FILE PHOTO: ChatGPT talks about generative AI’s impact on future communication. 

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Generative AI is ready to break through societal network barriers, facilitating the seamless integration and collaborative utilization of public and private domain resources. Since the inception of the Internet, the vast majority of accessible resources have been in the public domain. However, a lot of resources, often surpassing the volume of public domain resources, is stored in the private domain. Notably, generative AI possesses the capability to not only retrieve public domain resources but also professionally integrate and leverage private domain resources through user interaction. By curating a comprehensive dataset that aggregates public and private domain resources, it contributes to a more extensive and profound consolidation of existing human knowledge, culminating in an “omniscient” intelligent hub.”

Next-generation internet gateway

Generative AI has the potential to become the “next-generation internet gateway” and evolve into a “super media.” It is a social “infrastructure,” integrating functions like information retrieval, intelligent services, chatbots, and creative tools. This positions generative AI as the gateway for the next generation of the internet and is likely to elevate itself into an unprecedented “super media.” 

Generative AI seamlessly integrates into all aspects of human practices, injecting “human-centric” relationships and value elements into text generation through deep learning. This enhances the structural value of text expression, making users more engaged and comprehending in communication. Through continuous dialogue, it constructs the user’s cognitive process, becoming a force capable of influencing user cognition, surpassing traditional media’s communication effects.

The media is shifting from labor-intensive to technology-intensive and capital-intensive. It significantly enhances the efficiency and quality of traditional media processes, marking a qualitative leap. All communication elements are tightly integrated with new technologies. The immense productivity unleashed by intelligent technologies is poised to create a new form of “oligopoly,” enhancing the control of generative AI and technological oligopolies over critical social nodes. As generative AI becomes a ubiquitous “enhancement tool” for human intelligence, the institutions behind this technology may become core nodes connecting social resources, influencing social structures and raising concerns about the hegemony of capital over social politics.

Enhancing tool

Generative AI serves as an “enhancement” technology for human intelligence, narrowing the gap in capabilities and empowering the general public. It initiates a shift in human-machine relationships from “machines as extensions of humans” to “collaboration and mutual construction between humans and machines.” This revolution involves transforming the relationship from machines being extensions of humans to collaboration and mutual construction. As generative AI evolves into an intelligent entity with subjectivity, it becomes a crucial node for humans to establish value connections with the external world. Collaboration with generative AI will be commonplace, and the interaction between humans and AI will grow closer, making generative AI an indispensable intermediary for human practices and external connections. This collaborative ability will become a key capability in the human world.

Engaging with generative AI enables rapid acquisition of new knowledge, experiences, and skills, facilitating efficient task completion in social practices. The emphasis on skill operations and knowledge education will shift towards interacting with large models on a higher dimension. Human-machine collaborative capabilities will play an increasingly vital role in shaping human abilities and will be a crucial aspect of the evolution of post-human civilizations.

Generative AI’s most significant disruption to human society lies in enhancing equality in intellectual abilities, narrowing the capability gap between individuals. This allows ordinary people to significantly enhance in their capabilities, such as translation and programming skills. It enables them to effectively overcome “ability gap” barriers, activating and mobilizing vast external resources according to their preferences, resulting in powerful and rich social expression and value creation capabilities. This signifies another significant enlightenment for society in the era of digitization and intelligence, rejuvenating societal vitality and highlighting the governance and collaboration characteristics of the digital civilization era.

Generative AI, with its boundless knowledge construction and continuous dialogue, expands individuals’ “macro-perception” and cognition. By providing knowledge  beyond their original cognitive scope, it enables users to break through limitations. This represents a deep empowerment in perception and meaningful connections, allowing individuals to enter new circles and connect with new things without the need for new information as a mediator. The public now enjoys more equal opportunities and rights in content innovation, communication, and participation in dialogues. This aligns with the rights construction of the “distributed society” in the era of digital civilization and represents an initial step in asserting communication rights as the “first right.”

Revolutionizing, democratizing

Generative AI is transforming and opening up computer programming for everyone. In the past, only professionals had the exclusive right to create algorithms, but now generative AI makes this capability available to anyone. It generates effective computer code based on user needs, creating a new dimension of machine-intelligently generated content. Just as social platforms in the Web 2.0 era gave everyone a “voice” online, today’s Web 3.0 era sees generative AI empowering everyone with code-writing abilities. This enables users to leverage resources, possess digital creative capabilities, and engage in more freedom-oriented practices in the digital space.

As an intermediary tool for all human practices, the democratization of algorithms means that every user has the opportunity to access the digital civilization society and share the corresponding benefits. 

