1. Introduction

In today's deepening globalization and information technology, Artificial Intelligence (AI), as a disruptive technology, is influencing the development of all industries with unprecedented speed and breadth. The publishing industry, as an important carrier of cultural dissemination and knowledge transfer, is no exception to the profound impact of this wave of technology. Artificial Intelligence Generated Content (AIGC), as an emerging force in AI technology, is leading the publishing industry to a new stage of high-quality development with its powerful content generation and automated processing capabilities.[1] AIGC is a new technology that is leading the publishing industry to a new stage of high-quality development.

Relying on the in-depth comprehension of large language models, powerful computational capabilities, and extensive knowledge accumulation of pre-trained models, generative AI technology can autonomously create diverse text, images, audio, video, and even program code. This revolutionary technology not only significantly improves the efficiency and creativity of content production, but also broadens the boundaries of content forms, enabling publications to reach readers in a richer, more diversified, and interactive way, and facilitating the modernization process of knowledge dissemination and cultural communication.

However, although generative AI brings great opportunities and transformative power to the publishing industry, its application process also faces many challenges and dilemmas. The bottleneck of technological transformation, the obstacle of market crossing, the consideration of ethical safety, and the path of integration and development are all key issues that need to be solved urgently.

2. The application prospect of generative artificial intelligence to empower the high-quality development of publishing

Science and technology innovation is the core element for developing new quality productivity and promoting the development of high-end, intelligent, and green industries. Artificial Intelligence Generated Content (AIGC) relies on the depth of comprehension of the large language model, the extensive knowledge accumulation of the pre-trained model, and the learning mechanism based on the continuous optimization of human feedback to realize a whole new dimension in content creation - -autonomous integration and innovative generation, allowing the cultural publishing industry to usher in a profound change of high efficiency and intelligence, giving rise to diversified and highly efficient publishing application scenarios such as intelligent topic planning, manuscript writing assistance, human-machine collaborative editing and proofreading, intelligent printing plant operation, and intelligent knowledge services.

With the continuous progress of technology and the continuous exploration of application scenarios, the boundaries of intelligent publishing will be further broadened and deepened, bringing us a richer, more convenient, and high-quality publishing experience.[2] The following is a summary of the latest developments in intelligent publishing.

2.1. Comprehensive management of resource integration and sharing

First of all, generative artificial intelligence comprehensively optimizes the efficiency of resource allocation and sharing, promotes the in-depth sharing of resources such as copyright, editorial experience, and market data among different publishing subjects, breaks down the barriers of stock resources, realizes the continuous influx of incremental resources for publishing, and promotes the harmonious coexistence of the publishing business and the publishing industry. In recent years, the national level has also accelerated the construction of the industry data system. As of 1 August 2024, the National Public Service Platform for Publishing and Distribution Information has accessed 166 publishing and distribution units and Internet e-commerce companies, and 4,571 shops, and has cumulatively exchanged 1,671,900 items of bibliographic data, 519,000,000 sales data, 11,609,000,000 items of inventory data, and exchanged 374,800 e-monotony certificates. Gradually improve industry data management[3]. In the context of globalization, AI can likewise help publishing organizations break geographical restrictions and achieve resource integration on a global scale. For example, through cross-border cooperation and copyright transactions, publishing institutions can introduce outstanding foreign works and broaden access to resources, as well as promote outstanding domestic works to the global market and expand market share.

2.2. Intelligent Innovation in Content Creation and Presentation

As a cutting-edge technological system, generative AI is rooted in sophisticated algorithms, complex models, and multiple technological innovations, and is capable of autonomously creating an unprecedented diversity of content such as text, images, audio, video, and even programming code.[4] The result is an unprecedented diversity of content, including text, images, audio, video, and even programming code.

In the field of content creation in the publishing industry, generative AI can simulate the writing style and thought process of human authors by training large-scale language models to generate high-quality text content. These models can not only generate coherent paragraphs or even entire articles based on input keywords, topics, or contexts but can also be iteratively optimized based on feedback to improve the accuracy and innovation of the content. For publishing organizations, this means that they can respond more quickly to market demand and generate diverse content products while reducing their reliance on a single author and improving the flexibility and efficiency of content production.

