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.

中文翻译：

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从智能机器到智能机器：为什么一首诗价值超过一百万条推文

近年来，人们对人工智能和大数据的兴趣成倍增长，每天产生的数据量确实惊人。数据被认为是能够传递有意义的信息的“新石油”算法，从而使它们更加“智能”。在本立场文件中，我们回顾了DIKW金字塔模型，为每个组件赋予了新的亮点。特别是从工程角度来看，我们专注于信息的定义，赋予它新的概念结构。如果传统一直将信息视为具有数据意义的含义，那么在本文中，我们认为信息是没有意义的。实际上，通过对Shannon的通信工程研究的分析，我们强调了意义的概念对于信息的定义是不必要的。因此，我们需要探索其他途径，以找到能够提供新见解的可持续概念理论。因此，我们展示了不仅需要进行符号革命以将意义引入交际行为，而且还必须引入解释者的形象。由于这种解释性行为，这发生在有意识的自由之间的相互作用点菜生态，文化单位应运而生。因此，为了促进符号学革命，我们应该解决当今对新型数据形式的研究的一部分。尤其是，数字人文和文化遗产可以为符号学代表质量更高的新型数据提供渠道。知识和智慧是真正制造智能机器的下一步。