Generative AI will become the central hub for the next generation of the internet, transitioning from “information connectivity” to “relationship connectivity” and then to “intelligent connectivity,” thereby upgrading and iterating the connectivity paradigm.

Generative AI will also shorten the hierarchical levels of communication in human society and enhance efficiency. The core capability of media lies in its intermediacy, and the theory of “intermediacy” suggests that an individual’s centrality on the internet depends on the extent to which they participate in the chain of information transmission. Generative AI aggregates information from countless source nodes in social networks and performs generative value assessments and push notifications for each node’s information. Leveraging vast user data, content data, and transmission chain data, generative AI will become the central hub with strong intermediacy in the next generation of the internet.

As the number of users approaches a certain threshold, the structure of the communication network will shift from the layered and diffused “onion-style” structure to more of a “starfish-style” structure, where the majority of nodes are directly connected to the hub. This new structure will significantly compress the hierarchical levels of information dissemination, enhance the efficiency of communication, and greatly improve the dissemination of innovative information. This, in turn, reduces the loss of information at various communication stages, thereby exerting a powerful influence on the overall nature and efficiency of internet connectivity.

Generative AI will drive the form of societal interconnection from the “relationship connectivity” of mobile interconnection to the more finely grained “value connectivity” of intelligent interconnection. Based on the granularity of connectivity, the transformation of media-driven connectivity can roughly be divided into three stages.

The first stage is the PC Interconnection Era. Societal connections constructed during the PC Interconnection Era were rather rudimentary. This is reflected in the perception of individuals as static entities, rather than dynamic individuals with various needs continuously transitioning between different scenes. Connectivity  could only achieve coarse-grained, simple connections, addressing the question of “whether to connect.”

The second stage is the Mobile Interconnection Era. The Mobile Interconnection Era aimed to solve the challenge of connecting mainstream characteristics with mainstream values.

The third stage is the Intelligent Interconnection Era. Generative AI, as the connecting entrance and central hub, addresses two crucial issues: first, it personalizes users and reduces the marginal cost of meeting their long-tail demands to infinitesimal levels, thereby creating broader connectivity possibilities; second, with its unprecedented ability to identify individualized elements, simulate human cognition, and provide targeted outputs, generative AI fulfills the external value connection of individuals’ more detailed endogenous needs. In the context of mobile interconnection, the two ends of the connection are essentially treated as “black boxes,” where all connections are identified and matched solely based on the mainstream features of the two ends, without recognizing the concrete structures and inherent mechanisms of the connected parties. The revolutionary nature of Generative AI’s large models, with their human cognitive simulation mechanism, opens the “black box,” breaking down the barriers between internal and external relationships. It deconstructs, reorganizes, and reconnects more subtle and complex structural elements. The Intelligent Interconnection Era addresses the “connection of subtle features and subtle values.”

The role of mainstream media is undergoing a transformation. Once a “value leader” with substantial influence, mainstream media is now evolving into an organizer of future “emergence” phenomena in the “distributed society.” Mainstream media must  leverage synergy theory, chaos theory, hypercycle theory, fractal theory, etc., within the framework of dissipative structures, to participate in the “reorganization” of new social communication.

The functions and role positioning of mainstream media are shifting further towards a Business-to-Business model. Traditionally operating in a Consumer-to-Consumer model, mainstream media is now evolving in to a “To B” model, taking on roles such as the “soul-giver,” responsible for pre-training large model rules and logic, and the “prompt engineer,” standing between large models and users. It acts as a supporter of the value logic and professional rules of generative AI’s large models, an explorer of innovation and creation, and a balancer and corrector of discourse fields. Mainstream media thus becomes a “cornerstone” and “stabilizing force” in the communication field of society as a whole.

Emphasis is placed on creating and maintaining mechanisms that promote ethical considerations in intelligent algorithm models. The societal implementation of any technology is essentially the result of the “co-construction” between technological logic and social choices. We should establish societal supplements for “algorithm malfunction” and intervention mechanisms for “algorithm deviation.” Algorithms are not infallible, and in areas where computational power is insufficient, algorithms have no solutions, or data is lacking, there should be sufficient deployment of human and material resources. This ensures a good match and complementarity with the intelligent society. When the logic of intelligent algorithms crosses ethical boundaries, such as with “Asimov’s Three Laws,” we should have effective means and mechanisms for intervention and prevention. 

Yu Guoming (professor) and Su Jianwei (Ph.D. candidate) are from the School of Journalism and Communication of the Beijing Normal University.

Edited by WENG RONG