Artificial intelligence is a moving target. Here’s how to take better aim. [Read More]
Summary… * Machine-Made
In other words, they need to understand not just where #AI can boost innovation, insight, and decision making; lead to revenue growth; and capture of efficiencies—but also where #AI can’t yet provide value.
Furthermore, as the application of #AI expands, regulatory requirements could also drive the need for more explainable #AI models.
Employing these techniques, among others, to demystify #AI decisions is expected to go a long way toward increasing the adoption of #AI.
Limitation 4: Generalizability of learningUnlike the way humans learn, #AI models have difficulty carrying their experiences from one set of circumstances to another.
But the breathtaking range of possibilities from #AI adoption suggests that the greatest constraint for #AI may be imagination.
Opinion… * Man-Made
The promise of #AI is immense, and the technologies, tools, and processes needed to fulfill that promise haven’t fully arrived. It’s time to start understanding what is happening at the #AI frontier. #Trend @Alex_Vanhuyse
Source: Mckinsey & Company