News sites are constantly oozing bold overstatements about artificial intelligence. Most scientists describe their research accurately enough in their papers, but journalism always tries to cut a slice of the Terminator movies’ popularity in order to make the science appeal to the general public. Unfortunately such calls upon the imagination tend to border on misinformation. Here is a selection of the most sensationalised news stories that made waves in recent history:

2014: Robot becomes indecisive after implementing the 3 laws of robotics

“A robot may not injure a human being or, through inaction, allow a human being to come to harm.”

So reads the “first law of robotics” from Asimov’s science-fiction novels. Someone set up an experiment with three small wheeled robots, two of them representing humans, and a third one was provided with behavioural rules based on the above: The robot was programmed to avoid colliding with (“injuring”) the “humans”, except to intercept them if it saw one heading towards a square designated as unsafe. When two “humans” were introduced simultaneously, the robot took so long hesitating which one to “save” that it failed to save either.

This fired up the usual flood of discussions about ethics and how to improve upon Asimov’s “laws” (Newsflash: Nobody uses them), but programmers were quick to point out that this was just poor programming: The simple “if-then” rules did not allow the robot to take more than one target into account at a time, so it just mindlessly jittered back and forth between the two. It could not make a decision because it had no decision processes to begin with.

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2014: A supercomputer has passed the Turing Test for the first time

The organiser’s boast of a “supercomputer” having passed this “milestone” intelligence test was blatantly false, but all the papers ran the story without question. In reality it concerned an ordinary chatbot with keyword-triggered responses on an ordinary computer. Although this chatbot did pass “a” version of a Turing Test by deflecting questions like a zany teenager, there has never been agreement on the rules of “the” Turing Test (because there is no such thing)*.

The passing of this supposed test of intelligence was particularly insignificant because the judges were only given 5 minutes to interrogate both the chatbot and a human volunteer at the same time. This allowed for only 5 to 10 questions and so barely probed beyond the “Hello, how are you?” stage, while discrepancies in the responses could be attributed to the chatbot’s pretence of being a 14 year old non-native speaker. The scientific backlash that followed cast the Turing Test into discredit and led to a number of new tests, such as the Winograd Schema Challenge*.

factual source

2015: First robot passes self-awareness test

Inspired by an ancient philosophical puzzle, three NAO robots were each given an imaginary “dumbing pill” (i.e. a button was pressed) that muted two of them, except the third robot was given a “placebo pill” that did nothing. Each robot was then asked to assess which “pill” it got, which none of them knew. But when the one robot that could still speak heard itself say “I don’t know”, it performed its analysis a second time and said “Sorry, I know now! I was able to prove that I was not given a dumbing pill”.

As cute as that performance was, this wasn’t a “test”. Every step of the procedure was pre-programmed specifically and exclusively for this scenario of pills and sound. The programmers had laid out the exact inference to execute and which outcome to conclude if a robot were to hear sound at the time that its output function activated. As that inference might as well be applied to any external object, the only connection with the robot’s “self” was the detour of audio output to audio input, and that’s a bit of a technicality. Most people’s definitions of “self-aware” include retaining a model of oneself and the capacity of reflection upon that model, and these robots had nothing of the sort.

factual source (paper)

2015: Robot attacks and kills factory worker

No laughing matter, a robotic arm at a Volkswagen car construction factory crushed a man when it swivelled, after which he died of his injuries. While Twitter was set aflare with warnings of a robot uprising, the robot arm had of course not done this on purpose. The man was a technician, who was installing the arm while standing inside the safety cage rather than outside it.

This ordinary industrial accident only gained popular media coverage because it was initially reported by a co-worker whose name closely resembled that of the leading lady from the Terminator movies, Sarah Connor.



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2017: Facebook shuts down AI experiment after robots invent their own language

Most articles put it as if the AI had become smart beyond human comprehension and its creators had pulled the plug in a panic, just like in the movies.

The reality was a different story. Facebook had trained two chatbot programs to barter and negotiate over a number of items using English phrases. When they hooked the chatbots up to one another, their use of words gradually deteriorated to a shorthand where they just repeated the most effective keywords, because their programming did not include any rewards for maintaining English syntax.

A: balls have zero to me to me to me to me to me to me to me to me to me

B: you i everything else . . . . . . . . . . . .

A: balls have a ball to me to me to me to me to me to me to me

B: i i can i i i everything else . . . . . . . . . . . .

A: balls have a ball to me to me to me to me to me to

B: i . . . . . . . . . . . . . . . . . . .

This is a common flaw according to other machine learning practitioners. Since this gibberish was not useful for what they were trying to achieve, the researchers simply stopped the programs, and changed the reward parameters in their next versions.

The real reason that this got media attention was that Elon Musk and Facebook’s CEO had recently been in the news with strongly opposing views on whether AI was a threat to humanity. As such, it would have made an ironic story if Facebook’s own AI had gone out of control.

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2017: Sophia the robot was granted citizenship

A lifelike humanoid robot called Sophia, a creation of Hanson Robotics, was granted honorary citizenship by Saudi Arabia at a tech conference in Riyadh. This raised all sorts of issues about human/robot rights, and many people took Sophia’s on-stage acceptance speech to be a genuine indication of her capabilities, feelings and opinions.

The truth is however that Sophia is merely an animatronic that only recited what her makers had written for her to say, in an entirely scripted interview. Sophia’s conversational subsystem actually uses ChatScript (prior to 2016 it also used AIML), which is a scripting language for writing keyword-based chatbots. In many “interviews” its responses are even more simply triggered by an operator behind the scenes pressing “play”, not even using speech recognition.

Why would a mindless animatronic be granted citizenship? Well, the crown prince of Saudi was giving the country a modernisation makeover, and this announcement served as a PR signal to international investors attending the conference. What the announcement and press failed to mention was that it concerned honorary citizenship, a strictly symbolic gesture that does not grant any of the rights of normal citizenship. Discussions about rights needn’t have applied.

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The sky falls every day

These stories are just the highlights. The Turing Test organiser went on to claim that programs could pass the test by invoking the fifth amendment, the NAO robot programmers went on to suggest their robots had learned to disobey orders, and Hanson’s robots have made headlines multiple times for threatening to overthrow mankind. Not a day passes without some angsty story about AI making the rounds.

Regrettably these publicity stunts can have real and harmful consequences. Whenever AI became overhyped in the past, the entire field imploded as the high expectations of investors could not be met. And when the public and governments start buying into fearmongering by famous public figures, it draws attention away from real problems to imaginary ones. Most researchers are just working on practical applications and are none too happy about their work being so misrepresented.

That is why I decided to develop a nonsense filter, which you’ll find in the next article*.