At the 2024 Paris Olympics, an “A.I.” demonstration area was constructed to get children involved and show what sports they may excel at based on their performance in certain physical activities. While this is a creative use case for A.I., it exposes a flaw in how companies and organizations attempt to “sell” A.I. to the general public.
In an age where a CEO simply mentioning the word A.I. in shareholder meetings can cause a stock price to rocket upward, there is a general lack of understanding of what Artificial Intelligence can do and how it can affect organizations. Like all new technologies, there is a cloud of excitement surrounding A.I., a cloud that creates an elusive or mysterious feeling in the general public. Though people are excited about A.I., they aren’t entirely sure what it is. This poses a challenging task for companies working on such systems; they must both stoke excitement in the public and limit expectations as the infancy of A.I. takes shape. If expectations are too high and the product falls short, then investments and adoption will plummet, and the product won’t be able to improve. However, investments will be challenging to field if insufficient initial excitement exists, and the product will never get off the ground.
That said, demonstrations, such as the one at the Olympics, must be conducted carefully so as not to overpromise the system’s capability. The last line of the linked article is as follows, “It seems even with AI technology, computers cannot get it right every time.” This sentiment expresses the expectation that A.I. was supposed to be a new technology that fixed the flaws of modern computer capabilities. This was never the case; nonetheless, it was the general public’s expectation. Moving forward, organizations need to better express the true capability of current A.I. systems in realistic terms while cautiously and explicitly discussing what A.I. systems may be able to do in the future. By correctly balancing expectations and reality, the large-scale adoption of practical A.I. systems that benefit the specific use-case of organizations will allow for their better development in the future.
