Beyond Artificial Intelligence: The Disappearing Human-Machine Divide (Topics in Intelligent Engineering and Informatics)
Format: PDF / Kindle (mobi) / ePub
This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.
Artificial Dreams epitomize our controversial quest for non-biological intelligence and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.
While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which is often uncritically praised, or hypocritically condemned. And so this phenomenon found its place in the subtitle of the whole volume as well as in the title of the chapter of Kevin Warwick, one of the keynote speakers at “Beyond AI: Artificial Dreams”.
This metaphor tells us simply that the engineer works with the precisely defined entities while evolution does not know anything like that and builds on what is at hand and also spontaneously. Engineering or cybernetic model of the human mind is historically linked with the notion that the essence of human thinking is logical operations with the given symbols. In modern terminology this position is called cognitivism: 1 By the biological evolution we generally mean the process of these essential
reabsorption of serotonin, a neurotransmitter crucially involved in mood, thereby making more of it available to stimulate receptors. SSRIs also seem to make subjects more fair-minded and willing to cooperate. Tse and Bond  had subjects play the Dictator game – a game in which a dictator decides how a certain sum of money is to be divided between him or her and another participant – and found that subjects administered the SSRI citalopram divided the sum more fairly than controls. Conversely,
people have with advertising, brands and media. According to Aﬀectiva, “Aﬀdex reads emotional states such as surprise, dislike and attention from facial expressions using a webcam. It employs advanced computer vision and machine learning techniques to recognise and automate the analysis of tacit expressions, and it applies scientific methods to interpret viewers’ emotional responses quickly and at scale”.3 A comparable technology that could alert an agent to others’ micro-expressions relating to,
from between the lines and sometimes against author’s postulates, since only together they fully answer a question of the worldview of the given author – and, to a degree, the culture(s) he lives in. Quoting a ˙ Polish philosopher Ryszard Zarowski, the author of the Shield of Aristotle: the crucial element of an in-depth analysis is “not to be wiser than one’s guide for an adequately long time” . 3 River of Gods: The World Let us start the main part of this paper by brief introduction of
Assessment Methods The purpose of this paper is not only to assess the accuracy and reliability of some of the AI predictions that have already been made. The purpose is to start building a ‘toolbox’ of assessment methods that can be used more generally, applying them to current and future predictions. 3.1 Extracting Verifiable Predictions The focus of this paper is squarely on the behaviour of AI. This is not a philosophical point; we are not making the logical positivist argument that only