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01 Jan 2021Ended

WEBINAR - Building trust in AI outcomes

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Timings

09:00 AM - 06:00 PM
Not Verified

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Estimated Turnout

100 - 500
Delegates
Based on previous editions

Editions

Jan 2021
+1 more edition

Frequency

Bi-annual
Next edition likely in Jul 2021
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Rapid advances in automated machine learning (AutoML), pre-built AI solutions, and an ever-growing portfolio of augmented development tools are .. Read more certainly democratizing data science with the promise that impactful business outcomes lie only one or two clicks away. While this might be technically true, the automation trend brings significant challenges and outright risks. An ML model may appear accurate and operating within defined parameters, but are its decisions free from human- or data-borne bias? Is it compliant with corporate policies and government mandates? Will it continue to function as expected over time? Within this webinar, Omdia analysts will seek to equip enterprise AI practitioners with an understanding of these challenges and many other questions surrounding the creation of trustworthy AI. Attendees will come away from this webinar with insights into the rapidly evolving marketplace for AI and ML tools capable of tackling difficult objectives, such as bias identification and remediation, ML auditing, and data privacy enhancement.

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Rech Leong

Rech Leong

Research Engineer at Tuv Sud

Singapore
Jayachandra

Jayachandra

Sw at Timesya

Chittoor, India
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