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DTSTART:20210314T070000
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DTSTART;TZID=America/New_York:20210319T160000
DTEND;TZID=America/New_York:20210319T170000
DTSTAMP:20260814T081915
CREATED:20210122T191921Z
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SUMMARY:Ishtiaque Ahmed - Designing for Voice
DESCRIPTION:Designing for Voice: Access\, Autonomy\, and Justification Questions in Designing Computing Technologies with Marginalized Communities \nThe benefits of computing are often confined within the populations with certain privileges. Those benefits rarely reach billions of underprivileged lives around the world fighting extreme poverty\, illiteracy\, gender discrimination\, forced migration\, and various other exploitations and marginalization. The services that are available through computing often fail to address their needs and constraints. My research with various marginalized communities in the Indian subcontinent over the last twelve years has revealed how this failure is often associated with some of the core issues of computing\, including access\, autonomy\, and justification. In this talk\, I will explain these three topics by describing three projects that I have been working on\, each of which involves ethnography and design work with marginalized communities in Bangladesh\, India\, Pakistan\, and Canada. My talk will focus on how access to computing becomes limited by the imposition of colonial perspectives\, how autonomy over a digital platform is curtailed by discriminatory standards\, and how computing technologies often silence local voices by using western scientific rationalities. In this talk\, I will further demonstrate how my design research explores possible ways to strengthen the voice of marginalized communities by focusing on local values\, participation\, and pluralism. \nFridays 1-2 pm PT · On Zoom · Seminar on People\, Computers\, and Design · Open to the public \nRSVP: https://mailman.stanford.edu/mailman/listinfo/pcd-seminar
URL:https://archive.sigchi.org/event/ishtiaque-ahmed-tbd/
CATEGORIES:Events
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210305T160000
DTEND;TZID=America/New_York:20210305T170000
DTSTAMP:20260814T081915
CREATED:20210122T191655Z
LAST-MODIFIED:20210122T192016Z
UID:10000055-1614960000-1614963600@archive.sigchi.org
SUMMARY:Designing for Human - AI Complementarity
DESCRIPTION:AI systems are increasingly used to support human work in richly social contexts such as education\, healthcare\, and social work. To ensure that AI systems do more good than harm\, it is critical that they are designed to bring out the best of human ability while also helping to overcome human limitations. In some cases\, AI has the potential to help humans scale the delivery of services\, make more equitable decisions\, and free up human time for more meaningful activities. Yet if not carefully designed\, AI systems risk rigidly scaling practices without sensitivity to local context\, propagating harmful inequities\, or automating away valuable human–human interactions. \nIn this talk\, I will share work towards the design of systems that combine complementary strengths of human and AI decision-making\, across two main research strands: 1) co-designing effective human–AI partnerships for K-12 education and 2) supporting fairer decision-making in human–AI systems. As a case study\, I will first discuss insights from the co-design\, development\, and field evaluation of Lumilo\, a form of real-time\, wearable augmentation for K-12 teachers who work with AI tutors in the classroom. Then\, I will share research exploring commercial product teams’ challenges and needs for support in developing fairer AI systems. Finally\, I will discuss some ongoing research directions within my group\, exploring core challenges in designing for human–AI complementarity. \n \n\nKen Holstein is an Assistant Professor in the Human–Computer Interaction Institute at Carnegie Mellon University and director of the Co- Augmentation\, Learning\, & AI (CoALA) Lab: https://www.thecoalalab.com/. Their group creates and studies human–AI collaborative systems to support fundamentally human forms of work (i.e.\, ones projected to resist full automation\, such as care-based\, creative\, and social work). In their work\, they typically partner with relevant stakeholders in real-world contexts to co-design and build novel human–AI systems that draw upon complementary strengths of human and AI decision-makers. Finally\, they conduct field studies to understand the dynamics and impacts of human–AI collaborations in real-world contexts. \nFridays 1-2pm PT · On Zoom · Seminar on People\, Computers\, and Design · Open to the public · \nRSVP: https://mailman.stanford.edu/mailman/listinfo/pcd-seminar
URL:https://archive.sigchi.org/event/designing-for-human-ai-complementarity/
CATEGORIES:Events
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DTSTART;TZID=America/New_York:20210226T160000
DTEND;TZID=America/New_York:20210226T170000
DTSTAMP:20260814T081916
CREATED:20210122T191525Z
LAST-MODIFIED:20210223T132716Z
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SUMMARY:Smart Tutoring Through Conversational Interfaces