What's more, AI can also achieve the integration and innovation of multimodal content and broaden the boundaries of content forms. For example, when publishing picture books or popular science books, AI can generate illustrations, animations, or audio commentaries that match the textual content, enhancing the reading experience of readers, enabling publications to reach readers in a richer and more diversified, immersive and interactive way, attempting to operate full copyright and develop the whole industry chain, and facilitating the modernization process of knowledge dissemination and cultural communication.

2.3. Automated management of editing and print distribution

In the editing process, AI editing tools can automatically check the manuscript for grammatical errors, spelling mistakes, and improper use of punctuation, and provide suggestions for changes. This process not only reduces the workload of editors but also improves the accuracy of editing.

At the same time, AI can also perform content checking, identifying and marking potential plagiarism or duplicate content by comparing a large number of text databases to ensure the originality and copyright security of publications. For the editing of long books or complex documents, AI can also assist in structural analysis, chapter division, and logical sorting, making the editing process more systematic and scientific.

Publishers can also leverage AI to upgrade automated print and distribution management systems to reduce operating costs and improve responsiveness and customer satisfaction.[5] In the printing process, generative AI can automate format conversion, color correction, and typesetting. In the printing process, generative AI can automate the format conversion, color correction, and typesetting optimization of printing files, reducing manual intervention and error rates. At the same time, AI can also monitor the operation status of printing equipment and printing quality in real-time, and identify and solve problems promptly. In terms of distribution, AI can also provide optimal distribution strategies and logistics solutions by analyzing sales data, inventory, and logistics information.

2.4. Market Forecasting and Precision Marketing for Book Distribution

In the topic planning stage, AI can dig deep into user data from social media, online reading platforms, and other channels through big data analysis technology, identifying hot topics, potential bestseller themes, market demand gaps, etc., to provide valuable market information and topic direction, which can help publishers quickly orientate the market direction. At the same time, AI can also analyze historical sales data, market trends, and other information to carry out market forecasts and risk assessments of selected topics, helping publishers to scientifically plan the number of first printings and quickly respond to readers' needs while reducing the risk of inventory backlog.

Based on user behavioral data and preference analysis, AI can build detailed user profiles[6]. These portraits include information on the user's age, gender, geography, interest preferences, and other dimensions, which refines a more comprehensive reader portrait for the publishing organization and helps to further upgrade the intelligent recommendation system. For readers with different preferences, generative artificial can interactively analyze readers' preferences, accurately meet readers' needs, be more diversified to meet the audience's expectations of the field of vision, and achieve the personalized distribution of publishing content distribution of "a thousand people, a thousand faces".[7] In terms of publishing content distribution, it can provide personalized distribution and delivery for thousands of people. At the same time, it can also provide customized reading suggestions, enhance reader loyalty and satisfaction, and lay a solid foundation for long-term development.

3. Dilemmas and limitations faced at this stage

Compared with other forms of technology, generative AI shows excellent potential in terms of content and form and can seamlessly integrate the essence of intelligent technology with the modern needs of the publishing industry, promoting an unprecedented degree of fit between the two. However, generative AI still faces some key issues and challenges that need to be resolved to help the publishing industry achieve high-quality development.

3.1. Difficulty in transforming technology: shortcomings in innovation capacity in key areas

Although China is accelerating the pace of independent innovation, compared with the developed countries, especially in the core areas of high-end chips, operating systems, and industrial design software, and other core areas, China is facing dependence on external technology, AI arithmetic bottlenecks to be broken through, and significant shortcomings in innovation capacity in key areas, and this technological shortcoming has hindered China's path of independent development in the field of AI and limited the depth of the expansion of application scenarios.

The book publishing and distribution industry, currently at the turning point of building an intelligent network for cultural consumption, does not match the ratio of capital investment to actual output in the process of AI transformation. In the integration of AI and the cultural industry, despite the huge development potential, the large-scale application has not yet been realized, the deep mining of cultural data and the construction of the corpus are still in the early stage of exploration, and the development and practice of diversified application scenarios urgently need to be accelerated.[8] The development and practice of multiple application scenarios also need to be accelerate d urgently.

