emad Elwany, Todd Newman, Rafal Kocielnik, Bowen Yu, Sandeep Soni, Jaime Teevan, and Andrés Monroy-Hernández. 2017. Calendar.Help: Designing a Workflow-Based Scheduling Agent with Humans in the Loop. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). Association for Computing Machinery, New York, NY, USA, 2382–2393. https://doi.org/10.1145/3025453.3025780

Digital Library

[14]

Mary L Cummings. 2017. Automation bias in intelligent time critical decision support systems. In Decision Making in Aviation. Routledge, 289–294.

[15]

Ed Cutrell, Mary Czerwinski, and Eric Horvitz. 2001. Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance. In INTERACT 2001. IOS Press, 263–269. https://www.microsoft.com/en-us/research/publication/notification-disruption-and-memory-effects-of-messaging-interruptions-on-memory-and-performance/

[16]

Allan de Barcelos Silva, Marcio Miguel Gomes, Cristiano André da Costa, Rodrigo da Rosa Righi, Jorge Luis Victoria Barbosa, Gustavo Pessin, Geert De Doncker, and Gustavo Federizzi. 2020. Intelligent personal assistants: A systematic literature review. Expert Systems with Applications 147 (2020), 113193.

Digital Library

[17]

María del Carmen Rodríguez-Hernández and Sergio Ilarri. 2021. AI-based mobile context-aware recommender systems from an information management perspective: Progress and directions. Knowledge-Based Systems 215 (2021), 106740.

[18]

Paul Dourish. 2004. What we talk about when we talk about context. Personal and ubiquitous computing 8, 1 (2004), 19–30.

Digital Library

[19]

Denzil Ferreira, Vassilis Kostakos, and Anind K Dey. 2015. AWARE: mobile context instrumentation framework. Frontiers in ICT 2(2015), 6.

[20]

Rebecca Grinter and Margery Eldridge. 2003. Wan2tlk? Everyday Text Messaging. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Ft. Lauderdale, Florida, USA) (CHI ’03). Association for Computing Machinery, New York, NY, USA, 441–448. https://doi.org/10.1145/642611.642688

Digital Library

[21]

Ted Grover, Kael Rowan, Jina Suh, Daniel McDuff, and Mary Czerwinski. 2020. Design and Evaluation of Intelligent Agent Prototypes for Assistance with Focus and Productivity at Work. In Proceedings of the 25th International Conference on Intelligent User Interfaces (Cagliari, Italy) (IUI ’20). Association for Computing Machinery, New York, NY, USA, 390–400. https://doi.org/10.1145/3377325.3377507

Digital Library

[22]

Jeff Hancock, Jeremy Birnholtz, Natalya Bazarova, Jamie Guillory, Josh Perlin, and Barrett Amos. 2009. Butler Lies: Awareness, Deception and Design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, USA) (CHI ’09). Association for Computing Machinery, New York, NY, USA, 517–526. https://doi.org/10.1145/1518701.1518782

Digital Library

[23]

Steven R Haynes, Mark A Cohen, and Frank E Ritter. 2009. Designs for explaining intelligent agents. International Journal of Human-Computer Studies 67, 1 (2009), 90–110.

Digital Library

[24]

Roberto Hoyle, Srijita Das, Apu Kapadia, Adam J. Lee, and Kami Vaniea. 2017. Was My Message Read? Privacy and Signaling on Facebook Messenger. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). Association for Computing Machinery, New York, NY, USA, 3838–3842. https://doi.org/10.1145/3025453.3025925

Digital Library

[25]

Cheng-Kang Hsieh, Hongsuda Tangmunarunkit, Faisal Alquaddoomi, John Jenkins, Jinha Kang, Cameron Ketcham, Brent Longstaff, Joshua Selsky, Betta Dawson, Dallas Swendeman, Deborah Estrin, and Nithya Ramanathan. 2013. Lifestreams: A Modular Sense-Making Toolset for Identifying Important Patterns from Everyday Life. In Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems (Roma, Italy) (SenSys ’13). Association for Computing Machinery, New York, NY, USA, Article 5, 13 pages. https://doi.org/10.1145/2517351.2517368

Digital Library

[26]

Pranut Jain, Rosta Farzan, and Adam J. Lee. 2019. Adaptive Modelling of Attentiveness to Messaging: A Hybrid Approach. In Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (Larnaca, Cyprus) (UMAP ’19). Association for Computing Machinery, New York, NY, USA, 261–270. https://doi.org/10.1145/3320435.3320461

