BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM ESC - ECPv6.17.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:UM ESC
X-ORIGINAL-URL:https://esc.umich.edu
X-WR-CALDESC:Events for UM ESC
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20211015T103000
DTEND;TZID=America/Detroit:20211015T160000
DTSTAMP:20211015T142833Z
CREATED:20211015T142121Z
LAST-MODIFIED:20211015T142833Z
UID:2352-1634293800-1634313600@esc.umich.edu
SUMMARY:Building Equitable Ecologies of Artificial Intelligence and Machine Learning
DESCRIPTION:Building Equitable Ecologies of Artificial Intelligence and Machine Learning\nOctober 15\, 2021 10:30am-4:00pm\, Hybrid\n\n\n \nBig Data and Artificial Intelligence (AI) have become a major force that impacts our daily lives in essential ways\, from how political messaging and marketing are designed\, to automating the process of deciding who gets hired or which neighborhood should be intensely patrolled. Big Data and AI can be an important agent for social justice and equality; or they can also be used to perpetuate injustice and hurt populations that are already disadvantaged and marginalized. Artists have been at the fore­front\, together with scientists\, in explor­ing ways in which AI sys­tems can be more equi­table\, trans­par­ent and inclu­sive. This mini–symposium brings lead­ing voices in the field together\, and is inspired by two projects at U-M: \nStephanie Dinkins: On Love & Data\, the first survey exhibition of this prominent transmedia artist whose work creates platforms for dialogue about AI as it intersects race\, gender\, aging and future histories. This exhibit is organized by Stamps Gallery\, Penny W. Stamps School of Art & Design\, from August 27 to October 23\, 2021 and generously supported by the Andy Warhol Foundation for the Visual Arts. \n\nFair Representation in Arts and in Data\, a collaboration between data scientists\, artists and museum curators and funded by the U-M President’s Arts Initiative\, the project team uses facial recognition technology to consider both the limitations of racial representation within UMMA’s collection and the limitations of the technology itself. The results culminate in an exhibit\, “White Cube / Black Box”\, which will open at U-M Museum of Art on October 16\, 2021.\n\n\n \nPROGRAM\nOctober 15 \n10:30am  Opening Remarks – Zoom \n10:40-noon  Stephanie Dinkins\, Keynote and Q&A – Zoom \n12:30-1:45  Art\, Machine Learning and Data Justice Panel Discussion – Zoom \nSophia Brueckner\nAssociate Professor\, Stamps School of Art & Design \nH.V. Jagadish\nDirector\, Michigan Institute for Data Science \nDiana Nucera (Mother Cyborg)\nArtist\, Founder and Director of the Equitable Internet Initiative \nSrimoyee Mitra [Moderator] Director\, Stamps Gallery\, U-M \n\n2:30-4:00 Data Science and Machine Learn­ing for Artists work­shop\nU-M Museum of Art\, 525 S State St\, Ann Arbor \nThis will be a non-technical exploration of methods and possibilities for the use of data science and machine learning in the arts. We will cover a few of the ways that creative works can be viewed as data\, and consider how methods for learning from data can be used to advance creation and insight in the arts.  Students pursuing degrees at all levels in any field of arts are especially encouraged to attend. No prior exposure to data science or machine learning is expected. \nKerby Shed­den\,\nDirector\, Consulting for Statistics\, Computing\, and Analytics Research; Pro­fes­sor of Sta­tis­tics\, U-M \n\nGo to https://midas.umich.edu/art-data-science-mini-symposium/ to register and learn more.
URL:https://esc.umich.edu/event/building-equitable-ecologies-of-artificial-intelligence-and-machine-learning/
END:VEVENT
END:VCALENDAR