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X-WR-CALDESC:Events for ACM SIGCHI
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210201T100000
DTEND;TZID=America/New_York:20210201T113000
DTSTAMP:20260814T063720
CREATED:20210122T175212Z
LAST-MODIFIED:20210122T175212Z
UID:10000220-1612173600-1612179000@archive.sigchi.org
SUMMARY:Nithya Sambasivan
DESCRIPTION:Title: Everyone wants to do the model work\, not the data work: Human-Data Interaction in AI \nAbstract: AI models are increasingly applied in high-stakes domains like health and conservation. Data quality carries an elevated significance in high-stakes AI due to its heightened downstream impact to living beings. Paradoxically\, data is the most under-valued and de-glamorized aspect of AI. In this paper\, we report on data practices in high-stakes AI\, from interviews with 53 AI practitioners in India\, East and West African countries\, and USA. We define and report on Data Cascades compounding events causing negative\, downstream effects from data issues triggered by conventional AI/ML practices that undervalue data quality. Data cascades are pervasive (92% prevalence)\, invisible\, delayed\, but often avoidable. Data cascades demonstrate how broken incentives for data quality impact vulnerable groups tigers alive or dead\, cancer diagnosed or not. We also discuss findings on data collectors and raters\, paying attention to their values\, processes\, and tools. We discuss opportunities for HCI to design and incentivize data excellence\, moving from reactive to proactive focus on data work and workers in AI resulting in safer and robust systems for all. \nSpeaker Biography: Nithya Sambasivan is a Staff Researcher at PAIR and leads the HCI-AI group at Google Research India\, Bangalore. Nithya’s current research focuses on using HCI techniques in developing responsible AI in India\, with a focus on marginalized communities. Specific sub-areas are data\, fairness\, privacy and abuse\, and consent. She publishes in the fields of HCI\, ICTD\, and Privacy/Security. Nithya’s long-standing research agenda has been on HCI and under-represented communities in the Global South. She has a PhD. in Informatics from UC Irvine and a Master’s in HCI from Georgia Tech. \nHomepage: https://nithyasambasivan.com/ \nRSVP: https://www.academicfringe.org/registration
URL:https://archive.sigchi.org/event/nithya-sambasivan/
CATEGORIES:Events
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210118T100000
DTEND;TZID=America/New_York:20210118T110000
DTSTAMP:20260814T063720
CREATED:20201125T224936Z
LAST-MODIFIED:20201125T225045Z
UID:10000186-1610964000-1610967600@archive.sigchi.org
SUMMARY:Michael Bernstein
DESCRIPTION:Title: TBD \nSpeaker Biography: Michael Bernstein is an Associate Professor of Computer Science and STMicroelectronics Faculty Scholar at Stanford University\, where he is a member of the Human-Computer Interaction Group. His research focuses on the design of social computing and crowdsourcing systems. This research has won best paper awards at top conferences in human-computer interaction\, including CHI\, CSCW\, and UIST\, and recently a Lasting Impact Award from UIST 2020. Michael has been recognized with an NSF CAREER award and an Alfred P. Sloan Fellowship. He holds a bachelor’s degree in Symbolic Systems from Stanford University\, as well as a master’s degree and a Ph.D. in Computer Science from MIT. \nHomepage: https://hci.stanford.edu/msb/ \nRSVP: https://www.academicfringe.org/registration
URL:https://archive.sigchi.org/event/michael-bernstein/
CATEGORIES:Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210111T120000
DTEND;TZID=America/New_York:20210111T130000
DTSTAMP:20260814T063720
CREATED:20201125T224824Z
LAST-MODIFIED:20201126T141657Z
UID:10000185-1610366400-1610370000@archive.sigchi.org
SUMMARY:Panos Ipeirotis
