Led by: Bradley Shimmin, Distinguished Analyst
Rapid advances in automated machine learning (AutoML), pre-built AI solutions, and an ever-growing portfolio of augmented development tools are 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? Is it secure and free from tampering? Will it continue to function as expected over time? Do stakeholders understand how the model itself arrives at a given outcome?
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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