From Intelligent to Wise Machines: Why a Poem Is Worth More Than 1 Million Tweets

Abstract

In recent years, the interest in artificial intelligence and big data has grown exponentially, and the amount of data produced every day is truly staggering. Data are considered to be the “new oil” making algorithms capable of delivering meaningful information, which makes them more “intelligent.” In this position paper, we review the DIKW pyramid model, shedding a new light on each component. In particular, examining the engineering point of view, we focus on the definition of information, giving it a new conceptual structure. If tradition has always considered information as data-bearing meaning, in this paper, we argue that information is not meaningful. In fact, from the analysis of Shannon’s studies in communication engineering, we highlight how the notion of meaning is not necessary for the definition of information. It follows that we need to explore other paths in order to find a sustainable conceptual theory able to provide a new insight. Therefore, we show how it will not only be necessary to carry out a semiotic revolution to be able to introduce meaning into the communicative act, but it is also necessary to introduce the figure of an interpreting agent. Thanks to the interaction between such interpretative acts, which take place in conscious freedom à la Eco, cultural units emerge. Thus, we should address part of today’s research into new forms of data in order to facilitate a semiotic revolution. In particular, digital humanities and cultural heritage can funnel a new type of data for which semiotic representativeness has a greater degree of quality. Knowledge and wisdom are the next steps to truly craft intelligent machines.