Machine intelligence has been steadily progressing since the invention of the digital computer, but this progress has arguably been accelerating of late, with widespread deployment of machine learning systems and dramatically increased funding of artificial intelligence research.
Machine intelligence long surpassed human capability in numerical computation, application of algorithms, data processing, and games such as checkers and chess. In 2005-2015 dramatic improvements in image recognition and classification, speech transcription, game playing (e.g. Go and classic Atari), and automatic translation across many languages have approached or surpassed human levels. As of 2015 there is still a large gulf, however, in many intellectual capabilities. But for how long?
Assume that prior to 2040, a generalized intelligence test will be administered as follows. A team of three expert interviewers will interact with a candidate machine system (MS) and three humans (3H). The humans will be graduate students in each of physics, mathematics and computer science from one of the top 25 research universities (per some recognized list), chosen independently of the interviewers. The interviewers will electronically communicate (via text, image, spoken word, or other means) an identical series of exam questions of their choosing over a period of two hours to the MS and 3H, designed to advantage the 3H. Both MS and 3H have full access to the internet, but no party is allowed to consult additional humans, and we assume the MS is not an internet-accessible resource. The exam will be scored blindly by a disinterested third party.
Question resolves positively if the machine system outscores at least two of the three humans on such a test prior to 2040.
Note that this also effectively tests whether the internet as a whole functions as a human-level intelligence, in that a positive resolution indicates that the human participants are effectively superfluous. Resolves as ambiguous if no such tests are performed in the period 2035-2040.