DESCRIPTION:In the well-known two sigma problem introduced in 1984\, Bloom found that students tutored by a one-on-one mastery-learning tutor achieved a learning outcome two standard deviations higher than those tutored by traditional learning methods. Since one-on-one tutoring is too costly to scale to billions of students in society\, technology has been perceived as a promising tool to simulate a one-on-one tutoring experience. However\, current electronic learning systems still primarily consist of learning activities with limited interactions such as multiple-choice questions\, review-and-flip flash cards\, and listen-and-repeat practices. With recent advances in artificial intelligence (AI)\, we now have the potential to create conversation-based tutoring systems with the capability of providing personalized feedback to make learning much more engaging and effective\, and eventually help bridge the gap between one-on-one human tutoring and computer tutoring. \nIn this talk\, I present the design\, development\, and testing of four AI-based conversational tutoring systems that personalize learning for both adults and children. For adult learning\, I present two systems\, QuizBot for helping college students learn factual knowledge and EnglishBot for tutoring language learners in speaking English. For child learning\, I present two systems integrating narratives into conversational tutoring systems\, BookBuddy for helping children develop reading comprehension abilities and SmartPrimer for supplementing elementary school students’ math learning. I conduct human evaluations with these tutoring systems to understand how humans interact with AI in the educational setting. The test with over 500 students show that conversation-based tutoring systems that leverage new natural language processing (NLP) and reinforcement learning (RL) techniques can provide adaptive feedback\, engage students more\, motivate them to spend more time using the tutor\, and improve student learning outcomes\, when compared to current learning systems. \n \n\nSherry (Shanshan) Ruan is a Ph.D. candidate in Computer Science at Stanford University\, where she is advised by James Landay. Her research lies at the intersection of human-computer interaction and artificial intelligence with a focus on designing and building smart tutoring systems to improve student learning. Her work has been published in academic outlets such as CHI\, UbiComp\, IUI\, IDC\, LAS\, and AAAI\, and featured in media outlets such as NPR and WEF. Sherry received her B.Sc. in Mathematics and Computer Science from McGill University in Canada. \nFridays 1-2pm PT · On Zoom · Seminar on People\, Computers\, and Design · Open to the public · \nRSVP: https://mailman.stanford.edu/mailman/listinfo/pcd-seminar
URL:https://archive.sigchi.org/event/thesis-defense-smart-tutoring-through-conversational-interfaces/
CATEGORIES:Events
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DTSTART;TZID=America/New_York:20210219T160000
DTEND;TZID=America/New_York:20210219T170000
DTSTAMP:20260814T081916
CREATED:20210122T191347Z
LAST-MODIFIED:20210217T023005Z
UID:10000060-1613750400-1613754000@archive.sigchi.org
SUMMARY:Erin Hoffman-John\, Stadia — Machine Learning for Designers
DESCRIPTION:Machine learning is the next great technological revolution\, working hand-in-hand with distributed datacenter technology to achieve a paradigm shift in computing over the next decade. We often discuss machine learning and AI technologies in pure engineering terms — this talk will posit how to think about ML from a design perspective\, and why it is critically important for us to do so. \nErin is currently Head of Creative for Stadia R&D\, the gameplay research and development team for the streaming video games platform called Stadia. Stadia R&D produces prototypes aimed at unlocking the potential of cloud based games for game developers to create new kinds of game experiences. Prior to Stadia she was a game designer\, speaker/professor\, and author for orgs including Carnegie Mellon University\, Konami\, DreamWorks\, Zynga\, GlassLab\, and Simutronics. \nSubscribe to attend
URL:https://archive.sigchi.org/event/erin-hoffman-john/
CATEGORIES:Events
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DTSTART;TZID=America/New_York:20210212T160000
DTEND;TZID=America/New_York:20210212T170000
DTSTAMP:20260814T081916
CREATED:20210122T191202Z
LAST-MODIFIED:20210122T191230Z
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SUMMARY:Accessible Virtual Reality for People with Limited Mobility
DESCRIPTION:Virtual reality (VR) offers new and compelling ways for users to interact with digital content. VR provides immersive experiences that can be beneficial in various domains\, such as gaming\, training simulations\, education\, communication\, and design. As VR technologies continue to mature\, and as commercial VR systems continue to grow in popularity\, an opportunity exist to understand how to incorporate accessibility as a fundamental component in the design of VR systems and applications. This talk will describe ongoing research to understand and eliminate accessibility barriers that prevent people with limited mobility from engaging with VR. \n \n\nMartez Mott is a Senior Researcher in the Ability Group at Microsoft Research. His research is focused on designing\, implementing\, and evaluating intelligent interaction techniques that improve the accessibility of computing devices for people with diverse motor and sensory abilities. His current research focuses on identifying and overcoming accessibility barriers embedded in the design of virtual and augmented reality systems. Martez is passionate about improving diversity in the CS and HCI communities. He co-chaired the 2020 CHIMe Workshop\, is serving on the steering committee for CHIMe 2021\, and co-created the Black Researchers @ MSR group. Martez received his Ph.D. in Information Science from the Information School at the University of Washington. Prior to attending UW\, he received his B.S. and M.S. in Computer Science from Bowling Green State University. \nFridays 1-2pm PT · On Zoom · Seminar on People\, Computers\, and Design · Open to the public · Subscribe to email announcements
