Matters Arising from Early Turing Tests
Kevin Warwick, Huma Shah · Cambridge University Press eBooks · 2016
As we already mentioned, to realise Turing's tests is, in the opinion of Hayes and Ford (1995), harmful to the science of AI. We contest this position and feel it is a dereliction of the duty of science whose remit should not be to avoid difficult goals or to appease the sceptical. Science should pursue innovation and advance technology for the benefit of humanity. If realising Turing's two tests of imitation, deception and intelligence can help us ascertain what does and does not fool people, thus improving deception detection, then this cannot be contrary to the goals of good science. Especially as many researchers (including Block, Pinker, and Shieber) have pointed out and others (Colby et al., Heiser et al., Weizenbaum) have demonstrated through experiments that some intelligent humans are gullible. The current climate of increasing cybercrime sees opportunists turning to innovative means of defrauding people – stealing their identity, swindling funds – including using text-based chatting across the Internet. So now is a very good time to engineer virtuous artificial conversationalists to counter the attack from malware such as CyberLover . In this chapter we look at some of the common arguments over the Turing test and early Turing test implementations, considering the key questions of duration, knowledge, memory, cultural bias. We begin by asking what if anything is actually being measured. What is being measured? Is it intelligence or a type of human intelligence being measured in a Turing test? Turing (1950) believed a sustained level of answering any questions was sufficient to assess a machine's performance in thinking at a satisfactory level . But what then is thinking? To Moor (2004) it is information processing in ways which involve recognition, imagination, evaluation and decision. For Baum (2004) semantics is the concern of thought equivalent to capturing and exploiting the compact structure of the world. Demchenko and Veselov (2008) ask if the proven ability to think shortens the distance between machines and humankind. For a machine to succeed at providing sustained satisfactory responses in an imitation game these comments imply that a machine would necessarily be able to process information with the sophistication of a normal, living adult human being; that is, the machine must be a consummate actor.