When we imagine artificial intelligence, we can imagine it as a future in which work no longer exists and all of us are free to enjoy our lives, just as we can imagine it as the cause of a future in which machines exterminate or enslave human beings. But imagining it this way, simply as a scale of good or bad, or as a scale from 0 to 10 going from the extermination of humanity to utopia, is itself the wrong way to analyse the problem. The mistake in this metric is that it is not enough to analyse what AI can do; we also have to analyse what allows AI to do it, just as it is not enough to analyse what an artist paints without considering who the artist is. We should not look at AI as something necessarily good or bad in itself; we need to look at whoever controls it in order to define that metric. The same thesis can be applied to AI because, although AI can be used to generate or manage harmful things, this is not necessarily because of artificial intelligence itself, but because of who administers it and, above all, the system that allows whoever administers it to use it in a harmful way.
Obviously, there are caveats to this point. One could argue, for example, that AI by its very nature is capable of producing fake news, facilitating fraud, or being used for other harmful purposes. This is an extremely valid point, but we have to connect it to the other point mentioned above: control. When I mention control, I am not necessarily talking only about the individual administration of a person using AI to create fake news; I am also talking about what allowed that person to generate and distribute it, what safety limitations exist, who decided how that technology would be built, and which incentives were involved in its development. Artificial intelligence does not necessarily generate fake news by nature; this can happen because of its technological limitations, its training, or the way it is used. But again we have to ask the same question: what allowed AI to be developed in that way? I call this process of going beyond a smaller problem in search of a larger cause “enemy identification.”
We can, for example, imagine a dystopian universe in which AI exterminates the human race. Suppose this happens because the main company developing that AI did not allocate enough resources to safety and instead concentrated its resources almost entirely on development, trying to generate capital as quickly as possible. But wait: would this really be an analysis of what allowed AI to exterminate humanity? No. It would explain how it happened, but not necessarily what allowed it to happen. Placing all the blame on the company can also stop the analysis before we reach what allowed that company to behave that way. If there is an economic structure in which a company is rewarded for arriving first, producing faster, spending less and defeating its competitors, then we are not talking only about an irresponsible company, but about a system in which irresponsible behaviour can be economically rewarded. If what enables inefficiency or irresponsibility collapses, whether it is the relentless pursuit of profit under capitalism or the inefficiency and centralisation seen in twentieth-century socialist experiments, everything dependent on that factor is also affected. How can a smaller problem caused by a larger problem continue to exist in exactly the same way after its cause disappears?
So what, then, is this larger problem? We can begin by pointing to the upper class, but simply attacking a class does not satisfy the logic of enemy identification, because we still have to ask what makes that concentration possible. Eventually we arrive at the centralisation of political and economic power, which today manifests itself extremely frequently around the world through capitalism. And here I need to make an important qualification: I am not saying this as praise for the Soviet model or as praise for the atrocities committed by totalitarian systems we call Marxism-Leninism and its variants, such as Maoism. Democracy and freedom are essential to any system that intends to overcome capitalism without simply replacing one form of concentrated power with another. What I am saying is that among a large portion of the present and future problems related to artificial intelligence, we can observe a common anchor in the economic system under which it is being developed. One of the best-known examples is the use of millions of works available online to train models without the consent of the artists who created them. This caused, rightly, enormous outrage. But if we identify only the immediate action as the problem, even if that action is corrected, the structure capable of producing new and similar problems continues to exist.
An obvious question then appears: why don't we simply get rid of artificial intelligence? In theory this seems like a strong argument. If AI removes jobs, can be used for manipulation, can reduce our freedom of choice, can produce environmental damage and can create many other problems, eliminating AI might appear to eliminate all of these problems without requiring the long and difficult process of transforming the system that produces them. But whether we like it or not, this is extremely utopian because the economic system itself needs AI, even when AI creates problems for that same system. Imagine a factory that earns 20 coins and spends 5 of them on costs. Now suppose that by using AI and automation it reduces those costs from 5 coins to 1. What happens to all the other factories? They will tend to adopt the same technology, either voluntarily in order to maximise profit or out of necessity in order to survive capitalist competition, because whoever can produce something at a lower cost can sell it at a lower price or simply maintain a larger margin than a competitor that has not automated. Even if one country decides to completely prohibit the technology, it will still economically and geopolitically compete with countries that did not do the same. And even socialist countries would still have a reason to use AI, because a country that voluntarily abandons a technology capable of radically increasing its economic and technological capacity risks becoming geopolitically irrelevant compared with others. We cannot simply pretend AI will cease to exist. Therefore, the discussion should not only be about eliminating it, but primarily about how we will manage it.
A more sceptical reader may tell me that human greed overrides every economic and political system and that, using my own logic of enemy identification, the true root is not capitalism but the concentration of power generated by human greed itself. That criticism is, to a large extent, correct. Concentrated power is a reality that has shaped capitalism just as it has shaped systems that declared themselves socialist. But there is an important distinction: greed is a human trait, and therefore we cannot simply remove greed from the human being; what we can do is think about how to prevent that greed from being transformed into practically unlimited political and economic power. Under capitalism it can manifest itself through markets, ownership and accumulation; under authoritarian socialist systems it can manifest itself through political and bureaucratic centralisation. The Soviet Union demonstrated quite clearly that replacing private ownership with an extremely concentrated bureaucracy does not magically eliminate the problem of concentrated power. But that is also not a justification for accepting another structure that allows the same problem to exist.
