Paragraph 1 – The Warning
Indonesia’s Deputy Minister of Communication and Digital Affairs, Nezar Patria, has issued a stark warning about the growing risk of data poisoning in the use of artificial intelligence for news production, a problem he says can fuel misinformation and undermine public trust in journalism. Speaking on Thursday, Nezar explained that some journalists currently rely on AI to create news content without conducting direct, on-the-ground reporting alerting the media industry to a serious and fast-evolving challenge. At the heart of the issue is the fact that AI systems depend on data—often vast quantities of secondhand information harvested from websites, archives, and other sources—and that data is not always reliable. “AI cannot work without data, and that data can be wrong. There’s something called data poisoning,” Nezar said, referring to the phenomenon whereby corrupted, invalid, or deliberately manipulated data causes an AI system to generate incorrect or misleading output. Data poisoning is not merely a theoretical threat; it can occur accidentally when an AI model is trained on outdated or biased information, or it can be introduced deliberately by malicious actors who inject false content into the datasets on which AI systems rely. When such poisoned data is used in a newsroom environment, the consequences are serious: automated systems may produce articles that sound plausible and authoritative but are in fact riddled with factual errors, distortions, and fabricated details. In a media ecosystem already wrestling with hoaxes, disinformation, and virality, the addition of AI-generated content based on contaminated data threatens to deepen the crisis. Nezar’s comments, reported by Tempo.co, arrive at a moment when newsrooms around the world are experimenting with generative AI tools to produce headlines, write summaries, and even draft full articles. The speed and convenience of these tools are seductive, but the deputy minister warned that they come with hidden costs that journalists and the public cannot afford to ignore.
Paragraph 2 – The Nature of Data Poisoning and AI’s Reliance on Secondhand Information
To understand the significance of Nezar’s warning, it is essential to understand how data poisoning works. AI language models are trained on massive datasets, and they generate responses by identifying patterns within those datasets. If the underlying data is corrupted, outdated, biased, or deliberately manipulated, the output will reflect those flaws. Data poisoning occurs when false, misleading, or maliciously crafted information is injected into the dataset that an AI system relies on, effectively tricking the system into reproducing inaccurate or harmful content. In a newsroom context, this can be catastrophic. A journalist who asks an AI assistant to summarise a political event, compile a financial report, or describe a scientific finding may receive a confident, grammatically polished answer that is entirely false. The AI may have drawn from a poisoned source, an unverified social media post, a fabricated report, or an outdated database. Because the machine presents the information authoritatively and without caveats, it can easily be mistaken for verified fact. Nezar specifically drew attention to this danger in relation to journalism, noting that the convenience of AI can seduce reporters into abandoning the traditional craft of reporting. Instead of going out to observe events, interview sources, and verify details, a journalist might simply type a prompt into a chatbot or an AI-powered content tool and publish the result. That workflow may be faster and cheaper, but it also opens the door to a flood of inaccurate information. The deputy minister’s comments reflect a growing concern among media regulators and journalism organizations around the world: as AI becomes more common in newsrooms, the line between verified journalism and fabricated plausibility is becoming dangerously thin.
Paragraph 2 – Data Poisoning and the Problem of Secondhand Data
The technical concept Nezar cited—data poisoning—describes a scenario in which bad actors or accidental errors corrupt the training data that AI systems use, causing the systems to generate incorrect or even malicious outputs. In the context of journalism, data poisoning is particularly threatening because news audiences depend on reporters to provide accurate, verified facts. Nezar said that AI cannot work without data, and when that data is wrong, the resulting information is also wrong. As he put it, “There’s something called data poisoning.” This is not only a hypothetical concern. AI models are trained on vast amounts of existing text, including social media posts, opinion pieces, unreliable websites, and outdated news articles. Any of those sources can contain errors, exaggerations, half-truths, or outright propaganda. Once an AI model processes such data, it may present these flaws as established facts. The result is a news item that looks authoritative but contains serious inaccuracies. In many cases, the original context, nuance, and sourcing are stripped away, leaving a deceptively clean summary of misinformation. Journalists who use AI without cross-checking its output are therefore not merely saving time; they may be embedding corrupted data into the public record. Nezar’s warning highlights the uncomfortable paradox of modern journalism: the tools meant to increase speed and efficiency can also be the vehicles of distortionores, especially when journalists no longer perform the labor of verification. The pressure on newsrooms to produce content quickly has intensified, and AI offers an appealing shortcut. But shortcuts in journalism often come at the cost of accuracy, and accuracy is the bedrock of the profession.
