Can AI really pass the Turing test?
In an essay published in the 1950s, the mathematician and computer pioneer Alan Turing proposed the Turing test. It has become one of the most important milestones in the research and development of artificial intelligence.
The Turing test is the first step in determining whether a machine can detect human intelligence by engaging in a conversation with a human. The test examines whether humans can tell if they are talking to a machine or a human.
Not long ago, Google demonstrated the first time that a computer has entered into a natural conversation with a human, using the latest AI tech. The program, known as Eugene Goostman, is the first artificial intelligence to pass the test, originally developed by 20th-century mathematician Alan Turing.
The machine was tasked with persuading 30 human interrogators of its humanity, communicating with them via a series of five-minute keyboard conversations.
During a live demonstration at Reading University, the computer convinced multiple human judges that it was in fact a 13-year-old Ukrainian boy, not a machine. This stunt made the algorithm the first ever computer to pass the famous Turing test — successfully convincing over a third of the jury of its humanity. Today, Eugene Goostman stands as one of five supercomputers to have beaten the famous test.
The Reading University test was similar in its original form to the Turing test: an interrogator sent a text message to a human computer and received a reply. But some artificial intelligence experts dispute Eugene Goostman’s win, suggesting the competition has been weighted in favour of the chatbot. Others, however, disagree.
For many researchers, the question of whether or not a computer can pass the Turing test has become irrelevant. Instead of focusing on how to convince someone to talk to a human, rather than the computer program, our real focus should be on how to make human-computer interaction as smooth as possible.
So, it looks like today’s AI algorithms can pass the Turing test, but the real question is, could you? Or better yet, did you?
For those who haven’t clocked on yet, the above blog post was entirely generated by a machine, being both researched and written by an AI algorithm.
When AI meets PR
Personally, I’d like to think it doesn’t quite match up to my usual standard of writing — or the general standards of the Wildfire blog — but as a fun experiment, it’s interesting to see what today’s AI is capable of.
While this has been an interesting experiment, there is a serious point to be made here. AI copywriting is here to stay, and the technology behind it is getting better every day. AI content generation will soon be a fundamental part of marketing automation, martech, adtech and even social media tools.
For the tech brands developing these tools, AI copywriting has serious marketing potential. Not only as a point of interest for journalists and industry influencers, but also a great source of data for wider marketing campaigns.
Want to learn more about how your AI data can be used to build brand awareness and drive leads? Check out Wildfire’s AI-powered insights campaign for Emarsys. Using AI data, we helped Emarsys deliver over 150 pieces of news coverage, building awareness for its role as a leader in martech, retail and AI.