Artificial intelligence (AI) is made up of data, chips or code, but also the stories and metaphors we use to represent it. Stories matter. The imagery surrounding a technology determines the way in which the public understands it and, therefore, guides its use, its design and its social impact.
That is why it is worrying that, according to the majority of studiesthe dominant representation of AI has little to do with its reality. The ubiquitous images of humanoid robots and the anthropomorphic chatbot narrative as “assistants” and artificial brains are attractive on a commercial or journalistic level, but they are based on myths that distort the essence, capabilities and limitations of current AI models.
If the way we represent AI is misleading, how will we truly understand this technology? And if we don’t understand it, how can we use it, regulate it or align it with our interests?
The myth of autonomous technology
The distorted representation of AI is part of a widespread confusion that the theorist Langdon Winner already baptized in 1977 as “autonomous technology”: the idea that machines have taken on a kind of life of their own and act on their own on society in a deterministic and often destructive way.
AI now offers the perfect embodiment of that vision, because it flirts with the myth of the creation of an intelligent and autonomous being… and the punishment derived from it. arrogate to himself that divine function. An ancient narrative pattern that goes from Frankenstein to Terminator, from Prometheus to Ex Machina.
The myth of autonomous technology is already intuited in the ambitious name of “artificial intelligence”, coined by the computer scientist John McCarthy in 1955. The term turned out to be a success even though it provoked numerous misunderstandingsor maybe thanks to that.
As Kate Crawford points out in her book AI Atlas: “AI is neither artificial nor intelligent. Rather, it exists corporeally as something material, made of natural resources, fuel, labor, infrastructure, logistics, stories and classifications.”
Most of the problems with the dominant narrative of AI can be attributed to this tendency to represent it as an independent, almost alien entity, incomprehensible and beyond our control or decisions.
Metaphors that confuse us
The language used by many media, institutions, and even experts to talk about AI is full of anthropomorphism and animism, images of robots and brains, always false stories about machines rebelling or acting inexplicably and debates about supposed consciousnessnot to mention a feeling of urgency and inevitability.
That vision culminates in the narrative that has driven the development of AI since its inception: the promise of General AI (GAI), a supposed human- or superhuman-level intelligence that will change the world or even the species. Companies like Microsoft or Open AI and technology leaders like Elon Musk have been predicting the IAG as a ever imminent milestone.
However, the truth is that the path to this technology is not clear and there is not even a consensus on whether it will ever be possible to develop it.
Story, power and bubble
The problem is not just theoretical. The deterministic and animistic vision of AI builds a certain future. The myth of autonomous technology serves to inflate expectations about AI and divert attention from the real challenges it poses, thus hindering a more informed and plural public debate about the technology. In a report reference, the AI Now Institute therefore refers to the IAG promise as “the argument to end all arguments”, a way to avoid any questioning of the technology.
In addition to a mix of exaggerated expectations and fears, these narratives are also responsible for having inflated the possible economic bubble of AI that various people warn about. information and technology leaders. If that bubble exists and ends up bursting, it will be interesting to remember that it was fueled not only by technical achievements, but also by a representation that is as shocking as it is misleading.
A narrative change
Fixing the broken narrative of AI requires foregrounding its cultural, social and political dimension. That is, leave behind the dualistic myth of autonomous technology and adopt a relational perspective that understands AI as the result of an encounter between technology and people.
In practice, this narrative change consists of shifting the focus of representation in various ways: from technology to the humans who guide it, from the techno-utopian future to a present under construction, from apocalyptic visions to present risks, from AI presented as unique and inevitable to the emphasis on autonomy, the capacity for choice and the diversity of people.
Various strategies can promote these movements. in my book Technohumanism. For a narrative and aesthetic design of artificial intelligenceI propose a series of style recommendations to escape the narrative of autonomous AI. For example, avoid your use as subject of the sentence, when it corresponds to the role of tool, or not attributing anthropomorphic verbs to it.
Playing with the term “AI” also helps to see the extent to which words can change our perception of technology. What happens when we replace it in a sentence, for example, with “complex task processing”, one of the less ambitious but more precise names that were considered to designate the discipline in its origins?
Key debates about AI, from its regulation to its impact on education or employment, will continue to rest on shaky ground until the way we represent it is corrected. Designing a story that makes visible the sociotechnical reality of AI is an urgent ethical challenge that will benefit both technology and society.
Pablo SanguinettiProfessor of AI and Critical Thinking, IE University
This article was published in The Conversation. Read the original.