DESCRIPTION:Speaker Biography: Panos Ipeirotis is a Professor and David Margolis Teaching Excellence Faculty Fellow at the Department of Technology\, Operations\, and Statistics at the Leonard N. Stern School of Business of New York University\, and also an associated faculty member at the Center for Data Science and Computer Science departments. \nHe is also a Distinguished Scientist at Compass\, a role assumed after Compass acquired Detectica\, a startup he co-founded with Foster Provost. \nHe has received ten “Best Paper” awards and nominations\, a CAREER award from the National Science Foundation\, and is the recipient of the 2015 Lagrange Prize in Complex Systems\, for his contributions in the field of social media\, user-generated content\, and crowdsourcing. \nHe got his Ph.D. degree in Computer Science from Columbia University in 2004. \nRSVP: https://www.academicfringe.org/registration
URL:https://archive.sigchi.org/event/panos-ipeirotis/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201214T100000
DTEND;TZID=America/New_York:20201214T110000
DTSTAMP:20260814T063720
CREATED:20201125T224546Z
LAST-MODIFIED:20201125T224546Z
UID:10000184-1607940000-1607943600@archive.sigchi.org
SUMMARY:Redefining Productivity to Adapt to a Changing Landscape of Work - Shamsi Iqbal
DESCRIPTION:Title: Redefining Productivity to Adapt to a Changing Landscape of Work \nAbstract: As our work environments and work practices rapidly evolves as a result of the changing landscape of work\, what we envision as the future of work is being fundamentally challenged. Research in the area of productivity and multitasking has to adapt to the changing world anticipating what the future may look like – in particular taking into account growing needs of balancing work and life. In this research I will talk about redefining productivity where doing work is no longer confined to being at a desk and the need to do things while on the go or while in divided attention scenarios continues to dominate. Our team at Microsoft Research has looked at how complex tasks can be done without having to allocate larger chunks of time\, rather\, make use of seemingly unusable ‘micromoments’ – by decomposing a task into smaller tasks that can be done in a few moments. This work brings together theories from cognitive science\, human computer interaction and artificial intelligence. I will discuss a few ongoing projects in this area and present directions for research and product development. \nSpeaker Biography: Dr. Shamsi T. Iqbal is a Principal Researcher in the Productivity and Intelligence group (P+I) in Microsoft Research\, Redmond. Her primary expertise is in the domain of Attention Management and Interruptions. More recently her work has focused on redefining productivity\, introducing novel ways of being productive through leveraging micromoments and balancing productivity and well-being in interaction design. Her work on driving and distraction has been featured in the New York Times\, MIT Tech Review among others\, and also featured in the King 5 News (NBC affiliate in the Seattle area). Shamsi has served on many organizing and program committees for Human-Computer Interaction conferences\, is currently serving as an ACM TOCHI Associate Editor and was the General Co-chair for UIST 2020. Shamsi received her Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 2008 and Bachelors in Computer Science and Engineering from Bangladesh University of Engineering and Technology in 2001. \nRSVP: https://www.academicfringe.org/registration
URL:https://archive.sigchi.org/event/redefining-productivity-to-adapt-to-a-changing-landscape-of-work-shamsi-iqbal/
CATEGORIES:Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201207T100000
DTEND;TZID=America/New_York:20201207T110000
DTSTAMP:20260814T063720
CREATED:20201125T224350Z
LAST-MODIFIED:20201125T224355Z
UID:10000183-1607335200-1607338800@archive.sigchi.org
SUMMARY:Guidelines for Human-AI Interaction: Mihaela Vorvoreanu
DESCRIPTION:Title: Guidelines for Human-AI Interaction \nAbstract: In this talk\, Mihaela will present the work of synthesizing 20+ years on literature on human-AI and mixed initiative systems into 18 guidelines for human-AI interaction. She will introduce the guidelines to the audience and discuss their applications and implications for the design of user-facing AI systems. \nSpeaker Biography: Dr. Mihaela Vorvoreanu is head of UX research for Aether – Microsoft’s advisory committee on AI\, Ethics and Effects in Engineering and Research. Previous to joining Microsoft\, Mihaela was on the faculty at Purdue University\, where she founded and led undergraduate and graduate education in UX Design. \nRSVP: https://www.academicfringe.org/registration
