By Betsy Burton
Are We Turning Off Our Brains in Favor of AI?
We had a very interesting discussion today in the Aragon Research meeting that got me thinking about how much have we (or should we be) depending on information from emerging artificial intelligence services when we know we all have some data quality flaws.
And, more importantly, are we teaching ourselves to turn off our brains in favor of AI technologies doing our thinking for us?
In this blog, we explore the impact of depending on emerging information technology too much and remind ourselves that the definition of artificial intelligence calls for humans to remain engaged in decision-making.
The Case of The Wrongful Arrest
There was some news a year or so ago about a young man, Ousmane Bah, who is suing Apple for being falsely implicated and arrested for stealing from Apple stores in Delaware, New Jersey, and Manhattan.
It turns out that Artificial Intelligence-enabled facial recognition system had incorrectly identified him as the perpetrator of a shoplifting crime spree at Apple Stores.
As a result, Mr. Bah was arrested in the middle of the night. However, when the police went to compare the surveillance footage image of the actual perpetrator with Mr. Bah’s image, they looked nothing alike.
Putting Too Much Faith in Artificial Intelligence
What detectives believe happened is that the actual perpetrator used Mr. Bah’s previously lost drivers permit, that did not have a photograph on it, at an Apple Store. As a result, the perpetrator’s image was wrongly linked to Mr. Bah’s identity; the source of the information was compromised.
The real problem though is that Apple’s security firm and the police trusted the facial recognition system so much, that they failed to take a moment to have a real person double check the identities to ensure they matched before doing a 4 a.m. arrest, which resulted in months of legal issues and stress for Mr. Bah.
Garbage In, Garbage Out
As a former database person, I have always believed that there is no such thing as perfect data/information. And, in fact, the more humans and Artificial Intelligence systems can change it, the more it is used to create new views, and the further the data is from the source, the dirtier it potentially gets.
In fact, it is worse than just “garbage in, results in garbage out.” It’s more like, garbage in, result in more garbage created, learned and then generating more garbage to be learned and generated again and again.
Whatever data you use to teach and input into artificial intelligence systems must be good data, or you risk creating exponentially more issues.
The value of information analytics, predictive analytics, artificial intelligence, digital twins, etc, are all dependent on a lot of information. And in fact, when these systems are based on good algorithms, they will often do consistency checking to double-check their own analysis.
Bottom Line
Artificial Intelligence-enabled technologies will increasingly assume some routine and complex tasks and provide valuable insights and advice.
However, this does not mean that we humans can or should turn our brains off—especially when it comes to the security, and well-being of lives, the environment and economies.
Mastering 2024 and Beyond with Aragon’s Exclusive Predictions
Join Us LIVE on Thursday, September 21, 2023 at 10 AM PT | 1 PM ET
Join us on Thursday, September 21st, for exclusive early access to Aragon Research’s predictions for 2024 and beyond. These impactful and actionable predictions are essential for your strategic and operational planning for the upcoming years; crush your goals, and surpass your competitors.