Digital Library

[27]

Pranut Jain, Rosta Farzan, and Adam J. Lee. 2019. Are You There? Identifying Unavailability in Mobile Messaging. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI EA ’19). Association for Computing Machinery, New York, NY, USA, 1–6. https://doi.org/10.1145/3290607.3312893

Digital Library

[28]

Pranut Jain, Rosta Farzan, and Adam J Lee. 2021. Context-based Automated Responses of Unavailability in Mobile Messaging. Computer Supported Cooperative Work (CSCW)(2021), 1–43.

[29]

Jason D. Johnson, Julian Sanchez, Arthur D. Fisk, and Wendy A. Rogers. 2004. Type of Automation Failure: The Effects on Trust and Reliance in Automation. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 48, 18 (2004), 2163–2167. https://doi.org/10.1177/154193120404801807 arXiv:https://doi.org/10.1177/154193120404801807

[30]

E. Kimani, K. Rowan, D. McDuff, M. Czerwinski, and G. Mark. 2019. A Conversational Agent in Support of Productivity and Wellbeing at Work. In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE Computer Society, Los Alamitos, CA, USA, 1–7. https://doi.org/10.1109/ACII.2019.8925488

[31]

Johannes Knittel, Alireza Sahami Shirazi, Niels Henze, and Albrecht Schmidt. 2013. Utilizing Contextual Information for Mobile Communication. In CHI ’13 Extended Abstracts on Human Factors in Computing Systems (Paris, France) (CHI EA ’13). Association for Computing Machinery, New York, NY, USA, 1371–1376. https://doi.org/10.1145/2468356.2468601

Digital Library

[32]

Stefan Kopp, Mara Brandt, Hendrik Buschmeier, Katharina Cyra, Farina Freigang, Nicole Krämer, Franz Kummert, Christiane Opfermann, Karola Pitsch, Lars Schillingmann, Carolin Straßmann, Eduard Wall, and Ramin Yaghoubzadeh. 2018. Conversational Assistants for Elderly Users – The Importance of Socially Cooperative Dialogue. In Proceedings of the AAMAS Workshop on Intelligent Conversation Agents in Home and Geriatric Care Applications co-located with the Federated AI Meeting (Stockholm, Sweden), Elizabeth André, Timothy Bickmore, Stefanos Vrochidis, and Leo Wanner (Eds.). Vol. 2338. RWTH, 10–17. https://nbn-resolving.org/urn:nbn:de:0070-pub-29201667, https://pub.uni-bielefeld.de/record/2920166

[33]

Albrecht Kurze, Andreas Bischof, Sören Totzauer, Michael Storz, Maximilian Eibl, Margot Brereton, and Arne Berger. 2020. Guess the Data: Data Work to Understand How People Make Sense of and Use Simple Sensor Data from Homes. Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3313831.3376273

Digital Library

[34]

Christine Lee. 2003. How does instant messaging affect interaction between the genders. Stanford, CA: The Mercury Project for Instant Messaging Studies at Stanford University. Retrieved August 11 (2003), 2006.

[35]

Zilu Liang, Bernd Ploderer, Wanyu Liu, Yukiko Nagata, James Bailey, Lars Kulik, and Yuxuan Li. 2016. SleepExplorer: a visualization tool to make sense of correlations between personal sleep data and contextual factors. Personal and Ubiquitous Computing 20, 6 (2016), 985–1000.

Digital Library

[36]

Yuting Liao, Jessica Vitak, Priya Kumar, Michael Zimmer, and Katherine Kritikos. 2019. Understanding the Role of Privacy and Trust in Intelligent Personal Assistant Adoption. In Information in Contemporary Society, Natalie Greene Taylor, Caitlin Christian-Lamb, Michelle H. Martin, and Bonnie Nardi (Eds.). Springer International Publishing, Cham, 102–113.

[37]

Scott M. Lundberg, Gabriel Erion, Hugh Chen, Alex DeGrave, Jordan M. Prutkin, Bala Nair, Ronit Katz, Jonathan Himmelfarb, Nisha Bansal, and Su-In Lee. 2020. From local explanations to global understanding with explainable AI for trees. Nature Machine Intelligence 2, 1 (2020), 2522–5839.

