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BEGIN:VEVENT
DTSTAMP:20260611T163029Z
DTSTART;VALUE=DATE-TIME:20180201T160000
DTEND;VALUE=DATE-TIME:20180201T170000
SUMMARY:Dr. Ansgar Koene: Algorithmic Bias Considerations – societal impa
 cts and regulatory responses
TZID:Europe/London
UID:20180201-8a17841b612d07210161416b7dd65c97@warwick.ac.uk
CREATED:20180129T101659Z
DESCRIPTION:Despite warnings about Bias in Computer Systems going back to
  at least 1992\, it has taken concerted efforts by groups of researchers
  like FAT/ML (Fairness\, Accountability and Transparency in Machine Lear
 ning) and news and media reports highlighting discriminatory effects in 
 data driven algorithms (e.g. recidivism prediction) to dispel the naïve-
 optimistic myth that the logic/mathematics of computation would automati
 cally results in objectively unbiased outcomes. Starting from a brief ov
 erview of key challenges in the design and use of data driven algorithmi
 c decision making systems I will focus in on the inherently socio-techni
 cal nature of real-world applications that give rise to concerns about b
 ias. I will present some of the findings of the UnBias project on the li
 ved experience and concerns of teenaged digital natives regarding their 
 interactions with algorithmically mediated services and discuss the ongo
 ing work of the IEEE P7003 working group for developing a “Standard for 
 Algorithmic Bias Considerations”. I will conclude with a review of some 
 of the policy making initiatives that were recently launched by professi
 onal associations (e.g. ACM principles\; IEEE Global Initiative on Ethic
 al Considerations in AI and Autonomous Systems)\, industry led organizat
 ions (e.g. Partnership on AI) and regional/national government bodies (e
 .g. EC Algorithmic Awareness Building\; TransAlgo in France\; UK parliam
 entary inquiries).
LOCATION:CS101
CATEGORIES:
LAST-MODIFIED:20180129T101659Z
ORGANIZER;CN=Sara Kalvala:
END:VEVENT
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