URL:https://archive.sigchi.org/event/guidelines-for-human-ai-interaction-mihaela-vorvoreanu/
CATEGORIES:Events
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201130T030000
DTEND;TZID=America/New_York:20201130T040000
DTSTAMP:20260814T063720
CREATED:20201125T224050Z
LAST-MODIFIED:20201125T224050Z
UID:10000182-1606705200-1606708800@archive.sigchi.org
SUMMARY:Bias in Human-in-the-loop Artificial Intelligence - Gianluca Demartini
DESCRIPTION:Title: Bias in Human-in-the-loop Artificial Intelligence \nAbstract: Paid micro-task crowdsourcing has gained popularity also thanks to the rise of AI because of the convenient way to generate large-scale manually annotated corpora and because of the possibility to create human-in-the-loop systems. However\, when using crowdsourcing platforms for data gathering purposes\, human factors need to be taken into account as humans now become part of (and are not just users of) the system. \nIn this talk I will discuss our recent research in the area of micro-task crowdsourcing with a focus on understanding crowd worker behaviors and their implications on the quality of the collected data and the bias in it. I will first discuss open challenges in the crowdsourcing ecosystem including issues caused by adversarial approaches that may disrupt the crowdsourcing model as we know it. I will then discuss how human bias is reflected in the data which is being collected by means of crowdsourcing. Finally\, I will present our work making use of fine-grained behavioral logs. \nSpeaker Biography: Dr. Gianluca Demartini is an Associate Professor in Data Science at the University of Queensland\, School of Information Technology and Electrical Engineering. His main research interests are Information Retrieval\, Semantic Web\, and Human Computation. His research has been supported by the Australian Research Council (ARC)\, the UK Engineering and Physical Sciences Research Council (EPSRC)\, and by the EU H2020 framework program. He received Best Paper Awards at the AAAI Conference on Human Computation and Crowdsourcing (HCOMP) in 2018 and at the European Conference on Information Retrieval (ECIR) in 2016\, the Best Short Paper award at ECIR in 2020 and the Best Demo Award at the International Semantic Web Conference (ISWC) in 2011. He has published more than 100 peer-reviewed scientific publications including papers at major venues such as WWW\, ACM SIGIR\, VLDBJ\, ISWC\, and ACM CHI. \nHe has given several invited talks\, tutorials\, and keynotes at a number of academic conferences (e.g.\, ISWC\, ICWSM\, WebScience\, and the RuSSIR Summer School)\, companies (e.g.\, Facebook)\, and Dagstuhl seminars. He is a senior member of the ACM since 2020\, an ACM Distinguished Speaker since 2015\, and has been a TEDx speaker in 2019. \nHe serves as co-editor in chief for the Human Computation journal\, area editor for the Journal of Web Semantics\, and editorial board member for the Information Retrieval journal. He is General co-Chair for the ACM International Conference on Information and Knowledge Management (CIKM) 2021. He has been Senior Program Committee member for\, among others\, the ACM Conference on Research and Development in Information Retrieval (SIGIR)\, the ACM Web Search and Data Mining (WSDM) Conference\, the AAAI Conference on Human Computation and Crowdsourcing (HCOMP)\, and the International Conference on Web Engineering (ICWE). He is Program Committee member for several conferences including WWW\, SIGIR\, KDD\, IJCAI\, AAAI\, ISWC\, and ICWSM. He was Crowdsourcing and Human Computation Track co-Chair at WWW 2018 and co-chair for the Human Computation and Crowdsourcing Track at ESWC 2015. He co-organized several workshops and tutorials at international conferences as well as the Entity Ranking Track at the Initiative for the Evaluation of XML Retrieval in 2008 and 2009. \nBefore joining the University of Queensland\, he was Lecturer at the University of Sheffield in UK\, post-doctoral researcher at the eXascale Infolab at the University of Fribourg in Switzerland\, visiting researcher at UC Berkeley\, junior researcher at the L3S Research Center in Germany\, and intern at Yahoo! Research in Spain. In 2011\, he obtained a Ph.D. in Computer Science at the Leibniz University of Hanover focusing on Semantic Search. \nHomepage: http://www.gianlucademartini.net/ \nRSVP: https://www.academicfringe.org/registration