[38]

Deborah Lupton, Sarah Pink, Christine Heyes LaBond, and Shanti Sumartojo. 2018. Digital Traces in Context: Personal Data Contexts, Data Sense, and Self-Tracking Cycling. International Journal of Communications Special Issue on Digital Traces in Context, Vol 12, 647-665(2018).

[39]

Lisa M. Mai, Rainer Freudenthaler, Frank M. Schneider, and Peter Vorderer. 2015. “I know you’ve seen it!” Individual and social factors for users’ chatting behavior on Facebook. Computers in Human Behavior 49 (2015), 296 – 302. https://doi.org/10.1016/j.chb.2015.01.074

Digital Library

[40]

Mehdi Mekni, Zakaria Baani, and Dalia Sulieman. 2020. A Smart Virtual Assistant for Students. In Proceedings of the 3rd International Conference on Applications of Intelligent Systems (Las Palmas de Gran Canaria, Spain) (APPIS 2020). Association for Computing Machinery, New York, NY, USA, Article 15, 6 pages. https://doi.org/10.1145/3378184.3378199

Digital Library

[41]

Mohammad Naiseh, Nan Jiang, Jianbing Ma, and Raian Ali. 2020. Personalising Explainable Recommendations: Literature and Conceptualisation. In Trends and Innovations in Information Systems and Technologies, Álvaro Rocha, Hojjat Adeli, Luís Paulo Reis, Sandra Costanzo, Irena Orovic, and Fernando Moreira (Eds.). Springer International Publishing, Cham, 518–533.

[42]

Harri Oinas-Kukkonen and Marja Harjumaa. 2009. Persuasive systems design: Key issues, process model, and system features. Communications of the Association for Information Systems 24, 1(2009), 28.

[43]

Bauyrzhan Ospan, Nawaz Khan, Juan Augusto, Mario Quinde, and Kenzhegali Nurgaliyev. 2018. Context aware virtual assistant with case-based conflict resolution in multi-user smart home environment. In 2018 international conference on computing and network communications (coconet). IEEE, 36–44.

[44]

Motoyuki Ozeki, Shunichi Maeda, Kanako Obata, and Yuichi Nakamura. 2008. Virtual Assistant: An Artificial Agent for Enhancing Content Acquisition: How Ambient Media Elicit Information from Humans. In Proceedings of the 1st ACM International Workshop on Semantic Ambient Media Experiences (Vancouver, British Columbia, Canada) (SAME ’08). Association for Computing Machinery, New York, NY, USA, 75–82. https://doi.org/10.1145/1461912.1461927

Digital Library

[45]

Motoyuki Ozeki, Shunichi Maeda, Kanako Obata, and Yuichi Nakamura. 2009. Virtual assistant: enhancing content acquisition by eliciting information from humans. Multimedia Tools and Applications 44, 3 (2009), 433–448.

Digital Library

[46]

Lindsay C Page and Hunter Gehlbach. 2017. How an artificially intelligent virtual assistant helps students navigate the road to college. AERA Open 3, 4 (2017), 2332858417749220.

[47]

Veljko Pejovic and Mirco Musolesi. 2014. InterruptMe: Designing Intelligent Prompting Mechanisms for Pervasive Applications. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Seattle, Washington) (UbiComp ’14). Association for Computing Machinery, New York, NY, USA, 897–908. https://doi.org/10.1145/2632048.2632062

Digital Library

[48]

Sobah Abbas Petersen, Jörg Cassens, Anders Kofod-Petersen, and Monica Divitini. 2008. To be or not to be aware: Reducing interruptions in pervasive awareness systems. In 2008 The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies. IEEE, 327–332.

Digital Library

[49]

Martin Pielot, Bruno Cardoso, Kleomenis Katevas, Joan Serrà, Aleksandar Matic, and Nuria Oliver. 2017. Beyond Interruptibility: Predicting Opportune Moments to Engage Mobile Phone Users. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3, Article 91 (sep 2017), 25 pages. https://doi.org/10.1145/3130956

Digital Library

[50]

Martin Pielot, Rodrigo de Oliveira, Haewoon Kwak, and Nuria Oliver. 2014. Didn’t You See My Message? Predicting Attentiveness to Mobile Instant Messages. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Toronto, Ontario, Canada) (CHI ’14). Association for Computing Machinery, New York, NY, USA, 3319–3328. https://doi.org/10.1145/2556288.2556973

