"Next, artificial intelligence will provide you with voice services..." Readers in front of the screen should be familiar with this phrase. Although products around us have long been labeled as intelligent and human-like, artificial intelligence has suddenly appeared in every aspect of our lives. Even now, when we make phone calls for errands or inquiries, the communication we receive is handled by AI. Objectively speaking, artificial intelligence is constantly bringing us convenience, but is it all truly beneficial? The answer is probably no.
Artificial intelligence (AI) can be simply understood as enabling computers to simulate human thought processes and interact with us using human logic. This makes AI a computer science built upon multiple technologies, including computer languages, internet development, big data statistics, and logical reasoning. The process of building AI is essentially a process of storing data and constructing a logical framework—simply put, a process of "learning."
Furthermore, because the current application of artificial intelligence involves an interactive element, it also involves the "cognitive" process of AI. For example, when AI answers a call, it first needs to recognize the other party's language, then analyze its content, and finally convert the result into audio to be played back to the other party. This "cognitive" process may seem simple, but the underlying technology is extremely complex.
It is precisely because of the diverse needs that artificial intelligence is considered a challenging science, and because it involves some ethical issues, relevant departments have even issued the "New Generation Artificial Intelligence Ethical Code." And it is precisely because of this complexity that while artificial intelligence brings convenience to society, it also generates pressure.
The technological and economic pressures behind big data
Artificial intelligence relies on big data, and society generates new "content" every day. This "content" is recorded in big data, and AI must then continue to "learn" from it. This learning process involves considerable computation. Although our current computer technology can still handle it, as data increases, the relationships between data become increasingly complex. The computational load will multiply when computers construct these "data-result connections," so perhaps one day in the not-too-distant future, computers will be unable to withstand this massive computational burden and will crash.
The only solutions to this problem might be to increase the amount of computing equipment or improve existing computer technology, but either way, both would involve huge costs and long technology development cycles.
Algorithms are "killing" people's interest
Besides the pressure on technology, artificial intelligence also puts pressure on human development. Humans are also part of big data computation, and when we encounter AI, we find it consistently delivers content that interests us precisely. On the surface, this does bring convenience, but it also stifles our opportunities to experience new things. In other words, if AI doesn't further optimize its logic, one day we will lose the chance to experience new things.
Therefore, the popularization of artificial intelligence actually represents a much longer development path.
