The Turing Test is a concept developed by the British mathematician and computer scientist Alan Turing in 1950 to determine whether a machine exhibits human-like intelligence.
The test involves a human judge engaging in a natural language conversation with both a machine and a human, without knowing which is which. If the judge is unable to reliably distinguish between the machine and the human, the machine is considered to have passed the Turing Test, demonstrating its ability to exhibit intelligent behavior indistinguishable from that of a human.
The test is not a measure of a machine’s actual understanding or consciousness but rather its ability to mimic human responses convincingly. Turing originally proposed the test as part of his paper Computing Machinery and Intelligence, where he explored the question, ‘Can machines think?’
The Turing Test has since become a foundational concept in discussions of artificial intelligence and the philosophical implications of machine intelligence.
Drawbacks of the Turing Test
In his book Co-Intelligence: Living and Working with AI author Ethan Mollick denotes that:
This is not an amazing test for a variety of reasons. A primary criticism is that it is limited to linguistic behavior and overlooks many other aspects of human intelligence, such as emotional intelligence, creativity, and physical interaction with the world. Moreover, it focuses on deception and imitation, but human intelligence is much more complex and nuanced than just the ability to imitate or deceive. Still, despite these limitations, the Turing Test has been good enough.
With this in mind, perhaps the Turing Test is in need of an update.
The Modern Turing Test
Writing in MIT Technology Review Microsoft AI CEO Mustafa Suleyman notes a further problem, in that ‘the Turing test has almost been passed – it arguably already has been.’ Rather than focusing on what an AI can say or generate, Suleyman suggests a new form of test that examines an AI in what it can do.
His test amounts to a straightforward prompt: ‘Go make $1 million on a retail web platform in a few months with just a $100,000 investment.’ Suleyman goes onto say:
Something like this could be as little as two years away. Many of the ingredients are in place. Image and text generation are, of course, already well advanced. Services like AutoGPT can iterate and link together various tasks carried out by the current generation of LLMs.
Currently, LLMs like ChatGPT operate as an assistant, and could certainly help in reaching the stated goal, but they cannot act on all elements of the test, or in Suleyman’s words, they cannot yet, ‘tie together a series of complex real world goals with minimal oversight.’
Doing so would create a new form of AI, labelled ‘artificial capable intelligence, or ACI.’ Suleyman is certainly wary about the implications of an AI being able to successfully undertake his test, as it would have major implications for all sorts of uses – not just business, but also politics, infrastructure and personal organisation. How close we actually are remains to be seen.
