While the alignment community is frantically trying to convince themselves of the possibility of benevolent artificial superintelligence, the human cognition research remains undeservedly neglected. Modern AI models are predominantly based on neural-networks, which is the so-called connectionist approach in cognitive architecture studies. But in the beginning, the symbolic approach was more popular because of the lesser computational demands. Logic programming was the means to imbue the system with the programmer’s intelligence. Although symbolist AI researchers have studied the work of the human brain, their research was driven by attempts to reproduce the work of the brain, to create an artificial personality, rather than help programmers expressing their thoughts. The user’s ergonomics were largely ignored. Logic programming languages aimed to be the closest representation of the programmer’s thoughts. But they failed at being practically convenient. As a result, nobody is using vanilla logic programming for practical means. In contrast to that, my research is driven by ergonomics and attempts to synchronize with the user’s thinking. For example, while proving a theorem (creating an algorithm), instead of manually composing plain texts of sophisticated language, the user sees the current context and chooses the next step from available options.
While the alignment community is frantically trying to convince themselves of the possibility of benevolent artificial superintelligence, the human cognition research remains undeservedly neglected.
Modern AI models are predominantly based on neural-networks, which is the so-called connectionist approach in cognitive architecture studies. But in the beginning, the symbolic approach was more popular because of the lesser computational demands. Logic programming was the means to imbue the system with the programmer’s intelligence.
Although symbolist AI researchers have studied the work of the human brain, their research was driven by attempts to reproduce the work of the brain, to create an artificial personality, rather than help programmers expressing their thoughts. The user’s ergonomics were largely ignored. Logic programming languages aimed to be the closest representation of the programmer’s thoughts. But they failed at being practically convenient. As a result, nobody is using vanilla logic programming for practical means.
In contrast to that, my research is driven by ergonomics and attempts to synchronize with the user’s thinking. For example, while proving a theorem (creating an algorithm), instead of manually composing plain texts of sophisticated language, the user sees the current context and chooses the next step from available options.