BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//WordPress - MECv7.34.1//EN
X-ORIGINAL-URL:https://datasciences.utoronto.ca/
X-WR-CALNAME:DSI
X-WR-CALDESC:A hub for data science activity at the University of Toronto.
X-WR-TIMEZONE:America/Toronto
BEGIN:VTIMEZONE
TZID:America/Toronto
X-LIC-LOCATION:America/Toronto
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T030000
RRULE:FREQ=YEARLY;BYMONTH=03;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T010000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-PUBLISHED-TTL:PT1H
X-MS-OLK-FORCEINSPECTOROPEN:TRUE
BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-d18f655c3fce66ca401d5f38b48c89af@datasciences.utoronto.ca
DTSTART;TZID=America/Toronto:20211220T171500
DTEND;TZID=America/Toronto:20211220T181500
DTSTAMP:20210616T193619Z
CREATED:20210616
LAST-MODIFIED:20220805
PRIORITY:5
SEQUENCE:0
TRANSP:OPAQUE
SUMMARY:Data Sciences Speaker Series at UofT: Deborah Raji
DESCRIPTION:\nJoin us for the next installment of the Data Science Speaker Series at U of T with:\n\n\n\n \nDeborah RajiThe Mozilla Foundation\n\n\n\n \nFree Event | Registration Required\n\n\n\n \nTalk Title: The Challenges of Audits, Accountability & Algorithmic Justice\n\n\n\n \nAbstract: As its popularity and proliferation increase, AI products are slowly and surely making their way into our everyday lives. However, as its use becomes widespread, we continue to encounter harmful failures that are becoming increasingly difficult to tolerate – and hold decision makers accountable for. In this talk, rather than discussing the solutions to these harms, I hope to shed some light on the complex nature of the problems we face with current large-scale algorithmic deployments, and the unique challenges of ensuring accountability and algorithmic justice, for the benefit and protection of those impacted.\n\n\n\n \nSpeaker Profile: Deborah is a Mozilla fellow, interested in algorithmic auditing. She also works closely with the Algorithmic Justice League initiative to highlight bias in deployed AI products. She has also worked with Google’s Ethical AI team and been a research fellow at the Partnership on AI and AI Now Institute at New York University working on various projects to operationalize ethical considerations in ML engineering practice. Recently, she was named to Forbes 30 Under 30 and MIT Tech Review 35 Under 35 Innovators.
URL:https://datasciences.utoronto.ca/event/dsss_at_uoft_deborah_raji/
ORGANIZER;CN=Esther Berzunza:MAILTO:esther.berzunza@utoronto.ca
CATEGORIES:DSSS@ U of T - 2021-2022 Season,DSSS@U of T
LOCATION:Online (Zoom)
ATTACH;FMTTYPE=image/jpeg:https://datasciences.utoronto.ca/wp-content/uploads/2021/06/Deb_Raji_3x2-scaled.jpg
END:VEVENT
END:VCALENDAR