URL:https://archive.sigchi.org/event/accessible-virtual-reality-for-people-with-limited-mobility/
CATEGORIES:Events
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DTSTART;TZID=America/New_York:20210205T160000
DTEND;TZID=America/New_York:20210205T170000
DTSTAMP:20260814T081916
CREATED:20210122T191018Z
LAST-MODIFIED:20210122T191018Z
UID:10000062-1612540800-1612544400@archive.sigchi.org
SUMMARY:Designing Assistive Technologies for Agency: Blind-Accessible Video Games and Audio Navigation Tools
DESCRIPTION:Accessibility alone has not been enough to allow visually impaired people (VIPs) to experience the world with the same level of independence and richness as others can. Audio-based assistive technologies such as navigation aids and audio games (audio-only video games) succeed in making navigating and playing games accessible to VIPs\, but they come far from providing an experience equivalent to what sighted people enjoy. These technologies often act as guides that tell VIPs what to do\, but our goal should be to give VIPs the ability to make decisions themselves. In this talk\, I will show how to design assistive technologies to foster agency rather than merely acting as a guide. I will show two examples from my new lab\, which both to blind-accessible video games: the racing auditory display (RAD)\, which makes racing video games equivalently accessible to VIPs; and NavStick\, which gives users the ability to “look around” within virtual worlds. I will also discuss the implications that these systems have on real-world navigation. \n \n\nBrian A. Smith is an Assistant Professor of Computer Science at Columbia University\, where he directs the Computer-Enabled Abilities Laboratory (CEAL). He is also a Research Scientist in Snap Inc.’s HCI Research group. His research goal is to develop computers that can grant people new abilities\, abilities that help people better experience the world. His research approach is interdisciplinary and incorporates AI\, accessibility\, computer vision\, game design\, and social computing. \nBrian received his Ph.D. in Computer Science from Columbia University. Prior to joining Columbia and Snap\, he worked at Google Research and several small game development studios. \n\n\nFridays 1-2pm PT · On Zoom · Seminar on People\, Computers\, and Design · Open to the public · Subscribe to email announcements
URL:https://archive.sigchi.org/event/designing-assistive-technologies-for-agency-blind-accessible-video-games-and-audio-navigation-tools/
CATEGORIES:Events
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210129T160000
DTEND;TZID=America/New_York:20210129T170000
DTSTAMP:20260814T081916
CREATED:20210122T190735Z
LAST-MODIFIED:20210122T190735Z
UID:10000064-1611936000-1611939600@archive.sigchi.org
SUMMARY:Monroe Kennedy III
DESCRIPTION:The field of robotics has evolved over the past few decades. We’ve seen robots progress from the automation of repetitive tasks in manufacturing to the autonomy of mobilizing in unstructured environments to the cooperation of swarm robots that are centralized or decentralized. These abilities have required advances in robotic hardware\, modeling\, and artificial intelligence. The next frontier is robots collaborating in complex tasks with human teammates\, in environments traditionally configured for humans. While solutions to this challenge must utilize all of the advances of robotics\, the human element adds a unique aspect that must be addressed. Collaborating with a human teammate means that the robot must have a contextual understanding of the task as well as all participant’s roles. We will discuss what constitutes an effective teammate and how we can capture this behavior in a robotic collaborator. \n\n\n\n \n\nMonroe Kennedy III is an assistant professor in Mechanical Engineering at Stanford University. He leads the Assistive Robotics and Manipulation laboratory (arm.stanford.edu)\, which will develop robotic assistants by focusing on combining modeling and control techniques together with machine learning tools. Together\, these techniques will improve performance for tasks that are highly dynamic\, require dexterity\, have considerable complexity and require human-robot collaboration. Prof. Kennedy received his Ph.D. in Mechanical Engineering and Applied Mechanics and Masters in Robotics at the University of Pennsylvania\, advised by Dr. Vijay Kumar\, with a focus in robotics in the GRASP Lab. He was the recipient of GEM and NSF graduate fellowships. During his graduate studies\, his research focused on increasing the abilities and effectiveness of robotic mobile manipulators performing complex service tasks in unstructured environments with considerations for working alongside human collaborators. \n\n\n\n\nFridays 1-2pm PT · On Zoom · Seminar on People\, Computers\, and Design · Open to the public · Subscribe to email announcements
URL:https://archive.sigchi.org/event/monroe-kennedy-iii/
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