Many organizations are making a common mistake when it comes to AI. They fail to capitalize on the potential to enhance Customer Experiences through this powerful technology by building it incorrectly. By changing their strategic approach, they could gain a significant competitive advantage.

Take, for instance, a telecom company that developed an AI system to detect customer churn. While it successfully identified customers likely to churn, it fell short in explaining why they were leaving.

Here's the issue: AI models excel at predicting customer behavior but lack the ability to establish meaningful connections and provide context for the data. It's akin to Deep Thought from The Hitchhiker's Guide to the Galaxy revealing that the answer to life, the universe, and everything is 42. It may be a correct answer, but we're left without understanding the underlying context.

The mistake lies in how organizations set up their AI systems. The outcome resembles the ambiguous answer of 42. What we truly need is the context that explains the reasons behind it.

In this episode, we explore the mistake many organizations are making with AI and what might happen if the Flat Earthers get a hold of it. Chances are their answer will be about as useful as 42.

Here are some other key moments in the discussion:

• • 01:42  Colin kicks it off by asking how to link together The Hitchhiker’s Guide to the Galaxy, Flat Earthers, and Artificial Intelligence, and how that relates to the opportunity inherent in AI systems.
  • 09:11  We describe the difference between machine learning and deep learning under the larger umbrella of AI work, and why machine learning might have biases written into its code.
  • 14:44  Colin explains what Flat Earthers have to do with all this, and explains what they believe, suggesting that listeners watch this clip from the ABC News YouTube channel.
  • 20:08  Colin share the big danger of all this, particularly when you consider the parts of Customer Science that are coming as a new wave of change.
  • 29:16 We share our big takeaways from the discussion and how organizations would be wise to improve their AI strategy.

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