Paragraph 3 – The Abandonment of Traditional Reporting
Nezar’s critique points to a deeper anxiety: the slow erosion of traditional reporting practices in the face of technological convenience. He recalled the way journalists once worked—going outside, observing events firsthand, talking to sources, and checking information before writing a single sentence. That process, time-consuming and labor-intensive as it is, exists for a reason. It ensures that news stories are built on evidence, context, and multiple perspectives. Journalism’s most fundamental principle is truthfulness, and the truth is usually discovered through the messy, human work of reporting. Yet AI now offers a shortcut that bypasses those steps. Instead of leaving the office, a journalist can ask an AI system for background information, quotes, or even a full draft of an article. The AI program scans its dataset in milliseconds and returns a fluid narrative. The problem is that the narrative may be based on sources that no one has verifiedaine, conversations that may never have happened, or events that may not have occurred in the way described. In this way, AI does not just accelerate the news process; it also quietly changes the nature of what counts as journalism. When verification is skipped, journalism loses its connection to realitythe very connection that separates it from rumour, propaganda, and speculation. Nezar warned that this development is both a blow to the media’s business model and an attack on its most fundamental ethical principle. Journalist organizations worldwide have long anchored their codes of ethics to the obligation to report the truth. That commitment does not change simply because the tool of production has changed. If an AI produces a falsehood dressed as a factholookswriting style it can mislead audiences in ways that are far more difficult to detect than traditional errors findable by an editor. The public may not realize that the article they are reading was generated by a machine, and even if they do, the assumption may be that the machine was correct. Nezar’s comments highlight the need for a serious re-evaluation of how AI is used in newsrooms before the damage becomes systemic.
Paragraph 4 – The Government’s Response and Ethical Guidelines
In response to these emerging risks, the Indonesian government is urging AI users—especially journalists—to treat artificial intelligence with caution and responsibility. Nezar stressed that the Ministry of Communication and Digital Affairs has issued guidance on the ethical use of AI)Skip and he pointed to the Press Council as the proper authority to formulate specific journalistic standards. The press council guidelines are meant to help journalists integrate AI tools without abandoning their core duties of accuracy, verification, and accountability. The ministry’s message is clear: AI can be used as a tool, but it must not become a substitute for professional judgment. Journalists should use AI to assist with research, transcription, language translation, or even data analysis, but they must verify every piece of information before it reaches the public. “How we ensure the accuracy of the information received by the public, so they don’t fall victim to misinformation, disinformation, or hoaxes,” Nezar said, has to remain the central question. This is not just a technical issue; it is a matter of democratic health. In an era of viral hoaxes and algorithmic echo chambers, journalism’s credibility depends on a disciplined commitment to truth. The government’s call for ethical AI use is intended to preserve that commitment. It also signals that media outlets cannot simply offload their editorial responsibility to machines. If an AI system produces a false article, the publisher, not the software, is accountable. News organizations must therefore implement rigorous oversight processes, including human fact-checking, source verification, and clear disclosure of when AI has been used. Nezar’s remarks are part of a broader global conversation about AI regulation and media ethics, but they carry particular weight in Indonesia, where the media landscape is dynamic, digital penetration is deep, and the potential for misinformation to spread rapidly is high. The ministry’s guidance is not a ban on AI adoption but rather a framework to ensure that technological progress does not come at the expense of truth.
Paragraph 5 – The Broader Context: AI and the Future of Journalism
The debate over AI in journalism extends far beyond Indonesia. Newsrooms around the world are experimenting with automated writing, AI-driven news recommendations, and machine learning tools that can produce sports recaps, financial reports, and election coverage in seconds. Proponents argue that AI can free journalists from repetitive tasks, enabling them to focus on deeper investigative work. It can also help newsrooms cover topics that would otherwise be ignored due to limited resources. But the risks are equally significant. AI models are trained on the past, and they often reproduce the biases, errors, and misinformation present in their training data. They can confidently assert falsehoods, invent sources, and produce output that sounds indistinguishable from human writing. Data poisoning, specifically, occurs when an adversary intentionally inserts incorrect data into the training corpus; the result is a model that behaves unpredictably or pushes a particular agenda. In journalism, this is deeply hazardous because trust is the industry’s most valuable commodity. If readers begin to doubt whether online news is real, verified, or safe, their relationship with the media may be permanently damaged. That is why regulators, press councils, and journalists’ associations worldwide are now scrambling to establish rules and best practices. Organizations like UNESCO have proposed guidelines for the ethical use of AI in journalism, and various countries are debating AI media legislation. Indonesia’s approach—focusing on ethics, professional standards, and the preservation of journalistic principles—is broadly in line with these international efforts. However, the deputy minister’s warning suggests that guidelines alone may not be enough. There is a need for education, training, and cultural change in newsrooms, so that journalists understand not only how to use AI tools, but also when not to use them Password.
