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08:00
WELCOME & OPENING REMARKS
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DEVELOPING FAIR ML
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08:10
Increasing Trust in ML Models via Explainability
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08:35
Creating Accountable Systems
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09:00
Securing Workflows: Privacy Preserving ML & Robustness in ML
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09:25
COFFEE & NETWORKING BREAK
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FAIR ML IN PRACTICE
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09:35
Measuring Bias & Ensuring Fairness
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10:00
Data Governance & Compliance
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10:25
BREAKOUT SESSIONS: ROUNDTABLE DISCUSSIONS WITH SPEAKERS
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10:45
COFFEE & NETWORKING BREAK
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10:55
PANEL: How Can We Identify the Main Challenges & Overcome Them in Developing & Deploying Fair ML?
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11:45
MAKE CONNECTIONS: MEET WITH ATTENDEES VIRTUALLY FOR 1:1 CONVERSATIONS & GROUP DISCUSSIONS
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12:15
END OF SUMMIT