Can AI predict the future? 5 things we know now

Artificial intelligence has certainly made a huge difference in the world, especially in recent years. But everything comes with its limitations and strengths, the larger question is can AI predict the future? Can it provide a forecast of possible outcomes? AI for some is where science and technology collide, but is it that authentic?
Here are 5 things we know

The validity of AI predictions is a function of the quality of data upon which they are trained. The predictions will also be defective if training data is biased, incomplete, or outdated. For example, when historical data reflect social injustices, algorithms used in hiring and law enforcement have proved to be biased. For trustworthy AI forecasting, ethical, high-quality data must be ensured.

AI produces probabilistic forecasts as compared to humans, who often take guesses. For example, based on risk factors and prevailing health trends, a predictive model might suggest that a patient has an 85% chance of developing diabetes in five years. Business planning, insurance, and healthcare all make heavy use of this kind of forecasting.

AI is a pattern recognition master. It can recognise patterns and make educated guesses by studying vast amounts of past and present data. For instance, financial markets, sports prediction, weather prediction, and even consumer behaviour all rely heavily on AI models. These models extrapolate from what has happened before rather than predict what will happen in the future.

In predictive areas, artificial intelligence is found to be extremely useful in some regions. AI can predict when a machine is likely to break down in predictive maintenance, thus saving time and money. AI models used in medicine have high accuracy in predicting the growth of a disease or the deterioration of a patient. Such predictions are generally made on well-organised data and are short-term.

Although AI is very good at recognising patterns in historical data, it is not very good at predicting unusual or unexpected occurrences. These are random occurrences that AI has had no previous instances to evaluate, such as natural disasters, economic recessions, or global pandemics. AI cannot accurately predict such random occurrences because they are outside the realm of even the most sophisticated algorithms.