China Publishing Media Business Daily has actively introduced digital anchor technology in its innovative exploration of news reporting and live broadcasting, however, despite the unique charm of the digital anchor, the limitations of its current application should not be ignored: the lack of emotional communication ability, difficult to respond to audience needs, and even more unable to convey the warmth of the emotional resonance of people's hearts.

In the art of expression, digital anchors have made significant progress in the fluency of movement and the realism of language, but there is still room for improvement, and it is difficult to match the naturalness and vividness of real people. They undoubtedly have broad application prospects and can be widely used in a variety of fields, but as a complete replacement for real anchors, it seems premature.

Taking live streaming as an example, this area is particularly focused on emotional links and instant interaction. Consumers are often attracted by the anchor's emotional engagement and personalized charisma, thus stimulating the desire to buy. In the face of digital anchors who lack real emotional communication and intimacy, consumers may find it difficult to establish a deep emotional connection, which in turn affects their purchasing decisions. Therefore, despite the continuous evolution of digital anchor technology, it is still a huge challenge to cultivate a beloved star like "Dong Yuhui" or to surpass the real anchors in terms of the total amount of goods carried, at least in the publishing industry and similar industries that value emotional resonance.

Therefore, strengthening the basic research of AI technology, improving arithmetic efficiency, enriching algorithmic innovation, and building a perfect application ecosystem are strategic tasks that must be prioritized at present.

3.2. The market is hard to cross: the challenge of intelligent transformation in the book publishing industry

At present, there are obvious differences and imbalances in the adoption of AI technology and the distribution of resources among industries, regions, and even social strata, which inhibit the efficiency of information flow and hinder the popularization and development of the technology. Existing legal frameworks and regulatory mechanisms also show a certain degree of lag and limitations in the face of AI, a rapidly evolving field of science and technology, making it difficult to accurately grasp and respond promptly to its complex, volatile, and high-speed iterative nature. As a direct result, some large technology companies, the leaders in the field of AI, may take advantage of their dominant position in the market and adopt strategies such as data blocking and exclusivity agreements to create market monopolies, suppress the vitality of innovation in the market, and undermine the rights and interests of consumers.

As a key link in the traditional cultural industry chain, the book publishing and distribution industry, compared with those active in the field of digital science and technology, faces problems such as data scarcity, low data quality, and lack of data processing capacity. Specifically, the problem of "data silos" prevails in the industry, which makes it difficult to effectively integrate and share book data; at the same time, the low degree of advanced analysis and use of book data, and the lack of in-depth excavation and value refinement capabilities have failed to fully explore the value of the data assets, which makes it easy to miss the opportunities of the artificial intelligence era. Therefore, it is imperative to accelerate the intelligent upgrading of the book publishing and distribution industry, break the industry's data barriers, and enhance the effectiveness of data applications.[9] Therefore, it is imperative to accelerate the intelligent upgrade of the book publishing and distribution industry, break the industry's data barriers, and enhance the effectiveness of data applications.

3.3. Challenges and Opportunities of Data Rights Enforcement: Building a New Ecology of Copyright Protection for Publishing and Distribution in the Age of Intelligence

On a practical level, the issue of data rights poses a challenge that cannot be underestimated within the field of AI. Since the beginning of 2024, data resources have formally become part of the financial statements of enterprises, promoting the process of data assimilation, many places have also tried to integrate data and realize the table, but data rights are still facing many obstacles in practice. As a special and increasingly critical factor of production, the generation of data often involves complex interactions between multiple subjects with different degrees of contribution, and this intertwined attribute makes the definition of data property rights extremely complex.

While the introduction of generative AI in the publishing industry has brought innovation and efficiency in quality control, there are also concerns about ethical misconduct in its improper use.[10] The reason is that AI-generated works challenge the traditional concept of copyright. Because AI-generated works challenge the traditional concept of copyright, blurring the boundaries between originality and reproduction, and easily triggering copyright disputes.

