Ask Hackaday: The Turing Test Is Dead: Long Live The Turing Test!

Alan Turing proposed a test for machine intelligence that no longer works. The idea was to have people communicate over a terminal, with another real person and with a computer. If the computer is intelligent, Turing mused, most people will incorrectly identify the computer as a human. Clearly, with the advent of modern chatbots, that test is now broken. Despite the “AI” moniker, chatbots aren’t sentient or even pre-sentient, but they certainly seem that way. An AI CEO, Mustafa Suleyman, is proposing a new test: The AI has to take a $100,000 budget and earn $1,000,000.

We were a little bemused at this. By that measure, most of us aren’t intelligent, either, and it seems like this is a particularly capitalistic idea. We could probably write an Excel script that studied mutual fund performance and pull off the same trick, given enough time for the investment to mature. Is it intelligent? No. Besides, even humans who have demonstrated they can make $1,000,000 often sell their companies and start new ones that fail. How often does the AI have to succeed before we grant it person status?

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Death Of The Turing Test In An Age Of Successful AIs

IBM has come up with an automatic debating system called Project Debater that researches a topic, presents an argument, listens to a human rebuttal and formulates its own rebuttal. But does it pass the Turing test? Or does the Turing test matter anymore?

The Turing test was first introduced in 1950, often cited as year-one for AI research. It asks, “Can machines think?”. Today we’re more interested in machines that can intelligently make restaurant recommendations, drive our car along the tedious highway to and from work, or identify the surprising looking flower we just stumbled upon. These all fit the definition of AI as a machine that can perform a task normally requiring the intelligence of a human. Though as you’ll see below, Turing’s test wasn’t even for intelligence or even for thinking, but rather to determine a test subject’s sex.

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Amazon Offers $2.5M To Make Alexa Your Friend

Amazon has unveiled the Alexa Prize, a $2.5 Million purse for the first team to turn Alexa, the voice service that powers the Amazon Echo, into a ‘socialbot’¬†capable of, “conversing coherently and engagingly with humans on popular topics for 20 minutes”.

The Alexa Prize is only open to teams from colleges or universities, with the winning team taking home $500,000 USD, with $1M awarded to the team’s college or university in the form of a research grant. Of course, the Alexa Prize grants Amazon a perpetual, irrevocable, worldwide, royalty-free license to make use of the winning socialbot.

It may be argued the Alexa Prize is a competition to have a chat bot pass a Turning Test. This is a false equivalency; the Turing Test, as originally formulated, requires a human evaluator to judge between two conversation partners, one of which is a human, one of which is a computer. Additionally, the method of communication is text-only, whereas the Alexa Prize will make use of Alexa’s Text to Speech functionality. The Alexa Prize is not a Turing Test, but only because of semantics. If you generalize the phrase, ‘Turing Test’ to mean a test of natural language conversation, the Alexa Prize is a Turing Test.

This is not the first prize offered for a computer program that is able to communicate with a human in real time using natural language. Since 1990, the Loebner Prize, cosponsored by AI god Marvin Minsky, has offered a cash prize of $100,000 (and a gold medal) to the first computer that is indistinguishable from a human in conversation. Since 1991, yearly prizes have been awarded to the computer that is most like a human as part of the competition.

For any team attempting the enormous task of developing a theory of mind and consciousness, here are a few tips: don’t use Twitter as a dataset. Microsoft tried that,¬†and their chatbot predictably turned racist. A better idea would be to copy Hackaday and our article-generating algorithm. Just use Markov chains and raspberry pi your way to arduino this drone.

A Short History Of AI, And Why It’s Heading In The Wrong Direction

Sir Winston Churchill often spoke of World War 2 as the “Wizard War”. Both the Allies and Axis powers were in a race to gain the electronic advantage over each other on the battlefield. Many technologies were born during this time – one of them being the ability to decipher coded messages. The devices that were able to achieve this feat were the precursors to the modern computer. In 1946, the US Military developed the ENIAC, or Electronic Numerical Integrator And Computer. Using over 17,000 vacuum tubes, the ENIAC was a few orders of magnitude faster than all previous electro-mechanical computers. The part that excited many scientists, however, was that it was programmable. It was the notion of a programmable computer that would give rise to the ai_05idea of artificial intelligence (AI).

As time marched forward, computers became smaller and faster. The invention of the transistor semiconductor gave rise to the microprocessor, which accelerated the development of computer programming. AI began to pick up steam, and pundits began to make grand claims of how computer intelligence would soon surpass our own. Programs like ELIZA and Blocks World fascinated the public and certainly gave the perception that when computers became faster, as they surely would in the future, they would be able to think like humans do.

But it soon became clear that this would not be the case. While these and many other AI programs were good at what they did, neither they, or their algorithms were adaptable. They were ‘smart’ at their particular task, and could even be considered intelligent judging from their behavior, but they had no understanding of the task, and didn’t hold a candle to the intellectual capabilities of even a typical lab rat, let alone a human.

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