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The risks of the generative AI gold rush

FUTURES

WE EXPLORE THE TRENDS AND TECHNOLOGIES THAT ARE SET TO SHAPE THE FUTURE

The backlash didn’t take long. OpenAI released the latest version of its ChatGPT in the autumn of 2022, and within weeks startups were taking advantage of the generative AI tool and the large language model that powers it. In 2022 alone, $1.4 billion was reportedly invested in generative AI companies in 78 deals (futurism.com/deep-learning-expertgpt-startups-rude-awakening).

But warnings about the technology arose just as quickly. First, people didn’t understand the text was grammatically correct but not necessarily factual; that’s not a flaw but how these systems inherently work, although that was apparently news to many (indeed, ChatGPT itself warns that it “may occasionally generate incorrect information”, can be biased and has limited knowledge after 2021).

Critics also raised concerns about the ownership and quality of the data on which the models were trained, wondering where future data sets could be sourced. Then came the hackers and researchers, trying to find the edges of the controls for the systems, in order to break them.

Those shaking the most with fear over AI advancements weren’t regulators or ethicists but search incumbents. Google and Microsoft both launched their own generative AI chatbots, rushing out products to avoid being left behind. Google immediately raised eyebrows – and slashed eight percent from

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