Digital Library

[51]

Martin Pielot, Tilman Dingler, Jose San Pedro, and Nuria Oliver. 2015. When Attention is Not Scarce - Detecting Boredom from Mobile Phone Usage. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Osaka, Japan) (UbiComp ’15). Association for Computing Machinery, New York, NY, USA, 825–836. https://doi.org/10.1145/2750858.2804252

Digital Library

[52]

Ana Paula Retore and Leonelo Dell Anhol Almeida. 2019. Understanding Appropriation Through End-User Tailoring in Communication Systems: A Case Study on Slack and WhatsApp. In Social Computing and Social Media. Design, Human Behavior and Analytics, Gabriele Meiselwitz (Ed.). Springer International Publishing, Cham, 245–264.

[53]

Stephanie Rosenthal, Anind K. Dey, and Manuela Veloso. 2011. Using Decision-Theoretic Experience Sampling to Build Personalized Mobile Phone Interruption Models. In Proceedings of the 9th International Conference on Pervasive Computing (San Francisco, USA) (Pervasive’11). Springer-Verlag, Berlin, Heidelberg, 170–187.

Digital Library

[54]

Antti Salovaara, Antti Lindqvist, Tero Hasu, and Jonna Häkkilä. 2011. The Phone Rings but the User Doesn’t Answer: Unavailability in Mobile Communication. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services (Stockholm, Sweden) (MobileHCI ’11). Association for Computing Machinery, New York, NY, USA, 503–512. https://doi.org/10.1145/2037373.2037448

Digital Library

[55]

Maxim Stepanov. 2020. Some stats about voice assistants. https://uxdesign.cc/some-stats-about-voice-assistants-1c292476584. Accessed: 2021-07-20.

[56]

John C. Tang. 2007. Approaching and Leave-Taking: Negotiating Contact in Computer-Mediated Communication. ACM Trans. Comput.-Hum. Interact. 14, 1 (may 2007), 5–es. https://doi.org/10.1145/1229855.1229860

Digital Library

[57]

Lauren Thomson, Adam J. Lee, and Rosta Farzan. 2018. Ephemeral Communication and Communication Places. In Transforming Digital Worlds, Gobinda Chowdhury, Julie McLeod, Val Gillet, and Peter Willett (Eds.). Springer International Publishing, Cham, 132–138.

[58]

Nava Tintarev and Judith Masthoff. 2011. Designing and Evaluating Explanations for Recommender Systems. Springer US, Boston, MA, 479–510. https://doi.org/10.1007/978-0-387-85820-3_15

[59]

Christiana Tsiourti, Maher Ben Moussa, João Quintas, Ben Loke, Inge Jochem, Joana Albuquerque Lopes, and Dimitri Konstantas. 2018. A Virtual Assistive Companion for Older Adults: Design Implications for a Real-World Application. In Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016, Yaxin Bi, Supriya Kapoor, and Rahul Bhatia (Eds.). Springer International Publishing, Cham, 1014–1033.

[60]

Joshua R. Tyler and John C. Tang. 2003. When Can I Expect an Email Response? A Study of Rhythms in Email Usage. In ECSCW 2003, Kari Kuutti, Eija Helena Karsten, Geraldine Fitzpatrick, Paul Dourish, and Kjeld Schmidt (Eds.). Springer Netherlands, Dordrecht, 239–258.

[61]

Amy Voida, Wendy C. Newstetter, and Elizabeth D. Mynatt. 2002. When Conventions Collide: The Tensions of Instant Messaging Attributed. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Minneapolis, Minnesota, USA) (CHI ’02). Association for Computing Machinery, New York, NY, USA, 187–194. https://doi.org/10.1145/503376.503410

Digital Library

[62]

Steve Whittaker, Vaiva Kalnikaite, Victoria Hollis, and Andrew Guydish. 2016. ’Don’t Waste My Time’: Use of Time Information Improves Focus. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 1729–1738. https://doi.org/10.1145/2858036.2858193

Digital Library

[63]

Michael Winikoff, Jocelyn Cranefield, Jane Li, Cathal Doyle, and Alexander Richter. 2021. The Advent of Digital Productivity Assistants: The Case of Microsoft MyAnalytics. In HICSS. 1–10.

