THE AI DATA SYNDROME!

Data lies at the heart of our artificial intelligence revolution. Massive volumes of data hold the key to the analytical processes that induce artificial intelligence outcomes. Data is drawn from a wide variety of sources. Yet data are neither homogeneous, generic nor mailable! Data are amorphous whole and carry with it a myriad of problems. This could and does induce "data malfunctions" or “data syndrome” and the derived issue of data reliability. The following article addresses this issue. The article is qualitative in approach. It identified several triggers of data malignance going all the way from data deluge and data synthetics to data poisoning, data cannibalism and data multi science roots. It further identifies and analyses two prime sources of syndrome: data deluge and the multi science roots of data. The article tries to place this observed data malignance within a framework. It identifies the sources and tries to develop a conceptual framework for the phenomenon. The conclusion suggests a set of hypotheses that could be explored further.