Science fiction has a curious way of being prophetic. We can only hope that stories like «"Matrix », «Terminator », «"I", "Robot"» and others, missed the mark when they suggested that robots and computers would rebel against us and either use them as batteries or fertilizer for the plants they would crush with their robot steps.
If you're worried about the rise of machines, consider the fact that there are things humans do better than machines. A bird can even do one thing better. They might not save our species, but who knows.
10. Veery Birds are better at predicting hurricanes than cars.
Hurricane forecasting is a major undertaking. We currently rely on a variety of systems to help us determine whether a hurricane is approaching, including satellites, radars, and even ships and buoys in the oceans. Thanks to all this technology, we can predict a hurricane approximately 36–48 hours in advance.
When it comes to long-term forecasts, we have nothing better than chance. We can predict that hurricanes will arrive during hurricane season, but so what? That's like predicting the sun will rise tomorrow. For more certainty, we can turn away from computers and turn to birds. Viri have an uncanny ability to predict severe hurricane weather, as evidenced by their breeding seasons. These birds live in southern Canada and the northern United States and lay one clutch of eggs per breeding season.
In years with severe hurricane seasons, viriscans shorten their breeding seasons, even if they haven't yet succeeded. They do this several months before the start of hurricane season, but it's clear that the two are linked.
In 2018, an ornithologist predicted a particularly strong hurricane season, while meteorological data predicted the exact opposite. Weather scientists insisted it would be a mild year. Using the ACE number, which represents the accumulated energy of a cyclone, they predicted anywhere from 60, which is quite low, to a maximum of 103, which is below average.
An ornithologist who had never predicted the weather in his life suggested anywhere from 70 to as many as 150. The answer was 129. He arrived at his prediction by observing the behavior of the viri based on 20 years of observing their behavior in the wild.
9. People are excellent players, but they don't know how to work in a team.
The global gaming market is an absolute juggernaut. It's projected to be worth around $257 billion by 2027. That's Elon Musk's 93%! That kind of money has inspired countless amazing innovations in technology, including graphics and artificial intelligence. And computers aren't just lagging behind gaming; they're sometimes even outpacing it.
Artificial intelligence has proven itself to be a better gamer than the average human, even though it's a relatively recent development. But this should be taken with a grain of salt. In a strictly numbers-driven gameplay style, the computer often performs better than some guy from Idaho who keeps insulting your mother while you play Call of Duty. However, when the game becomes cooperative and requires teamwork, the AI begins to show some weaknesses. Namely, AI sucks at teamwork.
Human players often express frustration when it comes to interacting with AI teammates. A study found that an AI teammate didn't improve gameplay compared to playing with a preprogrammed computer partner, who was designed to simply know the rules and play a specific way. But the big difference was that human partners hated working with the AI. The computer was considered unreliable, unpredictable, and untrustworthy—three things you don't want in a gaming partner.
8. Computer translations are generally quite sloppy.
Have you ever stumbled upon a word or phrase in another language, then translated it online? Then you took the time to translate it back into English only to discover it was essentially gibberish? This happens because computers are incredibly bad at translation. Translation programs are notoriously bad at capturing context and other nuances of language, making computer translators simplistic at best and useless at worst.
Machines lose things like slang, cultural context, proper names, and more. Consider something like the word "set." According to the Guinness Book of World Records, this word has over 430 possible meanings. Machines need contextual cues to figure out how they'll be used in a given translation, and that's no easy task.
Idioms are usually translated literally by machines, even very advanced ones. Even individual words can change the tone of entire sentences, and this can be a challenge for AI translators. You may get the gist of the work, but that's not necessarily what you want, especially if you're reading fiction because you want a story, not just trying to distill the basic facts.
7. Collect fruits
Machines can create cars, computers, and all sorts of other things for us these days, but ironically, they struggle with some of the simpler tasks. For example, they're not very good at picking strawberries. Or many other fruits and vegetables, for that matter.
The reason for the robot's failure is too easy to guess. The robot isn't very good at judging whether it's being too rough or not. Fruits like strawberries and other berries require a light touch. The robot can probably pick nuts until the cows come home, but berries need to be handled carefully. Robotic harvesters can't tell if they're squeezing too hard and destroying the crop.
As it turns out, harvesting robots are being developed to overcome this problem by picking entire plants, not just berries. They can do the work of 30 people in the same amount of time. But for now, harvesting robots must scan fields and figure out where to go to find ripe fruit. Currently, they can only collect about 50% of ripe fruit, while humans can collect up to 90%.