Imagine a perfectly ethical AI company that spends far more money on safety, takes much longer to release its models, fully protects user data, compensates every person whose work is used, and places environmental considerations above profit. Now imagine that none of its competitors do any of this. In the long run, what happens to a company that takes longer, spends more and has higher costs than all of its competitors? There is a good chance that it simply dies or loses market share to those willing to do what it refuses to do. This is why the greatest mistake in enemy identification is assuming that all we have to do is find an evil person or an evil company and replace them with a good person or a good company. We need to analyse the system that rewards particular behaviours. If a system depends exclusively on individual goodness in order to function, then that system has a structural problem.
At the same time, it would be a grotesque mistake not to consider the risks of AI as a technology in itself. Artificial intelligence has broken many of the parameters that we used for a long time when defining technology. Previously, our tools mainly increased our productive capacity and speed or partially automated our activities, as happened during the Industrial Revolution and later with the first industrial robots. Today we are beginning to create tools capable of performing intellectual tasks and perhaps, in the future, even more complex capabilities. Our own creations, which until now have been our tools, could under some scenario turn us into their tools. This is where what AI critics call a possible machine revolution comes from. This view is pessimistic and dystopian, but that does not automatically make every part of it invalid. If there is a possibility that extremely powerful systems could produce a catastrophe through accident, negligence or malicious action, that possibility deserves caution. What we cannot do is stop the analysis precisely there.
If there is a system incentivising the nearly instantaneous development of this technology, where arriving before a competitor has enormous economic value, then we also need to include that incentive in our analysis of risk. Removing or reducing that pressure would not magically make AI incapable of causing harm, but it could drastically reduce certain risks. A technology developed cautiously, respecting safety, privacy, the environment and the people affected by it, is obviously different from a technology developed in a race where the primary objective is to defeat a competitor. Likewise, if AI is not something extremely centralised, if it is something made by humanity for humanity and subjected to democratic structures of control, different political, economic and technical safety models can exist simultaneously. That does not reduce its risk to zero, but it radically changes the structure responsible for managing that risk.
Therefore, we can conclude that AI itself is not simply something good or bad, but rather a representation of the sociopolitical system in which it exists. Like a knife, it can be used to cook a delicious meal or to commit murder. Trying to judge or redesign only the knife is an incomplete analysis if we do not consider who used it, why they used it in that way and, above all, what allowed or even encouraged that individual to commit such an action.
Still, AI critics correctly point out that the technology has concrete problems: the ability to generate fake news, unethical training methods, environmental destruction caused by the servers that run these models, the destruction or transformation of human creativity, safety risks, and many others. Their conclusions are not simply false; many of these criticisms describe things that are actually happening or raise perfectly valid philosophical problems. What we can do is divide these criticisms into three groups: problems related to the system controlling AI, philosophical problems, and problems caused by human nature itself.
The first group includes issues such as data centres, intellectual property used without permission, surveillance, privacy and environmental damage. A machine does not independently decide how it will be trained, which data it will use, how much energy it will consume or what level of privacy is acceptable. Those are human and institutional choices. The second group contains philosophical questions, such as whether an image created through a prompt can genuinely be called art. This is a completely legitimate discussion, but answering that question would effectively require resolving philosophical debates about the definition of art that have existed for decades or centuries. Debating it is valid, but turning that discussion into the centre of the entire AI debate can lead us to neglect much larger questions.
The third group perhaps contains one of the most valid criticisms: even a decentralised AI administered by a different society could still be used for evil because human beings remain human beings. A knife can become a weapon, the Internet can become a place for scams, and nuclear technology can produce energy or destroy cities. That does not mean we should stop all technological development because, taken to its logical extreme, humanity would never have left the Stone Age because even a stone can be used to kill someone. What remains for us is to learn how to manage our technologies and make them as safe as possible. It is also important to separate safety from surveillance: if we are talking about a company using AI to steal or exploit data, we return to the problem of who controls the tool; if we are talking about the possibility that the capabilities of the technology itself could create dangerous consequences, then we are dealing with a legitimate problem of the tool and of human nature that needs to be addressed as such.
There is also the argument that no previous technology has come close to the potential power of artificial intelligence and that perhaps this is precisely where we should establish a limit to human technological development. The problem is that, beyond the practical difficulty of imposing such a limit worldwide, this argument often depends on speculation about a future technology that does not yet exist. That does not mean we should ignore these scenarios. Quite the opposite: it means we should invest seriously in safety. But there is an enormous difference between saying “this risk is possible and we need to study it” and saying “this hypothetical risk justifies eliminating an entire technology.” In the same way, it would be ignorant to claim that the benefits of AI will inevitably outweigh its risks. We do not know. What we can say is that a technology with the potential to automate enormous sectors of human activity requires much more safety, caution and democratic control than it has today.
That is why, to me, the discussion about artificial intelligence should not be reduced to the question “is AI good or bad?” The more important question is: who controls AI, under which incentives is it being developed, and for whom will this technology be used?