Therefore, for the publishing and distribution industry, while actively applying AI technology, copyright issues must be handled carefully. How to define and maintain the legal boundaries of public domain knowledge and avoid unauthorized use or tampering requires publishing and distribution companies to work closely with copyright regulators, legal experts, and technology providers to develop copyright protection solutions that are in line with the characteristics of the new era of technology, and to ensure that technological innovation and the protection of cultural heritage coexist harmoniously and in parallel.[11] This will ensure that technological innovation and cultural heritage protection go hand in hand and co-exist in harmony.

3.4. Exploring Career Transitions in Publishing with Generative AI

With the deep integration of technology into the publishing process, AI tools have shown amazing efficiency in the traditional publishing process of "three reviews, three proofreads and one read-through", and practitioners in the publishing industry will face a major shift in their identity and responsibilities. They are no longer just decision-makers for content, but take on more of the role of operators and AI tool applicators. This requires that the relevant personnel not only be proficient in traditional publishing processes but also effectively use and guide intelligent technologies, achieving a double upgrade of their roles and skills.[12] The current rapid development of AI technology has made it possible to achieve the double upgrade of roles and skills. In the rapid development of artificial intelligence technology, AI tools have shown significant advantages in primary proofreading tasks, effectively overcoming the efficiency and accuracy problems that exist in the traditional Dark Horse proofreading software. The one-click operation not only simplifies the process but also significantly improves the work efficiency, especially in the basic error checking following the established language specification, AI has shown excellent ability.

However, when the proofreading work is deepened to the advanced level, especially when it involves the detailed sorting and checking of logical relations, the limitations of AI come to the fore, and AI's judgment is mainly based on the database of linguistic norms accumulated in history, and it tends to mark the contents that do not conform to these norms as errors directly, which is a "one-size-fits-all" approach. This "one-size-fits-all" approach is undoubtedly a powerful force for productivity when dealing with texts that need to strictly follow the original language, especially when checking citations. On the other hand, for the pursuit of original language styles, especially for poetry, an art form that inspires unique textual charms by breaking conventional language norms, AI's standardized judgments may become a constraint.

Therefore, practitioners need to rethink their professional positioning, adapt to the new mode of working with AI, improve work efficiency and content quality, and more importantly, improve themselves to maintain the unique value of in-depth understanding and creative control of content. Because the massive training data that generative AI relies on may imply value issues such as secular bias and racial discrimination, these hidden risks may be invisibly amplified and spread under the impetus of AIGC. Therefore, publishers should strengthen the ethical review and supervision mechanism, strictly abide by the identity of "gatekeeper", and promote the harmonious coexistence of technology and humanities, to ensure the high quality of published content and the positive development of society.

Advances in technology have also touched the creative job market, with the rise of automated writing tools casting a shadow over the career prospects of many traditional writers and facing a reshaping of the employment structure. However, AI creation has the potential to exacerbate the problem of content homogenization, which will stimulate writers to seek breakthroughs and propel the publishing industry toward greater efficiency and precision.

3.5. Privacy Security, Algorithmic Bias, and the Urgent Issue of Ethical Review

The widespread use of AI systems is also accompanied by privacy and data security concerns. To provide a personalized service experience, AI may collect and analyze a large amount of personal data, and how to balance user experience and privacy protection has become an urgent issue.

The deeper concern is that the potential bias of AI algorithms may lead to the exacerbation of social problems such as gender and race, bring about market-oriented blind pursuit, and exacerbate the imbalance of social and cultural ecology. Joy Buolamwini, a researcher at the MIT Media Lab, pointed out that AI systems, especially those models that rely on big data from the Internet for deep learning, may absorb and amplify the biases that exist in human society. This phenomenon is known as Garbage In, Garbage Out (GIGO), where the quality of a model's output is limited by the quality of its input data. When training datasets contain biases, such as gender inequality or racial discrimination, AI systems will also reflect these biases when generating results, affecting the dissemination of positive culture. At the same time, the tendency of intelligent algorithms to push popular content may also inhibit the exposure of original and niche works, exacerbate the problem of content homogenization, form an information cocoon, and to a certain extent squeeze the living space of diversity, affecting the wide dissemination of knowledge and culture[13] . The information cocoon will be formed, squeezing the space for diversity to some extent and affecting the wide dissemination of knowledge and culture.

