Artificial intelligence Robots like Sophia may appear impressive, but do not be deceived by their humanoid appearance; these machines possess artificial intelligence akin to human emotions.
At the beginning of this month, several leading outlets spread the news that artificial intelligence will not jeopardize humanity. This reassuring news came from a consortium of chatbots linked to humanoid robot heads. Journalists were invited to question the robots, including Sophia, created by Hanson Robotics, a machine that has appeared on talk shows and even achieved citizenship in Saudi Arabia, albeit controversially.
In the midst of questioning whether AI would spell humanity’s doom or outsmart thieves, chatbot experts were able to provide responses thanks to their knowledge in the field, enabled by the powerful capabilities of ChatGPT. However, despite their renowned accomplishments, robots’ answers are autonomously generated and reflect the meaningful opinions of intelligent components.
How did this happen?
Robots capable of mimicking human expressions evoke emotional responses from spectators, as we tend to focus on such cues.
However, this oversimplification disregards the current and future risks associated with advanced AI, which ChatGPT’s cutting-edge iteration is not yet capable of handling and requires over a hundred million dollars to create. Thus, even advanced AI programs like ChatGPT and other state-of-the-art AI systems are limited to their constrained “knowledge” of the world.
Sophia’s previous artificial intelligence sometimes managed to give plausible responses, but systems like GPT-4 have not yet reached such advanced stages. While researchers, led by Ben Goertzel, a prominent artificial intelligence researcher and CEO of SingularityNET, strive to apply machine learning progress to Sophia’s software to enable responses to human speech.
While Sophia and the company’s misguided “meetings” show their ambition to create a truly intelligent system, the understanding of artificial intelligence history should serve as a sobering reminder of the potential pitfalls of surpassing human intellect.
The first machine learning system created for the U.S. Navy in 1958, a rudimentary artificial neural network by Cornell scientist Frank Rosenblatt, was covered in The New York Times during the early stages of artificial intelligence. The Times described an enticing picture of learning circuits that may mimic human-like intelligence: “Today a Navy device released electronic strains of the same voice that talks, sees, writes, reproduces itself, and recognizes its own voice with a semblance of natural grace.” Just 400 pixels are needed for pattern recognition.
If you think of IBM’s chess-playing Deep Blue, DeepMind’s champion Go player AlphaGo, and many breakthroughs of the past decade all descendants of Rosenblatt’s machine – it is clear that the pursuit of a more human-like intelligence remains an ongoing endeavor.
This doesn’t mean that the creation of projects like Sophia is insignificant or the possibility of creating even smarter machines is out of reach. However, it is crucial to pay close attention to the capabilities of this powerful technology. To understand the progress of artificial intelligence, we must refrain from asking foolish questions to anonymous Boolean circuits and instead embrace the significance of artificial intelligence’s advancement. Haltingly pondering the potential of artificial intelligence allows us to grasp its meaning.
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