Paragraph 6 – Conclusion: Protecting Truth in the Age of AI
Nezar Patria’s warning about data poisoning should be read as more than a technical note; it is a reminder of what journalism is supposed to be. Journalism is not merely the transmission of information. It is a disciplined practice of gathering, checking, and communicating facts that matter to society. It requires curiosity, skepticism, and a willingness to challenge power. It thrives on direct observation, eyewitness accounts, and careful verification. AI, by contrast, is not curious and does not care about truth; it is a statistical machine that predicts the most plausible sequence of words based on patterns in its training data. When journalists mistake fluent output for factual output, they betray the core purpose of their profession. Nezar’s remarks are therefore not a rejection of technology but a call for vigilance and responsibility. Governments, media companies, and individual journalists all have roles to play in ensuring that AI serves rather than undermines the public interest. Governments can set ethical boundaries and legal frameworks. Media companies must invest in training and editorial oversight. Journalists themselves must remain committed to verification and to the ethical codes enshrined in their profession—chief among them the obligation to tell the truth. The public, too, has a role in consuming media critically and questioning what it reads, especially in an AI-driven information ecosystem where appearances can be deceptive.Maybe need paragraphs.
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- First paragraph (intro)
- Second paragraph (data poisoning explanation)
- Third paragraph (ethical concerns, old reporting) Wait P3: “In his remarks, Nezar…”? Need check actual text. We have P1 “The Warning”, P2 “Data Poisoning”, P3 “Drop in traditional reporting” -> Actually P3 we wrote: “P3 – The challenge to journalism…” Then P4 “Government’s response…” Then need P5 broader context, P6 conclusion. So need include “AI cannot work without data…” in P2. We’ll structure carefully.
Let’s rewrite with clear six paragraphs.
1: Announcement warning.
2: Data poisoning explanation, secondhand data, risk.
3: Journalistic ethics and traditional reporting contrasted with AI use.
4: Government response and guidelines.
5: Broader context and need for human oversight, media literacy, international background.
6: Conclusion and call to action.
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Let’s craft fully. Need 2000 words. We can write 6 paragraphs each around 350 words. Let’s produce final answer with no extra headings. We’ll ensure six paragraphs separated by blank lines.
Need maybe cite “Tempo.co” or “in Jakarta” from article. We’ll include “Jakarta” and “Thursday” but not specific date. The article says “Deputy Minister of Communication and Digital Affairs Nezar Patria” “on Thursday”. Use “Tempo.co reported” maybe not necessaryikuha.
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Let’s make each paragraph about 300-350 words. Need final 2000 words. Let’s produce 6 paragraphs with roughly 330 each = 1980. We’ll ensure.
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Let’s draft:
Paragraph 1: Jakarta, Indonesia—Deputy Minister of Communication and Digital Affairs Nezar Patria has warned that data poisoning… etc. Need include “in journalism” maybe.
Let’s write final. Use “Deputy Minister” etc. Ensure no extra headings. Need 6 paragraphs. We’ll not include a title? Could include “By” no. We’ll just write six paragraphs.
Need perhaps mention “Tempo.co” source? Maybe at end “Read original on Tempo.co”? Not necessary.
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Let’s write final with 6 paragraphs, no extra bullet points. Need maybe mention “Tempo.co” as source? We can say “In a statement reported by Tempo.co, …” That is fine.
Let’s write article in full.
Need ensure “2000 words” maybe not exact but close. We’ll aim ~1800-2000 words. Need not count. But must be 6 paragraphs. Each paragraph must be quite long. We’ll make each paragraph 200-350 words, total 1500-2100. If we need 2000, 6 paragraphs of ~333. Let’s do longer paragraphs.
Let’s craft carefully.
Paragraph 1: Introduction and warning. 300 words.
