How is artificial intelligence changing internet publishing?

Levent Kurt
By Levent Kurt
21 Min Read

Artificial Intelligence (AI) is revolutionising the landscape of journalism, internet publishing and content creation, bringing both exciting opportunities and formidable challenges. The integration of AI in newsrooms, from automating routine tasks to generating content, has the potential to enhance productivity and drive innovation. However, it also raises significant legal, ethical, and trust issues that need to be addressed to ensure responsible and transparent use of this technology.

AI has been a game-changer in the journalism, internet publishing and content creation particularly in larger newsrooms where automation has streamlined production processes for years. AI tools can generate earnings reports, sports recaps, and even transcriptions, allowing journalists to focus on more complex and creative tasks. For instance, generative AI systems like ChatGPT and DALL-E can produce summaries, newsletters, and even full articles, potentially transforming how news is created and consumed.

Despite the benefits, the integration of AI in internet publishing is fraught with legal and ethical challenges. One primary concern is the risk of inaccuracies and the potential erosion of public trust. AI-generated content can sometimes contain errors or present biased information, which could undermine the credibility of news organizations. Ensuring the accuracy and reliability of AI-produced content is therefore paramount. Another significant issue is copyright infringement. The use of AI to generate content can lead to the unintentional misuse of copyrighted material, both by and against news organizations. Legislators need to establish clear definitions and regulations around AI use to protect intellectual property rights and prevent violations.

To address these challenges, a multi-faceted approach involving policymakers, publishers, technology developers, and academics is essential. Legislation must provide clear guidelines on AI use in internet publishing, including specific disclosures for different AI categories and practices. This will help ensure transparency and accountability in how AI is utilized. News organizations and tech companies must also establish ethical guidelines and educational programs to promote responsible AI use. Training journalists on the ethical implications of AI and how to use these tools responsibly is crucial. Furthermore, fostering collaboration between stakeholders can lead to the development of best practices and standards that enhance trust and reliability in AI-generated content.

The Future of Journalism and Internet Publishing

The future of journalism and internet publishing in an AI-driven world will likely see a blend of human creativity and machine efficiency. AI can support journalists by providing resources such as images, video clips, and data analysis, allowing them to craft more compelling and accurate stories. Additionally, AI can help identify original sources of information and suggest relevant topics, enhancing the overall quality and depth of news coverage.

In recent times, several prominent media companies have turned to AI to generate content. For instance, News Corp has reportedly been using AI to produce 3,000 Australian news stories per week. This trend is not confined to Australia; media organizations globally are adopting similar practices. The appeal of AI lies in its ability to rapidly produce large volumes of content, thereby addressing the high demand for continuous news updates. However, this shift raises critical questions about the quality and integrity of AI-generated journalism.

Large language models, such as GPT-4, do not inherently produce factual information. Instead, they predict language patterns based on the data they were trained on. This fundamental nature of AI presents a significant limitation. AI models can generate content that sounds plausible but may not be accurate or reliable. This issue was highlighted when tech news outlet CNET published AI-generated articles that were riddled with errors, leading to public outcry and a subsequent pause in their use of AI.

The rapid adoption of AI in journalism is part of a broader trend where mainstream media organizations are increasingly operating like digital platforms. This shift is driven by the need to monetize attention in a data-hungry, algorithmically optimized environment. However, this approach often comes at the expense of journalistic integrity and quality. The use of AI to generate content exacerbates existing issues of misinformation and the erosion of public trust in news media.

A significant concern with the proliferation of AI-generated content is the potential for a recursive loop where AI systems are trained on outputs created by other AIs. This phenomenon, referred to as “Habsburg AI,” can lead to a degradation in the quality of content, as the AI becomes increasingly detached from original, human-generated data. Research suggests that without fresh, original data, AI models quickly collapse, resulting in a decline in the quality and reliability of their outputs.

The Impact of AI on Click-Through Rates and Ad Revenues for News Websites

The integration of artificial intelligence (AI) into content creation has sparked both excitement and concern within the media industry. While AI offers various benefits, such as improved efficiency and personalized content delivery, it also poses significant threats to traditional news business models. One of the most pressing concerns is how AI will impact click-through rates (CTR) and advertising revenues for news websites.

Traditionally, news websites have relied heavily on search engines to drive traffic. Users search for information, and search engines provide links to relevant articles. This traffic is vital for news websites as it translates into ad impressions and revenue. However, AI is changing this dynamic. Advanced AI systems are increasingly capable of generating direct answers to user queries without requiring users to click through to external sites. For instance, when a user asks a question, AI can produce a comprehensive response sourced from multiple articles, effectively bypassing the need to visit the original news sites. This shift could lead to a substantial decrease in click-through rates, as users obtain the information they need directly from the search engine results page.