In addition, the authenticity and ethical censorship of AI-generated content has become a new challenge, especially when the content contains misleading or inaccurate information, the definition of responsibility attribution has become exceptionally complex and involves the rights and responsibilities of developers, publishers, and even the AI itself.

In summary, while embracing AI technology, the publishing industry must adhere to the ethical bottom line to ensure that the development and application of the technology can promote the progress of the industry while taking into account copyright protection, privacy and security, cultural diversity, and content fairness. Publishers, technology providers, and regulators should work closely together to build a set of industry norms adapted to the AI era, leading the technology in a more responsible and inclusive direction, and creating a healthier and more beneficial cultural environment for readers and society.

4. Innovative Development Strategies and Governance Paths of Generative Artificial Intelligence in the Publishing Industry

It has become a new dimension of communication, and a key innovation engine to promote the modernization of publishing in line with the trend of the times and to grasp the general trend of development. At present, this field has ushered in unprecedented development opportunities but is also accompanied by a series of urgent challenges. While enjoying the convenience and efficiency brought about by technological progress, we also need to implement precise measures to effectively manage the practical obstacles on the path of development and ensure the healthy and sustainable development of technology applications.

Specifically, on the one hand, we should actively embrace the changes brought about by generative AI, and make use of its powerful content generation capabilities, personalized recommendation systems, and efficient editing and processing tools to accelerate the digital transformation of the publishing process, enhance the efficiency and quality of content creation, and broaden the boundaries and depth of cultural communication.

On the other hand, given the ethical risks, data security, copyright protection, and other issues that may arise in the process of technological development, we need to establish a sound system of relevant laws and regulations, strengthen industry self-regulation and supervision, and guide technology developers and users to uphold the principle of technology for the good.

4.1. Optimizing the AI market ecology and build a strong defense of data security and privacy

Firstly, the government should take the initiative to gain an in-depth understanding of the challenges faced by cultural publishing enterprises in AI transformation, formulate and improve relevant laws and regulations such as data security and data rights, encourage the legal and compliant flow and sharing of data, and build a policy system that supports the development of AI.

Secondly, by providing incentives such as tax breaks and financial subsidies, it provides a solid backing for enterprises' technological innovation and R&D investment and stimulates market vitality. At the same time, we will strengthen market supervision, refine the guidelines for "fair competition" in the AI era, closely monitor the business behaviors of all kinds of platforms and enterprises, establish a sound reporting and feedback mechanism, work to prevent market monopoly, maintain a healthy order of market competition, and build an open, fair and sharing AI ecological environment.

Publishing and distribution enterprises should also establish comprehensive data security management mechanisms and technical defenses. In terms of internal management, they should raise the awareness of data security among all staff, implement a layered authorization system, such as setting differentiated data access rights for different business scenarios, apply encryption technology to strengthen sensitive information and carry out regular data security risk assessment and repair work. When cooperating externally, sign strict confidentiality agreements with third parties, clearly define the boundaries of data exchange and application, and prevent data leakage or improper use to ensure the healthy and sustainable development of the data ecosystem.[14] We will ensure the healthy and sustainable development of the data ecosystem.

4.2. Driving the upgrading of the book publishing and distribution industry

Book publishers and distributors need to take the initiative to cooperate with high-performance technology research and development teams, data support teams, and product service teams, follow the trend of technology, and improve the "technology application power" of generative artificial intelligence. In the cooperation, AI can achieve the digitization and structuring of copyrighted content, activate the stock of knowledge assets, innovate the way of cultural dissemination, enhance the overall competitiveness of the industry, and let "AIGC+Reading+Culture+Social" burst with new vitality. At the same time, it builds a perfect data governance system, ensures copyright compliance and information security, and promotes the harmonious coexistence of AI ethics and human values.

