BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Venue Radar//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:ACM FAccT 2027 Calendar
BEGIN:VEVENT
UID:acm-facct-2027-deadline-abstract@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20261028T115900Z
DTEND:20261028T125900Z
SUMMARY:[Fairness & Responsible AI][Explainability & Interpretability] ACM 
 FAccT 2027 - Abstract submission deadline
DESCRIPTION:Conference title: ACM Conference on Fairness\, Accountability\,
  and Transparency\nWebsite: https://facctconference.org/\nSource URL: htt
 ps://facctconference.org/2027/cfp.html\nLocation: TBD\nTopics: Fairness &
  Responsible AI\, Explainability & Interpretability\, Ethics & Governance
 \, Privacy-preserving ML\nSize: M\nSubmission type: Paper-based / interdi
 sciplinary\nConfidence: confirmed\nLast checked date: 2026-08-20\nNotes: 
 Official FAccT 2027 call for papers lists conference dates and abstract/p
 aper submission deadlines.\nScope: Fairness\, accountability\, and transp
 arency in computing\, combining algorithmic research with sociotechnical\
 , legal\, philosophical\, and human-centered approaches. Characteristic c
 ontributions include audits and evaluation practices\, governance\, human
  experiences of systems\, and responsible development and deployment. A f
 airness or accountability question should be substantive\, not a passing 
 motivation for generic ML.\nAdditional topics: Human-AI Interaction & Dep
 loyment\, Robustness & Safety\nScope sources (2026): https://facctconfere
 nce.org/2026/cfp.html\nScope last checked: 2026-10-07
URL:https://facctconference.org/2027/cfp.html
END:VEVENT
BEGIN:VEVENT
UID:acm-facct-2027-deadline-full-paper@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20261104T115900Z
DTEND:20261104T125900Z
SUMMARY:[Fairness & Responsible AI][Explainability & Interpretability] ACM 
 FAccT 2027 - Paper submission deadline
DESCRIPTION:Conference title: ACM Conference on Fairness\, Accountability\,
  and Transparency\nWebsite: https://facctconference.org/\nSource URL: htt
 ps://facctconference.org/2027/cfp.html\nLocation: TBD\nTopics: Fairness &
  Responsible AI\, Explainability & Interpretability\, Ethics & Governance
 \, Privacy-preserving ML\nSize: M\nSubmission type: Paper-based / interdi
 sciplinary\nConfidence: confirmed\nLast checked date: 2026-08-20\nNotes: 
 Official FAccT 2027 call for papers lists conference dates and abstract/p
 aper submission deadlines.\nScope: Fairness\, accountability\, and transp
 arency in computing\, combining algorithmic research with sociotechnical\
 , legal\, philosophical\, and human-centered approaches. Characteristic c
 ontributions include audits and evaluation practices\, governance\, human
  experiences of systems\, and responsible development and deployment. A f
 airness or accountability question should be substantive\, not a passing 
 motivation for generic ML.\nAdditional topics: Human-AI Interaction & Dep
 loyment\, Robustness & Safety\nScope sources (2026): https://facctconfere
 nce.org/2026/cfp.html\nScope last checked: 2026-10-07
URL:https://facctconference.org/2027/cfp.html
END:VEVENT
BEGIN:VEVENT
UID:acm-facct-2027-conference@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270621
DTEND;VALUE=DATE:20270625
SUMMARY:[Fairness & Responsible AI][Explainability & Interpretability] ACM 
 FAccT 2027 - Conference
DESCRIPTION:Conference title: ACM Conference on Fairness\, Accountability\,
  and Transparency\nWebsite: https://facctconference.org/\nSource URL: htt
 ps://facctconference.org/2027/cfp.html\nLocation: TBD\nTopics: Fairness &
  Responsible AI\, Explainability & Interpretability\, Ethics & Governance
 \, Privacy-preserving ML\nSize: M\nSubmission type: Paper-based / interdi
 sciplinary\nConfidence: confirmed\nLast checked date: 2026-08-20\nNotes: 
 Official FAccT 2027 call for papers lists conference dates and abstract/p
 aper submission deadlines.\nScope: Fairness\, accountability\, and transp
 arency in computing\, combining algorithmic research with sociotechnical\
 , legal\, philosophical\, and human-centered approaches. Characteristic c
 ontributions include audits and evaluation practices\, governance\, human
  experiences of systems\, and responsible development and deployment. A f
 airness or accountability question should be substantive\, not a passing 
 motivation for generic ML.\nAdditional topics: Human-AI Interaction & Dep
 loyment\, Robustness & Safety\nScope sources (2026): https://facctconfere
 nce.org/2026/cfp.html\nScope last checked: 2026-10-07
URL:https://facctconference.org/2027/cfp.html
LOCATION:TBD
END:VEVENT
END:VCALENDAR