Relative to other kinds of software R&D, A.I. projects are typically expensive. Today's sage guest, Keith McCormick, details approaches for ensuring that A.I. projects not only are transparent, but that they are profitable too.

Keith:
• Is Executive Data Scientist in Residence at Pandata LLC, a consulting firm focused on transparent, human-centered A.I.
• Is predictive analytics instructor at UC Irvine.
• Has created 20 LinkedIn Learning courses on machine learning and A.I. with, in aggregate, hundreds of thousands of students.
• Authored four books, recurringly focused on statistics with SPSS Modeler.

Today’s episode should appeal to anyone who’s eager to get a return on an investment in an A.I. project, no matter whether you have technical or non-technical background.

In today’s episode, Keith details:
• His straightforward approach to ensuring that A.I. projects are successful.
• How A.I. projects need to be set up and managed in order to get a profitable return on the project.
• The corporate roles that need to be in place in order for a data science team to complete projects that drive value.
• What A.I. transparency is and how it relates to the field of Explainable A.I.
• How data scientists who have advanced software-writing skills could benefit from the use of low-code/no-code tools.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.