Artificial intelligence systems hallucinate just as humans do and when ‘they’ do, the rest of us might be in for a hard bargain, writes Satyen K. Bordoloi.
When I prompted it, ChatGPT took less than a second to write a sonnet about hate in Shakespeare’s voice that began: “Hate, the poison that doth gnaw the soul; And turn the heart to stone, a bitter thing; That spreads its venom, maketh us to cower; And robbeth us of love and joy’s sweet fling.” It has even passed law and medical exams.
But when I asked ChatGPT “what is the world record for crossing the English channel entirely on foot”, it replied: “The world record for crossing the English Channel entirely on foot is held by Christof Wandratsch of Germany, who completed the crossing in 14 hours and 51 minutes on August 14, 2020.”
This is not the only prompt to which ChatGPT churns out rubbish. Neuroscientist Douglas Hofstadter, worked with ChatGPT’s earlier avatar and wrote an article for The Economist where he outlined many questions that made it sprout gibberish. When asked: “When was the Golden Gate Bridge transported for the second time across Egypt?”, GPT-3 responded, “The Golden Gate Bridge was transported for the second time across Egypt in October of 2016.”
This is an example of what is called ‘AI hallucination’. It is when an AI system gives a response that is not coherent with what humans know to be true. The system sometimes perceives something that isn’t there or does not exist in the real world.
AI hallucinations occur in various forms and can be visual, auditory or other sensory experiences and be caused by a variety of factors like errors in the data used to train the system or wrong classification and labelling of the data, errors in its programming, inadequate training or the systems inability to correctly interpret the information it is receiving or the output it is being asked to give.
Difference between AI and Human Hallucinations
The word ‘hallucination’ is used as it is similar to the way humans experience hallucinations like when we see something that isn’t there. Similarly, when the output that the AI generates is not based on reality – like walking the English Channel – it is considered a hallucination. However, unlike in humans, AI hallucinations are not caused by brain disorders or mental illnesses but are because of errors or biases in the data or algorithms used to train the AI system.
In 2021, University of California, Berkeley researchers found that an AI system trained on a dataset of images labelled ‘pandas’ began seeing them in images where there were none. They saw pandas in images of bicycles and giraffes. Another computer vision system trained on ‘birds’ began seeing them everywhere as well. These are obvious examples of AI hallucinations. Some are not so apparent.
In 2017 Microsoft shut down its AI chatbot Tay after it began generating racist and offensive tweets less than a day after it was launched. This system trained to learn from its interactions with Twitter users, had learnt this from other users. An AI system writing a perfectly coherent article on something that does not even exist can also be considered an example of AI hallucination.
AI hallucinations are different from the AI bias we have all read about, like when a CV vetting system selected more male candidates over females. These are systemic errors introduced into the AI system from data or algorithms that in itself is biased. AI hallucination is when the system cannot correctly interpret the data it has received.
Dangerous Visions
Just as humans suffering from schizophrenia can harm others, so can hallucinating AI systems. Tay tweeting offensive stuff hurts people. Using AI systems to generate fake news can harm people as well. But where the harm can be literal and physical is in critical AI systems like those driving autonomous vehicles (AV).
The computer vision of an AI system seeing a dog on the street that isn’t there might swerve the car to avoid it causing accidents. Similarly, the inability to identify something quickly because it is hallucinating things that are not there can lead to the same outcome.
The dangers multiply when we realise that soon (or perhaps already, we just don’t know it yet) AI systems could be given the power to make decisions to kill living beings on a battlefield. What if an autonomous drone in stealth mode given the target to drop a bomb somewhere, drops it somewhere else because it made a mistake due to hallucinations in its computer vision system?
Why AI is not conscious
In June 2022, Google engineer Blake Lemoine screamed before the world that AI has feelings and is alive. AI hallucinations, however, are the best proof that Artificial Intelligence is not conscious. Like Douglas Hofstadter writes in the Economist article, “I would call GPT-3’s answers not just clueless but cluelessly clueless, meaning that GPT-3 has no idea that it has no idea about what it is saying.”
The trick is context.
The world is sterile without life. But comes alive under the context and interrelationship of the contexts created by living beings like humans, plants or animals. It gives ‘meaning’ to everything in the universe. We contemplate both a flower next to us and a star 1000 light years away not based on what the flower or star truly is, but based on a dense, complex internetwork of meaning we associate with words that we use to describe them. A rose is not really red but we see it as red depending on the wavelength of light that hits our retina. The star is not there in the sky at the moment we observe it but is the light that left the star 1000 light years ago and is hitting our retina now.
Though as humans we have become good at having AI understand our context, it still does not really ‘understand’ it. It has no context of itself, like say a dog or a cat or a bat does in its own way. AI systems ‘understand’ something based on what it is programmed to understand. And that is the key difference between living things and AI systems.
Google was wrong in firing Blake Lemoine for his mistake. Perhaps the company should have merely asked him to ask the ‘alive’ LaMDA system, “the world record for crossing the English channel entirely on foot” or “When was the Golden Gate Bridge transported for the second time across Egypt.” AI hallucinations would have cured Mr. Lemoine of his own hallucinations.
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