BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CFP.DEV//CFP.DEV shortcodes//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Voxxed Days Zürich 2026
X-WR-RELCALID:c426493a-54d4-472b-b975-6f3aaa7163fa
X-WR-TIMEZONE:Europe/Brussels
BEGIN:VEVENT
UID:cfp-1151-13600@cfp.dev
DTSTAMP:20261005T213123Z
SEQUENCE:0
STATUS:CONFIRMED
DTSTART:20260324T081500Z
DTEND:20260324T085000Z
SUMMARY:The Promise of Trustworthy AI
DESCRIPTION:Teams building with AI are often presented with a false choice:
  share data to get frontier models\, or protect privacy and accept weaker 
 results. It is a convenient story\, especially for anyone who benefits fro
 m accessing your data\, but it is not the full story.This session introduc
 es a counterintuitive paradigm where AI models can improve without ever co
 llecting your raw data\, and where organizations can collaborate without g
 iving up control. By combining Federated Learning\, the idea of training l
 ocally while learning globally\, with cryptographic computation on encrypt
 ed updates using Homomorphic Encryption\, the result is a system that trea
 ts privacy not as a policy or a feature\, but as a structural property by 
 design.Through practical examples\, this session explores why centralized 
 training creates hidden constraints like security exposure\, compliance fr
 iction\, and data gravity that limit real-world adoption. You will learn h
 ow Federated Learning flips the classic “bring data to the code” appro
 ach\, and how Fully Homomorphic Encryption closes the final subtle leak: w
 hat model updates can reveal\, even when your valuable data never leaves y
 our yard.\nSpeakers: César Soto Valero\nTrack: Machine Learning & AI
URL:https://vdz26.voxxeddays.ch/talk/the-promise-of-trustworthy-ai/
LOCATION:Room 4\nARENA Cinemas\, Sihlcity\nZürich\, Switzerland
CATEGORIES:Machine Learning & AI
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