By now, all of us have heard and read a lot about artificial intelligence (AI). You’ve likely used some of the countless AI tools that are becoming available. For some, AI feels like a magic wand that predicts the future.
But AI is not perfect. A supermarket meal planner in Aotearoa New Zealand gave customers poisonous recipes, a New York City chatbot advised people to break the law, and Google’s AI Overview is telling people to eat rocks.
At its core, an AI tool is a particular system that addresses a particular problem. With any AI system, we should match our expectations to its abilities – and many of those come down to how the AI was built.
Let’s explore some inherent shortcomings of AI systems.
One of the inherent issues for all AI systems is that they are not 100% accurate in real-world settings. For example, a predictive AI system will be trained using data points from the past.
If the AI then comes across something new – not similar to anything in the training data – it most likely won’t be able to make the correct decision.
As a hypothetical example, let’s take a military plane equipped with an AI-powered autopilot system. This system will function thanks to its training “knowledge base”. But an AI really isn’t a magic wand, it’s just mathematical computations. An adversary could create obstacles the plane AI cannot “see” because they are not in the training data, leading to potentially catastrophic consequences.
Unfortunately, there is not much we can do about this problem apart from trying to train the AI for all possible circumstances that we know of. This can sometimes be an insurmountable task.
Let’s take the example of an AI system trained to predict the likelihood a given individual will commit a crime. If the crime data used for training the system mostly contains people from group A (say, a particular ethnicity) and very few from group B, the system won’t learn about both groups equally.
As a result, its predictions for group A will make it seem these people are more likely to commit crimes compared to people from group B.
As (future) users of AI and technology, it is important for all of us to be aware of these issues to broaden our perspective on AI and its prediction outcomes concerning different aspects of our lives.
Source : Business World
