Recently, artificial intelligence (AI) technologies, including generative neural networks, have become more and more widespread among the general public. One of the most advanced and widely known examples is ChatGPT, which is based on the GPT-3.5 architecture, which allows it to process and parse natural language and provide precise and often surprising answers to a variety of questions. ChatGPT can be used in many areas including education, healthcare, banking, and many more.
Despite all its capabilities, and contrary to numerous remarks on the Internet, ChatGPT, like any other “smart program”, cannot completely replace a person in his workplace. In this article, we will discuss why human labor will remain relevant.
History and causes
Let’s start with the fact that back in the days of the USSR, they were quite seriously talking about “replacing people with robots” (yes, in plain text). Here are some videos to prove it. Several decades have passed, but people are still needed, moreover, in many areas, there is a shortage of qualified specialists (eg Germany). Why is it so? It would seem that now each of us carries in his pocket a knowledge base about everything in the world, which fits into our smartphone. There are several reasons for this:
- The cost of innovation. The introduction of technologies that partially replace people in the business process is costly. In times of crisis, the costs of innovation are reduced, and some do not provide for such at all, so the need for human labor at such times only increases.
- Economic justification. When innovations have already been created and there is a clear understanding of how to implement them, dry numbers come into play. The capitalist, in pursuit of the goal of raising the rate of profit, replaces human labor with a machine only when the machine ultimately costs less. The economic justification is calculated for a specific task in a certain type of entrepreneurial activity.
- Human labor cannot be completely replaced by definition. In the process of production, a new value is created precisely by human labor, because. he is able at a given moment of time not only to create his own value (labor power) but also to create surplus value, which passes to the capitalist. Let’s dwell on this point in more detail.
How it works in an ideal world
If everything is clear with the first two reasons – the cost of innovation and economic justification can be calculated, then with the third reason it is somewhat more difficult. No machine can work completely autonomously. Suppose we replaced the only copywriter from an imaginary marketing agency with ChatGPT, what do we get? To make ChatGPT work, she needs to write a specific instruction in the natural language, the so-called “prompt”(English prompt). Next, the text or picture generated by the generative model must be checked for usability.
In the case of a text, all facts and statements must be checked for truth. OpenAI, by the way, does not hide the fact that “ChatGPT may give inaccurate information about people, places, or facts.” Naturally, for the above tasks, a person is still required. Let’s say that in our imaginary marketing agency, there was not one copywriter, but three. Then, due to the introduction of ChatGPT, it may be possible to cut one, or maybe even two copywriters. However, the remaining copywriter number 3 will have to work for three, albeit doing less of the “dirty” work of writing the text, but the tasks of post-editing, as well as proofreading of texts, will noticeably increase.
Support
Each introduced innovation requires support. If you have implemented a conditional “1C” in your enterprise, you need to at least set it up, pay for a subscription. And, if necessary, pay a consultant who will help you figure out how to work with the system. The same is true for ChatGPT and other AI products. Undoubtedly, more and more jobs will be created in the direction of AI consulting. Therefore, the very copywriters who were fired from our marketing agency can easily become domain experts in AI consulting. Thus, the “total mass” of jobs in our imaginary world has maintained its balance.
What’s actually going on
A significant number of studies have established that there is a correlation between the amount of innovation and unemployment. The more they “optimize” business processes, the fewer jobs there are. Probably based on these results, with the start of the ChatGPT hype. There were a lot of opinions about replacing humans with AI and calls for a halt to research.
In opposition to this trend, an information campaign was created called “AI will not replace you. A person using AI will”. Its essence is to motivate people to use and adapt AI in their daily work. Since those who know how to use such things will be more productive and attractive to the employer. Clearly, this campaign appeals to AI developers and consultants.
There is another opinion that the introduction of AI. Like other innovations, on the one hand, provokes a reduction in the number of jobs requiring low and medium qualifications. And on the other hand, an increase in the number of jobs with high qualifications. To be more precise, it is not so much the qualifications that are growing, but the level of skills: roughly speaking, to create a website, you do not need to be able to write machine code, it is enough to be able to use an online constructor.
Conclusion
Over the past 100 years, there have been several changes in technological patterns, and therefore several waves of innovation. However, there is no tendency to increase the average unemployment rate (at least if you look at the statistics).
I dare to assume that even during the current wave of innovations the global picture will not change quantitatively. Only the structure of jobs will change. quality component.