6. AI is bad at reading emotions
Facial recognition technology has been in the news for years. People are wary of it because it smacks of a surveillance state and constant monitoring. But another aspect that people fear is the ability of computers to look at you and read you, essentially determining how you're feeling from moment to moment. This can be used to exploit people for marketing, advertising, and other profit-making purposes. Schools in China used it to determine how children were feeling during remote learning, ostensibly to improve the overall learning process.
The fact is, emotion-detecting computers aren't very good. Despite the claims of those selling this technology, there's little evidence that it's very effective. Neuroscientists have explicitly stated that facial expressions can't accurately assess a person's emotional state.
5. Humans are better soldiers than robots.
One of the most controversial applications of AI in the modern world is military. Should we trust machines to make life-and-death decisions in a warzone? Is it ethical to allow a robot to take a human life? It seems most people are against the idea, and the US has already assured us that humans will always make the final decision. However, some suggest that the ship has sailed, and autonomous killing machines have already been used in the field. So are robots better soldiers than humans? It depends on what you mean by better.
A machine, even an artificial intelligence, will do what it's told. Without human emotions and ethics, an artificial intelligence would likely make a different decision than Stanislav Petrov did in 1983 when he received news that the US military had launched a nuclear strike on the Soviet Union. Petrov didn't alert his government to the attack detected by his monitoring station, as required, but instead continued his investigation, determining it was a false alarm. An AI would likely do the opposite, and none of us would be here today to discuss it. They lack morality and can be unpredictable in how they process data.
Everyone from Elon Musk to Stephen Hawking has warned that AI could doom us all. That's not what a good soldier does.
4. AI has not yet mastered common sense
Most of us have encountered someone in our lives who is incredibly smart but lacks common sense. We recognize the difference. You can be a mathematical wizard but still act like an idiot. That's what AI is like. It can be incredibly smart, but it lacks common sense.
Common sense is how we describe abductive inference. It's what allows us to ignore the myriad silly explanations for things that happen in life and focus on the ones that make the most sense. If you hear a noise upstairs, you might think it's your spouse or your cat, not an elephant or Gordon Ramsay. The latter two options sound silly because you have common sense. AI doesn't, so it needs to consider them as possibilities.
Modern AI relies on symbolic logic and deep learning. These explain a lot, but they ignore common sense and are the reason why AI cannot come close to replicating real human intelligence.
3. Artificial intelligence writing programs have not yet improved human writing.
The future of writing may be captured by machines, but they're not quite ready yet. AI can write prose, especially things like journalistic articles, but it hasn't yet fully mastered the human voice.
Computers using something called GPT-3, or Generative Pre-trained Transformer 3, can generate text that almost mimics the writing of a real person. It's very good at certain types of writing, but not at others. For example, if you want it to imitate the speech of a real person, it's more likely to generate nonsense. It can easily write a fact-based article, but if you want it to imitate a Stephen King story that reads like the real King, it might seem wrong. The phrasing would be suspect, or it would need serious editing.
The flaw lies in the way the technology works. It's based on prediction and pattern matching. So, overall, it can generate general texts well. But when you need a specific text, like Stephen King, it limits the technology's ability to understand what the text is trying to convey.
2. Fulfillment of factory orders
Believe it or not, most of us would assume that a robot would perform significantly better than a human, but that's simply not the case. In a warehouse setting like Amazon's, robots aren't as good at fulfilling orders as humans.
In 2019, it was estimated that it would take at least ten years for robots to usurp human labor. Robots can pick large items for orders, but smaller items in baskets tend to get damaged and are not as efficient as when picked by humans.
Elon Musk admitted that Tesla had gone too far in automation and needed to be scaled back because humans were simply better at being flexible and dealing with inconsistencies.
1. Captchas
If there's one thing everyone on the internet knows, it's that robots can't look at nine squares and choose the ones with traffic lights. Captcha tests are a website's last defense against robot intrusion, and they use multiple layers of data, including screen size and resolution, IP address, browsers, plugins, keystrokes, and more, to determine that you are you and not a machine.
If you've noticed that these tests are getting more difficult, and those that require you to identify distorted text can sometimes even fool you, that's because robots are actually getting better at these tests, making them increasingly difficult to beat. In fact, in some tests, robots are already significantly better than humans. But we're still a step ahead with basic programs, and until we develop something better, like the various game-like tests or inkblot puzzles that have been attempted, this should be good enough.