Artificial intelligence , define correlation or causation , a very important difference
Artificial intelligence stems from a concept invented by Alan Turing during his work with The Bomb , an early computer , in World War II. Needless to say, there are many aspects of today’s AI. However, most of them are driven by various features and math formulas.
Ultimately, I mean data fields ,are the primary drivers of AI and the concept of correlation or causation . In essence, they are represented in the graph by a line pointing upward or down a trend , if you involve two features , let’s say, in the same general direction of the other arrow, and, there is another arrow adjacent to it in the same general direction up or down that can be interpreted either as correlation or causation, This is important in all fields , meaning that just because two things are happening and going in the same direction , or trend , they are correlated, but it’s does not mean one is causing the other , this is critical to understand , as a sidenote we have made this mistake in history and science many times.
Of course this is another reason to base your science on standardized verified , human curated, information not just raw data ,or data, manipulated by algorithms to make them, conform to a model usable by AI. As you see from the diagram , including melting ice cream, it’s not the cause of a sunburn it is simply correlated.
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