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DTSTART;TZID=America/New_York:20260924T173000
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DESCRIPTION:"Engineering Data You Can Trust: Synthetic Data and the Hidden 
 Privacy Failures in Enterprise AI."\n\nEnterprise AI systems depend on lar
 ge volumes of rich data\, and much of that data is personal and regulated.
  This session looks at how organizations are resolving that tension with s
 ynthetic data\, which is artificially generated data that preserves the st
 atistical patterns of real data without copying any real record. Participa
 nts will see what synthetic data actually is\, how it is generated\, and w
 here enterprises are using it today\, including software testing\, AI mode
 l training\, analytics\, and safe data sharing. The session also explains 
 why traditional masking and anonymization fall short\, and then follows a 
 single piece of data through a modern AI pipeline to show where privacy qu
 ietly breaks\, including training data memorization and the collapse of co
 nsent boundaries in foundation models. It closes with the practical contro
 ls and governance steps that keep these systems trustworthy. Attendees wil
 l leave with a clear understanding of how synthetic data works\, where it 
 fits in an enterprise AI strategy\, and what questions to ask of any AI sy
 stem that touches personal data.\n\nSpeaker(s): Harshavardhan Peddireddy\n
 \nRoom: Voltage Room\, March First Brewing & Distilling\, 7885 E Kemper Rd
 \, Cincinnati\, Ohio\, United States\, 45249
LOCATION:Room: Voltage Room\, March First Brewing & Distilling\, 7885 E Kem
 per Rd\, Cincinnati\, Ohio\, United States\, 45249
ORGANIZER:dave@arcflashbrokerage.com
SEQUENCE:9
SUMMARY:IEEE Cincinnati September 2026 Meeting
URL;VALUE=URI:https://events.vtools.ieee.org/m/568122
X-ALT-DESC:Description: <br /><p><span data-olk-copy-source="MessageBody">"
 Engineering Data You Can Trust: Synthetic Data and the Hidden Privacy Fail
 ures in Enterprise AI."</span></p>\n<p>Enterprise AI systems depend on lar
 ge volumes of rich data\, and much of that data is personal and regulated.
  This session looks at how organizations are resolving that tension with s
 ynthetic data\, which is artificially generated data that preserves the st
 atistical patterns of real data without copying any real record. Participa
 nts will see what synthetic data actually is\, how it is generated\, and w
 here enterprises are using it today\, including software testing\, AI mode
 l training\, analytics\, and safe data sharing. The session also explains 
 why traditional masking and anonymization fall short\, and then follows a 
 single piece of data through a modern AI pipeline to show where privacy qu
 ietly breaks\, including training data memorization and the collapse of co
 nsent boundaries in foundation models. It closes with the practical contro
 ls and governance steps that keep these systems trustworthy. Attendees wil
 l leave with a clear understanding of how synthetic data works\, where it 
 fits in an enterprise AI strategy\, and what questions to ask of any AI sy
 stem that touches personal data.</p>
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