AI Intervention and the Paradox of Media Content Reproduction and Human Creativity

Dr. Hassan Bashir, Professor and Head of the Governance Discourse Analysis Think Tank

The emergence of artificial intelligence generation models and large language models in various fields of the media industry can be seen as an emergence beyond a technological improvement in the use of media content writing and editing tools. The emergence of the mentioned models should be seen as indicating a "cognitive and structural turn" and "a fundamental transformation" in the communication ecosystem in general and especially in the field of media.

The media, both in the traditional way and in the form of mass media, were always formed on the basis of human agency and based on a kind of gatekeeping management of media content, especially news content, and also based on semantic creativity. The world of media has faced a fundamental change in the current situation. Media is now faced with a non-human agent that has a high capacity for scalability, personalization and automation of content. In this new situation, the paradox of media content reproduction and creativity has been created as an "unwanted thing" in the communication space, the main factor of which is artificial intelligence.

In this situation, artificial intelligence, as an "assistive and accelerating tool", has created a kind of "human-machine pseudo-agency" that has caused the media space to experience the "paradox of man versus machine".

It can be said that in the initial stages and even in the decades after that, computer algorithms in the field of media content were only responsible for a few basic tasks, which included, for example: classification, surface editing and content distribution. The emergence of artificial intelligence, especially "multimodal artificial intelligence", has assumed a very sensitive and important role in this field, which can be considered as "meaning production", which is far more extensive than the mere production of content. In other words, if at the beginning of mediaization, the content and the meaning of the content were created and discussed by humans, now with the advent of artificial intelligence, the production of the desired meaning, without human agency, is created and discussed by artificial intelligence. In this situation, man has become strongly dependent on the produced meaning.

Artificial intelligence automatic editorials, convergent multimodal production of media that simultaneously includes text, image, sound, movement, etc., and finally personalization of content based on the analysis of each user's behavioral data at an unimaginable speed, has changed the basic concept of "journalist" and in fact "writer/author" from an effective, knowledgeable and creative subject, to a "prompt writer engineer" who can access different contents with different meanings by changing the direction of the prompt. find and publish.

Despite the paradox created between the reproduction of media content and creativity and the reduction of the human presence in content production and the emergence of a powerful competitor called "artificial intelligence" that creates different meanings for any social action in different societies with the speed of content production and redefinition, and it can be considered a negative challenge in relation to human power and meaning-making, but this situation cannot be completely considered an anti-human challenge in "denying the power of creativity". In this field, we can also mention positive works. Improving the efficiency and speed of the news production cycle, the democratization of multimedia production, and the creation of data-oriented journalism that relies on big data and the targeted exploitation of these data can be seen as positive effects of artificial intelligence, along with human creativity, which has promoted "news richness".

Of course, despite these positive effects, it is necessary to point out some weaknesses of artificial intelligence in the current situation, until the creation of smarter and superior versions. One of the basic problems in this field is "multiplication of statistical illusion". Many statistics of artificial intelligence and even the resources used by it require "verification". Here, we can see the role of the "human factor" to what extent it can use its reality and intellectual and research power along with artificial intelligence data and move the content from "truth-telling erosion" to "truth becoming more powerful".

Justified standardization, cultural-intellectual uniformity and reproduction are some of the basic problems of artificial intelligence. Based on the information and different algorithms that it uses, artificial intelligence does not have the ability to distinguish "right" from "false" or "truth" from "reality". On this basis, it tries to standardize, which can be a fundamental factor for human decision-making, which prepares the ground for "forced acceptance" with exploits that are loaded with various information, and here lies the fundamental danger, according to which "human agency" suffers a fundamental weakness.

In the same context, it can be said that in the hegemony of artificial intelligence and to the exclusion of "human agency", "public opinion engineering" will simply take place with the same standardizations and desired biases and based on big data fed into artificial intelligence. In this context, deep fakes will lead societies to a "semantic crisis" whose direct and indirect effects are not yet well known.

Based on this, the future of man can be described as a "human-artificial intelligence-linked symbiosis" is emerging in the new conditions, which not only makes "content production" a fundamental challenge and an important transformation, but also has turned the concept of "gatekeeping" into "gatekeeping" in which the user is responsible for the production of various contents more than the media owners and has imposed the role of "accountability" on those media owners.

In the end, it can be said that the intervention of artificial intelligence in the production of media content has put the media situation in a "historical twist" that is not unlike the time of the "invention of printing" or the "emergence of the Internet/Web". Artificial intelligence can produce content from big data that is not known to what extent it adheres to "social obligations", "cultural conditions", "moral conscience" and "religious principles". And this issue is the most important paradox and challenge between humans and artificial intelligence, which requires redefining the role of humans in this special critical situation from being a "content producer at any cost" and turning it into a "guardian of truth and meaning", which requires serious attention from every reporter or user to every content producer.