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Data Science Fails: Building AI You Can Trust

Any organization that is considering adopting AI must first be willing to trust in AI technology. They must feel confident that human error did not inadvertently contribute to AI bias that resulted in inaccurate findings.

Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. 


Gain insights including: 
• How to watch for bias in AI
• Why your organization’s values should be built into your AI
• How human errors can influence AI findings
• The optimal level of disclosure to AI stakeholders

Data Science Fails: Building AI You Can Trust