655: AI ROI: How to get a profitable return on an AI-project investment

<p>Transparent data science, profitable AI, and what’s missing from a data science education: Pandata’s Data Scientist in Residence Keith McCormick and Jon Krohn discuss how “insights” can never be the end product of a data science project, how to ensure you have a specific goal at the start of a project that is related to revenue, and why there is so much miscommunication between data scientists and their clients. Exclude the C-suite at your peril!<br/><br/>This episode is brought to you by Glean (<a href='https://glean.io/'>glean.io</a>), the platform for data insights, fast. Interested in sponsoring a SuperDataScience Podcast episode? Visit <a href='https://www.jonkrohn.com/podcast'>JonKrohn.com/podcast</a> for sponsorship information.<br/><br/>In this episode you will learn:<br/>• What an Executive Data Scientist in Residence is [05:27]<br/>• What A.I. transparency is and how it relates to the field of Explainable A.I. (XAI) [17:34]<br/>• How companies can ensure they profit from AI projects [36:47]<br/>• Possible organization structures for data science teams to be profitable [1:02:41]<br/>• The current gaps in data science education [1:09:58]</p><p>Additional materials: <a href='https://gate.sc/?url=http%3A%2F%2Fwww.superdatascience.com%2F655&amp;token=35b7c1-1-1676970707102'>www.superdatascience.com/655</a></p>