4.3. Collaborative promotion of digitization and talent development paths in the Cultural Industry

Cultural publishing enterprises should strengthen targeted training, encourage employees to adopt new technologies, apply new modes, adjust job functions, and adapt to the needs of the cultural industry in the new era. In 1998, the UK Department for Culture, Media and Sport (DCMS) issued the Creative Industries Mapping Document (which was updated in 2001), which for the first time treated the cultural industry as a creative industry in terms of top design, tracked the international development trend, and planned the development direction of the UK cultural and creative industries. In 1998, the Department of Culture, Media and Sport (DCMS) issued the Creative Industries Mapping Document (the document was updated in 2001), which, in terms of top-level design, for the first time treats the cultural industry as a creative industry, tracks the international development trend, plans the direction of the development of the UK's cultural and creative industries, and implements an overall marketing and branding strategy to help creative products and enterprises go global[1] The document points out that: "Electronic publishing is an important part of the UK's cultural and creative industries. The document points out that "electronic publishing provides an important opportunity for publishers and content providers to expand their global market share. Growth will be fuelled by converging technologies, opportunities to develop new revenue streams, and continued demand for information in fast and flexible formats." In terms of institutional innovation, the UK has formed a cross-sectoral and cross-industry Creative Industries Tak Force to improve the efficiency of specialized work.

Cultural publishing enterprises can refer to the reference, priority integration of traditional business teams, integrated communication teams, e-commerce service teams, data support teams, and other personnel, to form a special group, strengthen collaboration, improve efficiency, and integrate into the intelligent publishing process. Simultaneously increase the cultivation and introduction of innovative talents, optimize the talent training mechanism, improve the talent introduction policy, and attract more excellent talents to devote themselves to the research and development of key areas of the digital economy.

4.4. Technological Innovation, International Dissemination and Cross-Disciplinary Collaboration

In today's wave of generative AI, we need to accelerate the construction of a generative AI technology highland, and the cultural publishing industry is even more important to assist in the construction of a corpus centered on the Chinese Knowledge Ontology, which will support the research and development of AI technology with independent intellectual property rights, paving the way for the deep integration of the publishing industry with local technological innovation, and promote the localized prosperity of the knowledge and culture as well as the international dissemination of the knowledge and culture.

At the same time, we need to participate in the establishment of international standard data sets in a forward-looking manner, accurately grasp the balance between development and security, broaden our international vision, embrace audience orientation, make full use of the power of generative artificial intelligence technology, gain deep insights into the needs and cultural preferences of overseas markets, and create a global discourse system that not only contains Chinese characteristics but also transcends the cultural divide. This discourse system will be widely disseminated through multi-dimensional channels such as intelligent knowledge service platforms, cross-border book transactions, and international cooperation on copyright, to enhance the international community's deep understanding of China and its wide recognition of, and to jointly promote the construction of a more just and diversified global discourse system.

Deepening cross-field collaboration and interoperability will also be an important way to achieve this goal. The cultural industry should actively participate in cross-border cooperation, deeply understand the characteristics of data "multi-dimensional reuse" and "full-link traceability", and promote data sharing and in-depth fusion between the cultural industry and other industries, to maximize data efficiency, stimulate industrial synergy, and promote the development of a future society led by artificial intelligence. We will work together to build a highly interconnected future society led by artificial intelligence.

5. Conclusion

Generative AI is leading the cultural publishing industry into a profound and unprecedented change, becoming the core engine for promoting the high-quality development of publishing and bringing new opportunities for content creation, copyright development, editing and printing efficiency, and communication and interaction. However, copyright disputes, ethical risks, value penetration, and the digital divide are all challenges on the way forward that require the publishing industry to deal with prudently. While pursuing technological empowerment, the publishing industry needs to balance the scales of development and safety, deeply understand and handle the relationship between humans and machines, make use of technological power to make up for the limitations of manpower, and also correct technological bias and avoid cultural chaos with the help of human wisdom, to practically empower the publishing industry to achieve high-quality and sustainable development and endeavor to build an intelligent cultural ecology for the new era.