Trend 2 - Sound data gaining importance
Artificial intelligence is the ability of a computer system to learn from its environment. You probably heard the term machine learning getting bandied around. AI learns from experience and adjusts itself based on feedback from the environment or the user. In other words, reaping what we’ve sown.
Unfortunately, not all the information such a system feeds on is entirely accurate. The data used to train AI contains inaccuracies here and there. Take GenAI models like ChatGPT. Misinformation creeps in there too, both unconsciously and consciously.
Blissful ignorance?
Suppose Galileo Galilei had asked ChatGPT in the 16th century whether the earth revolves around the sun, the chatbot would have answered with a definitive no. After all, most of Galilei's contemporaries did not know any better. And AI tools tend to reinforce the general consensus, whereas a critical writer is predetermined to question everything.
Informed?
According to the World Economic Forum's (WEF) 2024 Global Risk Report, disinformation will become the biggest risk to our global society in the next two years.
In that assessment it beats the other contenders like extreme weather events, cyber insecurity, armed conflict, inflation and social polarisation. WEF experts see two main reasons: the success of populist politicians AND ... generative AI.
Of course, a combination of both - populist politicians abusing generative AI to lead people astray - is extra dramatic. Especially when you know that fake news circulates up to six times faster than real news, according to a study by the Massachusetts Institute of Technology.
Quality over quantity
Even if you are going to train your own 'customised' AI tools, it is essential that you feed your system with sound data. If you put junk in, junk will inevitably come out.
Consequently, be meticulous and strict in your role as gatekeeper: which data is allowed in, and which is not? Quantity obviously matters for training models, but quality is even more important.
Focus only on data that is both relevant and reliable, and invest in its management, because that will determine how quickly you can switch and scale up.