Schrodinger’s Automation in AI and the Automation Bias

Posted on by Jen Stirrup
Automation and AI

Automation is one way in which we can have human-centered Artificial Intelligence. It can relieve us from repetitive and mundane tasks so that we can make the most of our human skills and talents. That said, we may have to use those human skills and talents as a check on Artificial Intelligence and its outcomes, or perhaps to solve the problems that appear when we don't open the box. We can be said to have an Automation Bias, where we assume that technology just works.

New Year’s Resolutions for your Business Intelligence, Data Science and Artificial Intelligence teams

Posted on by Jen Stirrup

What are your New Year's Resolutions for your Business Intelligence, Data Science and AI teams? Check out this post for recommendations on getting ahead for the New Year. I'll share some New Year Resolutions that I think Business Intelligence, Data Engineering, Artificial Intelligence and Data Science teams start doing from today.

AzureML and CRISP-DM – a Framework to help the Business Intelligence professional move to AI

Posted on by Jen Stirrup

Azure ML can become a part of the data ecosystem in an organization, but this requires a mindshift from working with Business Intelligence to more advanced analytics. How can we can adopt a mindshift from Business Intelligence to advanced analytics using Azure ML? Although CRISP-DM is not perfect, the CRISP-DM framework offers a pathway for machine learning using AzureML.