Prosper in the AI ​​era: where humans have the advantage

Artificial intelligence comes for your work. Humans will soon have to be redundant. This is what many would like to believe. The truth is that the alarmist attracts your attention, isn't it? Perfect clickbait. But such declarations believe in history lessons.

According to the quantitative researcher Toby Carrodus, resistance to new technologies is not new. When John Henry Ford presented the first affordable family car to the world, immediate reactions were disapproving. Many feared that the replacement of horses with cars will cause mass unemployment by putting stables, marshal-farms and manure. However, a new unpredictable economic ecosystem appeared around the automobile. New jobs have been created, ranging from mechanics to service stations and lacquers.

In fact, this phenomenon, known familiarly by some under the name of Fobo: “The fear of obsolescence”, was documented in the 16th century, when Queen Elizabeth, I rejected a patent for a knitting machine for fear of the impact that it would have on weaks. At its essence, Fobo is also a fear of the unknown. However, as the lessons provided by Ford, history has timeless lessons on how we can remain relevant in the era of technological change.

Interpersonal skills

Despite the rise of computers, we still share this planet with 8 billion human beings. The more you get along with people and have good relationships, the more opportunities and better chances you have in life. It is in your interest to ensure that you have the skills necessary to hear yourself with as many types of people as possible, because they are always people who debate and create laws, have found companies and buy products and services – not computers. Everything that computers do, they do for people.

Historically, we have evolved in tribes because it has ensured the greatest probability of survival. We depend on the forces of the other and benefit from the diversity of skills within the group to survive. In modern times, although our immediate tribes have become smaller, we are more likely to be members of several different “tribes” simultaneously.

If the individual members of these different tribes each have a unique set of skills, we have access to a wide range of skills and capacities that our ancestors. In their famous summary of human history, “History lessons“, Published almost 60 years ago, renowned historians Will and Ariel during noted that” men who can manage men who can only manage things “- things like computers. This lesson was as true as now.

Inspired by his long career as a quantitative analyst, Toby Carrodus notes after having observed this in the first hand, having made a great use of so -called “learning machine” techniques. A concept expressed by Carrodus is that it is often these quantitative analysts that master the relationships as well as their subject that take front. It is unlikely that computers and AI will change this.

Creativity

Another key aspect where humans prevail over AI in creativity. Let us not forget that AI is formed on the content produced by humans. Recent research shows that AI formed on the content produced by AI produces nothing more than charabia.

For example, Recent research published in Nature studied the results of a large language model (LLM) formed on the original content generated by humans compared to the content generated by AI. The researchers compared the production of the LLM formed on the content generated by humans with that produced from 9 successive iterations of the LLM model formed on its own content generated by AI after initially started with the content generated by humans.

The result? The release of the LLM model formed on its own content generated by AI was an absurd babbling that brought no semblance to reality! Researchers have concluded that the model “becomes poisoned with his own projection of reality“Become more and more disconnected with each iteration.

This augurs well for the areas that are based on our inner human capacity to create new and new concepts. Carrodus was personally it as a quantitative researcher focused on algorithmic trading models. AI models can succeed in identifying the parameter combinations that perfectly explain the past but have a minimum foreseeability for the future due to certain statistical properties (or their absence) on the markets.

Toby Carrodus explains that most algorithmic trading models that have led to an AI suffered from a lack of stability in their statistical market estimates (known as “stationarity”). A fundamental consequence of this is that the simple fact that you estimate certain statistical parameters on historical data does not mean that you can reasonably expect that these estimates remain valid when applied to future data. In addition, by adopting a statistical approach purely oriented towards data without any knowledge of the field, the real cause of an effect is often unknown.

This becomes important to understand when a perceived effect (in this case, a trading signal) can stop working. This difficulty is true for most human fields, which are characterized by social phenomena – or “complex”, where we do not have the capacity to carry out parallel experiences in parallel universes.

On the other hand, AI can be very useful for studying physical phenomena, where statistical properties such as “stationarity” are less a problem. For example, recently, Microsoft has teamed up with the Pacific Northwest National Laboratory To reduce 32 million theoretical materials to only 18 which could be used to reduce lithium consumption in batteries by 70%. Scientists must still carry out the work, but AI has helped them reduce the scope of their research and reduce the costs of carrying out such large -scale research.

That said, it should be noted that AI has demonstrated a creative capacity in the field of art, let's say. AI is able to create beautiful false images of fantastic landscapes and works of art where there is no good or bad response. But in the fields where there is a good or a bad answer, AI still depends on the content generated by man and the qualified human contribution.

Use AI to your advantage

Technology will only be part of our daily life over time. Rather than resisting it and claiming to be a victim of its ascent, it is in our interest to take it from our daily tasks as far as possible. The fears of AI in its current form consume large expanses of our working world are, in balance, exaggerated. An AI LLM always depends strongly on the human contribution on which to be formed and to interpret its exit.

By focusing on intrinsically human attributes of your work, such as creativity and interpersonal skills, you can set up to prosper at a time of AI. New jobs around the AI ​​ecosystem are already emerging, such as “fast engineers”, which are paid, well, better questions to LLM such as Chatgpt. It would therefore be wise to know how you can take advantage of these technologies and, above all, do not forget the other members of the tribe with whom you share this planet if you want to have a successful and fulfilling career.

About Toby Carrodus

Toby Carrodus is a quantitative researcher focused on algorithmic trading. He worked in Frankfurt, London, Sydney and Los Angeles for companies such as Pimco and Winton Capital. Toby Carrodus also heads stock market fund For students from socio-economic backgrounds, taking advantage of his experiences to allow the next generation of learners. Follow him Liendin,, XOr Support.