URL:https://archive.sigchi.org/event/bias-in-human-in-the-loop-artificial-intelligence-gianluca-demartini/
CATEGORIES:Events
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20201123T100000
DTEND;TZID=America/New_York:20201123T110000
DTSTAMP:20260814T063720
CREATED:20201120T183419Z
LAST-MODIFIED:20201120T185134Z
UID:10000029-1606125600-1606129200@archive.sigchi.org
SUMMARY:Matthew Lease - The Academic Fringe Festival
DESCRIPTION:Title: Adventures in Crowdsourcing: Toward Safer Content Moderation and Better Supporting Complex Annotation Tasks \nAbstract: I’ll begin the talk discussing content moderation. While most user content posted on social media is benign\, other content\, such as violent or adult imagery\, must be detected and blocked. Unfortunately\, such detection is difficult to automate\, due to high accuracy requirements\, costs of errors\, and nuanced rules for acceptable content. Consequently\, social media platforms today rely on a vast workforce of human moderators. However\, mounting evidence suggests that exposure to disturbing content can cause lasting psychological and emotional damage to some moderators. To mitigate such harm\, we investigate a set of blur-based moderation interfaces for reducing exposure to disturbing content whilst preserving moderator ability to quickly and accurately flag it. We report experiments with Mechanical Turk workers to measure moderator accuracy\, speed\, and emotional well-being across six alternative designs. Our key findings show interactive blurring designs can reduce emotional impact without sacrificing moderation accuracy and speed. See our online demo at: http://ir.ischool.utexas.edu/CM/demo/. \nThe second part of my talk will discuss aggregation modeling. Though many models have been proposed for binary or categorical labels\, prior methods do not generalize to complex annotations (e.g.\, open-ended text\, multivariate\, or structured responses) without devising new models for each specific task. To obviate the need for task-specific modeling\, we propose to model distances between labels\, rather than the labels themselves. Our models are largely agnostic to the distance function; we leave it to the requesters to specify an appropriate distance function for their given annotation task. We propose three models of annotation quality\, including a Bayesian hierarchical extension of multidimensional scaling which can be trained in an unsupervised or semi-supervised manner. Results show the generality and effectiveness of our models across diverse complex annotation tasks: sequence labeling\, translation\, syntactic parsing\, and ranking. \nHomepage: https://www.ischool.utexas.edu/~ml/. \nSpeaker Biography: Matthew Lease is an Associate Professor in the School of Information at the University of Texas at Austin\, where he is co-leading Good Systems (http://goodsystems.utexas.edu/)\, an eight-year Grand Challenge to design responsible AI technologies. In addition\, Lease is an Amazon Scholar\, working on Amazon Mechanical Turk\, SageMaker Ground Truth and Augmented Artificial Intelligence (A2I). He also worked previously at CrowdFlower. Lease received the Best Paper award at the 2016 AAAI Human Computation and Crowdsourcing conference\, as well as three early career awards for crowdsourcing (NSF\, DARPA\, IMLS). From 2011-2013\, Lease co-organized the National Institute of Standards and Technology (NIST) Text Retrieval Conference (TREC) crowdsourcing track. \n\nRSVP: https://docs.google.com/forms/d/e/1FAIpQLSegSUQnDrs6VG9Wl8BTw8xY9Yg0HN1uph8CMP2a89-cT-RKBQ/viewform
URL:https://archive.sigchi.org/event/matthew-lease-the-academic-fringe-festival/
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