Advertising revenue models for news websites are tied to web traffic. Lower traffic means fewer page views, which directly impacts the number of ad impressions. As AI-generated responses become more prevalent, advertisers might find that their ads are no longer reaching their intended audience through traditional news websites. This could lead to a decrease in ad spend on these platforms, further eroding their revenue base.

In addition, AI’s ability to provide instant, direct answers also affects user engagement with news websites. When users spend less time navigating through articles and more time getting quick answers from AI, they engage less with the comprehensive reporting and analysis that news websites offer. This reduced engagement can lead to a decrease in loyalty and subscription rates, as users may no longer see the value in paying for content they can get summarized for free.

On the one hand, artificial intelligence is a useful tool for everyone and every company that produces content on the Internet, but on the other hand, it may cause websites and content producers to lose their jobs, reduce their income or deteriorate their financial structure. In addition, the fact that search engines such as Google will provide direct results with their own artificial intelligence applications, instead of directing users to websites as in the current search order, will cause a very serious decrease in traffic to websites and will seriously affect many companies that produce content, and may even lead to their closure. On the other hand, if we consider that the data that feeds artificial intelligence is created by content producers on the Internet, it means that content producers will not be able to create more content in such a bad scenario, and search engines or artificial intelligence applications will not be able to access the content created on the Internet to train their models after a while. This can lead to a decrease in the performance of artificial intelligence models that are not trained with current data and information and may produce incorrect results. It is therefore necessary to create useful and sustainable solutions for both parties.

AI’s Impact on Journalism: Enhancing Efficiency Amid Ethical and Operational Challenges

Let’s take a look at recent studies and reports on this topic and consider the issue in more depth. A report by Felix M. Simon, funded by the Tow Center for Digital Journalism at Columbia University, delves into this phenomenon, examining how AI is transforming journalism and its broader implications for the public arena. Drawing on 134 interviews with news workers from 35 news organizations across the United States, the United Kingdom, and Germany, as well as 36 international experts, the report underscores that AI adoption is driven by a combination of technological advancements, market pressures, competitive dynamics, and the pervasive sense of uncertainty and hype surrounding AI.

The report also sheds light on the dependency of news organizations on major technology companies (like Google, Amazon, and Microsoft) for AI tools and infrastructure. This reliance is particularly pronounced among smaller publishers who lack the resources to develop in-house AI solutions.

Despite the potential benefits, the report highlights several challenges and concerns. The quality and reliability of AI outputs can vary, leading to potential reputational risks for news organizations. Furthermore, the use of AI raises ethical considerations, such as the risk of biases in AI-generated content and the potential erosion of journalistic autonomy as news organizations become more dependent on technology companies. The integration of AI into journalism is not without its complexities. News production involves a variety of tasks that are not easily automated, and the adoption of AI can sometimes introduce new demands rather than alleviating existing burdens. For example, while automated transcription can save time, it may also require journalists to spend additional time verifying and editing AI-generated content.

The report concludes that AI is currently more of a retooling mechanism rather than a revolutionary change in journalism. It enhances efficiency and productivity in certain contexts but does not fundamentally alter the core functions of news organizations. The ultimate impact of AI on journalism will depend on how news organizations choose to implement and utilize these technologies, balancing the pursuit of efficiency with the need to maintain journalistic integrity and autonomy.

AI-Powered Journalism: Lessons and Insights from The New York Times’ AI Director

Zach Seward, editorial director for AI initiatives at The New York Times, shared his thoughts on the current state of AI-powered journalism at SXSW. He discussed both the pitfalls and successes of AI integration in journalism and offered lessons for the future.

The Dark Side of AI Journalism

Seward discussed failures in the use of AI in journalism, highlighting cases where AI-generated content has led to significant errors and ethical issues:

  • CNET’s Financial Advice: CNET used automated technology to publish financial advice articles that were full of errors and plagiarism. The articles were then corrected by human experts, revealing the inadequacy of relying solely on AI for complex content.
  • Gizmodo’s Star Wars Chronology: G/O Media’s attempt to create a chronological list of Star Wars content using AI resulted in inaccuracies that embarrassed the publication. This highlighted AI’s limitations in handling specialized content without human supervision.
  • Sports Illustrated and The Street: Arena Group’s use of AI to write product reviews revealed the existence of fake writers. This incident highlighted the dangers of deceptive practices in AI-generated journalism.