[64]

Ting-Wei Wu, Yu-Ling Chien, Hao-Ping Lee, and Yung-Ju Chang. 2021. IM Receptivity and Presentation-Type Preferences among Users of a Mobile App with Automated Receptivity-Status Adjustment. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 640, 14 pages. https://doi.org/10.1145/3411764.3445209

Digital Library

[65]

Neil Yorke-Smith, Shahin Saadati, Karen L Myers, and David N Morley. 2012. The design of a proactive personal agent for task management. International Journal on Artificial Intelligence Tools 21, 01(2012), 1250004.

[66]

Fengpeng Yuan, Xianyi Gao, and Janne Lindqvist. 2017. How Busy Are You?: Predicting the Interruptibility Intensity of Mobile Users. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). ACM, New York, NY, USA, 5346–5360. https://doi.org/10.1145/3025453.3025946

Digital Library

Cited By

Kim ILee A(2024)"I know what you did last semester": Understanding Privacy Expectations and Preferences in the Smart CampusProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642174(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642174
Jain PFarzan RLee A(2023)Co-Designing with Users the Explanations for a Proactive Auto-Response Messaging AgentProceedings of the ACM on Human-Computer Interaction10.1145/36042487:MHCI(1-23)Online publication date: 13-Sep-2023
https://dl.acm.org/doi/10.1145/3604248
Jeromela JConlan O(2023)Voicing Suggestions and Enabling Reflection: Results of an Expert Discussion on Proactive Assistants for Time ManagementProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3604317(1-6)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3604317
Show More Cited By

Recommendations

Co-Designing with Users the Explanations for a Proactive Auto-Response Messaging Agent
MHCI

Explanations of AI Agents' actions are considered to be an important factor in improving users' trust in the decisions made by autonomous AI systems. However, as these autonomous systems evolve from reactive, i.e., acting on user input, to proactive, ...
Design and Evaluation of a Virtual Assistant for improving Awareness in Mobile Messaging
GROUP '23: Companion Proceedings of the 2023 ACM International Conference on Supporting Group Work

Mobile messaging suffers from the lack of effective communication cues that help people infer the availability of others, like in face-to-face communication. My research focuses on designing, implementing, and evaluating an agent that can communicate ...
Learning Summarised Messaging Through Mediated Differentiable Inter-Agent Learning
Multi-Agent Systems and Agreement Technologies
Abstract
In recent years, notable research has been done in the area of communication in multi-agent systems. When agents have a partial view of the environment, communication becomes essential for collaboration. We propose a Deep Q-Learning based multi-...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

DIS '22: Proceedings of the 2022 ACM Designing Interactive Systems Conference

June 2022

1947 pages

ISBN:9781450393584

DOI:10.1145/3532106

Editors:
Florian `Floyd' Mueller
Monash University, Melbourne, Australia
,
Stefan Greuter
Deakin University, Melbourne, Australia
,
Rohit Ashok Khot
RMIT University, Melbourne, Australia
,
Penny Sweetser
The Australian National University, Canberra, Australia
,
Marianna Obrist
University College London, UK

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 June 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Badges

Honorable Mention

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

National Science Foundation

Conference

DIS '22

Sponsor:

SIGCHI

DIS '22: Designing Interactive Systems Conference

June 13 - 17, 2022

Virtual Event, Australia

Acceptance Rates

Overall Acceptance Rate 1,158 of 4,684 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
761
Total Downloads

Downloads (Last 12 months)477
Downloads (Last 6 weeks)97

Reflects downloads up to 16 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Kim ILee A(2024)"I know what you did last semester": Understanding Privacy Expectations and Preferences in the Smart CampusProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642174(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642174
Jain PFarzan RLee A(2023)Co-Designing with Users the Explanations for a Proactive Auto-Response Messaging AgentProceedings of the ACM on Human-Computer Interaction10.1145/36042487:MHCI(1-23)Online publication date: 13-Sep-2023
https://dl.acm.org/doi/10.1145/3604248
Jeromela JConlan O(2023)Voicing Suggestions and Enabling Reflection: Results of an Expert Discussion on Proactive Assistants for Time ManagementProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3604317(1-6)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3604317
Jain P(2023)Design and Evaluation of a Virtual Assistant for improving Awareness in Mobile MessagingCompanion Proceedings of the 2023 ACM International Conference on Supporting Group Work10.1145/3565967.3571758(63-65)Online publication date: 8-Jan-2023
https://dl.acm.org/doi/10.1145/3565967.3571758

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents