AI Today Podcast

In order to understand the goal of Artificial General Intelligence (AGI) which is also sometimes reffered to as Strong AI, it’s important to understand the difference between strong AI versus narrow or weak AI. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron...

Companies of all sizes in just about every single industry are looking to see how Artificial Intelligence (AI) and machine learning (ML) can provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous op...

The term Artificial Intelligence (AI) was coined in 1956. Despite the fact that the term is now decades old, there still is no commonly accepted definition. In this episode of the AI Today podcast, hosts Kathleen Walch and Ron Schmelzer share Cognilytica’s definition for AI.
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On the AI Today podcast we regularly interview thought leaders who are implementing AI and cognitive technology at various companies and agencies. However in this episode hosts Kathleen Walch and Ron Schmelzer interview Greg Mester who is host of the 5am Mester Scrum podcast. As ...

It’s one thing for us to talk about the Cognitive Project Management for AI (CPMAI) Methodology and the benefits it can bring to managers running AI and advanced data projects, but hearing directly how individuals are applying the CPMAI Methodology can be incredibly valuable. In ...

When putting together your Ethical and Responsible AI Framework it’s important to remember that it needs to be actually implemented. Why spend all this time and resources to put together a framework just to let it sit on a shelf untouched. Remember: Ethical & Responsible AI is so...

When working on your ethical and responsible AI framework you should not overlook the roles, boards, and committees that will need to be put in place to ensure that the framework is actually implemented and updated as needed for overall AI project success for the long term. In th...

The pace of adoption for artificial intelligence (AI) and cognitive technologies continues unabated with widespread, worldwide, rapid adoption of AI and its various patterns. However with any transformative technology laws and regulations may be slow to catch up with the quickly ...

Not all algorithms are explainable. So does that mean that it’s ok to not provide any explanation on how your AI system got to the decision it did if you’re using one of those “black box” algorithms? The answer should obviously be no. So, what do you do then when creating Ethical...

In order to have people use AI systems they need to feel that they can trust these systems. That includes putting measures in place around AI Auditability, Traceability, and System Control. But what exactly does that mean and how do you do this in the context of your Ethical and ...

When building Ethical and Responsible AI systems it’s important to think about AI System Transparency. These are ethical principles that focus on giving human users as much visibility into overall system behavior, including issues of visibility into data and AI configuration, app...

In order to have people use AI systems they need to feel that they can trust these systems. That includes when they system provides an answer they may not want to hear. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer discuss issues related to AI Tod...