These examples share common problems such as unchecked content, lazy approaches, selfish motivations and dishonest presentations. These cases highlight the importance of rigorous moderation, transparency and a focus on readers’ interests.

Successful AI Applications

Seward presented examples of successful uses of AI in journalism:

  • The Marshall Project: This nonprofit used GPT-4 to summarize prison book banning policies in several states and made them accessible to readers.
  • Oversight Reporting in the Philippines: A private GPT helped journalists expose corruption by summarizing government audit reports.
  • Realtime: This automated news site uses AI to provide context to data graphics, giving readers a clear understanding of financial markets and public records.
  • WITI Recommends: By extracting product recommendations from unstructured text in a daily newsletter, this project showcased the ability of generative AI to create order from chaos.

These examples show how AI can add value in journalism when used correctly and demonstrate how successful AI applications should be underpinned by human oversight and journalistic principles.

AI Transforming Publishing: Benefits, Barriers, and Future Potential

In another report, Artificial Intelligence (AI) is becoming increasingly important to the UK publishing industry, according to a report by Frontier Economics for the Publishers Association. This comprehensive study, the first of its kind in the UK, uses interviews, case studies, and an industry-wide survey to explore AI’s current role and potential future impact on publishing. The findings reveal that AI applications are already generating substantial benefits, with expectations for even more significant advancements in the near future.

The report includes several key statistics:

  • 62% of surveyed publishers are currently using AI.
  • 79% of large publishers have invested in AI compared to 39% of smaller publishers.
  • AI applications are expected to deliver up to $2.1 billion in cost savings and additional revenue by 2030.

The sector faces several barriers to further AI adoption, including a lack of technical skills, challenges integrating AI with existing IT infrastructure, and the high upfront costs associated with AI research and implementation. Legal uncertainties regarding intellectual property laws pose significant concerns, particularly around text and data mining rights and the patenting of AI-generated content. To overcome these barriers, the report recommends enhancing collaboration between publishers, AI-focused SMEs, and academia to leverage diverse expertise and resources. Policy interventions are also suggested to ensure legal clarity concerning intellectual property rights and to provide financial and technical support to smaller publishers. By addressing these challenges, the UK publishing industry can better harness AI to drive innovation, efficiency, and competitive advantage.

In conclusion, the integration of AI into journalism and internet publishing presents both opportunities and challenges. While AI can enhance certain aspects of news production and accessibility, it also poses significant risks to the quality and integrity of contents. As media organizations navigate this complex landscape, it is crucial to prioritize ethical considerations and maintain a commitment to journalistic integrity.

Ensuring the accuracy, reliability, and ethical use of AI-generated content is paramount to prevent the erosion of public trust. Addressing concerns such as copyright infringement, biases in AI-generated information, and the potential displacement of human journalists requires a multi-stakeholder approach involving policymakers, publishers, technology developers, and academics. The evolving landscape of AI in journalism necessitates the establishment of robust guidelines, transparent practices, and continuous education to promote responsible AI use. By fostering collaboration and creating sustainable systems that balance the benefits for both content creators and AI developers, the media industry can navigate the complexities of AI integration effectively.

Looking ahead, the future of news websites in the AI-driven era will be defined by their ability to adapt and innovate. News organizations must focus on maintaining quality journalism by investing in technologies that support accurate reporting, fostering transparency in AI use, and upholding ethical standards. The challenge will be balancing the efficiency gains from AI with the irreplaceable value of human insight and editorial judgment. Furthermore, news websites must find ways to sustain their revenue models in the face of declining ad revenues and changing user behaviors.

The future of journalism and internet publishing in an AI-driven world will likely see a symbiotic relationship between human creativity and machine efficiency, ensuring that technological advancements support, rather than undermine, the core values of journalism. News organizations that embrace innovation while staying true to these principles will be best positioned to thrive in this dynamic landscape. Additionally, fair compensation for news outlets whose content is used to train AI models must be addressed to prevent further financial harm to the industry.

As AI continues to evolve, it is crucial for the media industry to adapt and find ways to integrate AI in ways that support, rather than undermine, the financial viability of news organizations. Ensuring that AI serves as a tool to enhance human journalism, rather than replace it, will be key to maintaining a healthy, diverse, and sustainable media landscape.

The integration of artificial intelligence (AI) into journalism, internet publishing, and content creation presents a dual-faceted reality of immense opportunities alongside substantial challenges. AI has proven to be a game-changer, enhancing efficiency, productivity, and innovation within newsrooms by automating routine tasks and generating content. However, this technological advancement brings forth significant legal, ethical, financial and trust issues that must be carefully managed to maintain the integrity of journalism.

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