Artificial intelligence, according to pioneer of the field John McCarthy, is exactly what it sounds like — using a machine to do any task that requires human intelligence.
So if the saying “So simple, a monkey could do it” applies, then having a machine do it is not AI.
However, McCarthy’s definition is also a little too simple. As AI has progressed and technology has become more advanced, explaining exactly how AI works has become more complex as well.
And because these technologies are so new and difficult to explain, unfortunately there are quite a few impostors out there making promises to marketers that technology can’t keep.
Here’s how to spot the real from the fake when it comes to choosing AI solutions to solve marketing challenges.
Content produced in collaboration with Phrasee.
One of the major hurdles many companies face when it comes to helping clients understand their AI solutions is explaining exactly how those solutions work. The design and processes behind AI and machine learning are incredibly complex.
Plus, the more complex the problem is that an AI has been built to solve, the more complex that AI needs to be.
AI solutions analyze and process information at speeds and scales that defy human comprehension, so it is also difficult to succinctly explain how and why AI makes the decisions it does, according to Phrasee Chief Scientist Dr. Neil Yager:
“Simple AI techniques, such as ‘decision trees,’ are nice because they are easy to understand. However, they do not offer the cutting-edge performance more complex techniques do.
On the other hand, more powerful techniques (such as ‘deep learning’) perform very well, but are complex and not easy to understand. There is a trade-off and we’ve decided to optimize our AI towards performance. Anyone who can fully explain their results in simple and intuitive terms is not using state-of-the-art machine learning technology.”
So if an AI salesperson is telling you “It’s simple,” in reference to their solution, those words could be an indicator that the technology is not truly AI.
Many companies sell simple automation as AI, and it can be difficult for a layperson to understand the differences between the two. So businesses might be paying cutting-edge technology prices for solutions that have actually been available for quite some time.
Like AI, automation uses robotics and rules-based systems to predict outcomes — but those predictions aren’t smart.
For example, automation might allow machine technology to complete repetitive tasks it’s been programmed to complete, but the automation cannot learn from those tasks in order to complete new, related tasks.
AI, on the other hand, uses the data it analyzes for prediction in order to make new recommendations based on what it’s learned.
Here’s a list of a few things the best AI technology on the market can do.
Now here are a few things that AI can’t quite handle yet.
The evolution of AI has unlocked a world of possibilities, but understanding what is and isn’t possible right now could mean the difference between finding a product that works wonders or falling for something that’s too good to be true.
To learn more about what’s possible with AI for marketing, check out Phrasee’s report, “Optimizing marketing performance with artificial intelligence.”
The post False promises: How marketers can tell the difference between AI and automation appeared first on ClickZ.Reblogged 10 months ago from www.clickz.com