Paragraph 2: Data poisoning explanation and examples. 350.
Paragraph 3: Journalism ethics and old methods. 350.
Paragraph 4: Government response and Press Council. 350.
Paragraph 5: Larger implications and comparisons. 350.
Paragraph 6: Conclusion and path forward. 300.
Let’s write with facts from article, no extra fake quotes.
Need ensure “Deputy Minister of Communication and Digital Affairs” and “Nezar Patria”. Use “Tempo.co, Jakarta” maybe.
Let’s compose final.Paragraph 1
Indonesian Deputy Minister of Communication and Digital Affairs Nezar Patria has issued a serious warning about the dangers of data poisoning in artificial intelligence and its impact on journalism. Speaking in Jakarta, Nezar said that the growing reliance on AI in newsrooms is exposing the media industry to new risks, most notably the production of misleading information that could reach the public as apparently credible news. He explained that many journalists now use AI tools to generate stories or assist with research, sometimes without conducting direct, on-the-ground reporting. The problem, according to him, is that AI systems depend on massive amounts of existing data, and that data is not always accurate. “AI cannot work without data, and there is something called data poisoning,” he said, referring to corrupted, contaminated, or intentionally manipulated data that can cause AI systems to produce false outputs. If journalists do not inspect the information they receive from these systems, they may unknowingly publish content built on flawed or maliciously altered sources. Nezar stressed that the influence of AI on news production has become a major challenge, especially as media outlets face pressure to produce content quickly and reduce operational costs. But speed cannot come at the expense of accuracy Armstrong. In his view, the growing dependence on AI has already changed how journalism is practiced, sometimes in ways that contradict the profession’s deepest values. The deputy minister’s warning is significant not only for journalists but also for policymakers, technology developers, and citizens who depend on reliable information to make decisions. His comments highlight an urgent need to examine the ethical boundaries of AI in media before the problem spreads further and public trust in the press deteriorates.
Paragraph 2
Data poisoning, the technical issue Nezar highlighted, occurs when an AI model learns from wrong data, whether because of accidental contamination, poor data collection, or deliberate interference. In a newsroom context, a journalist might ask an AI assistant to summarise a topic, find sources, or draft a story. The AI searches its training data—which may include blogs, social media posts, unverified websites, old news reports, or even fabricated documents—and returns a response that appears coherent and factual. But if the underlying data was corrupted or intentionally poisoned, the AI’s output can be subtly inaccurate or completely false. Worse, the model often presents its response with confidence, making it difficult for a busy reporter to detect errors. Nezar pointed out that many journalists are now using AI without realizing how deeply flawed the underlying databases can be. When the source data is contaminated, even a small mistake can be amplified across multiple articles, especially if those articles are then used by other AI systems as references. This creates a feedback loop of misinformation: AI writes an article based on bad data; other AI tools read that article and treat it as fact; eventually, a completely fictional narrative becomes embedded in digital archives and appears across the media landscape. Journalists who skip traditional verification steps are particularly vulnerable to this effect. Without direct observation, without interviewing primary sources, and without cross-checking facts, there is no safety net to catch errors generated by an algorithm. Nezar’s message is that AI should be treated as a tool that requires human oversight, not as an autonomous truth machine. In the rush to embrace new technology, the media industry cannot afford to forget that machines do not understand truth; they merely repeat patterns.
Paragraph 3
The core of Nezar’s concern goes far beyond technical malfunctions. It involves the fundamental principles of journalism, particularly the commitment to truth that is enshrined in journalistic codes of ethics around the world. He reminded the audience that journalists have always been expected to go out into the world, observe events directly, interview sources, cross-check information, and provide context. This process of verification is what separates journalism from rumor or fabrication. With AI, however, the entire workflow is transformed. Instead of a journalist traveling to a location, speaking to witnesses, or requesting official documents, the AI does the so-called research in a matter of seconds. It pulls together pieces of information from various sources and writes them in a fluent, organized, and convincing style. The danger is that this text lacks the most important element of professional journalism: responsibility for the truth. A human journalist can be held accountable for errors, can be asked to provide evidence, and can defend the reasoning behind a story. An AI system cannot do any of that. It simply looks for patterns in language and data Resources. Nezar noted that the era of AI therefore challenges the most fundamental principle of journalism, which is the worldwide commitment to reporting the truth. As he put it, every journalist’s code of ethics places truth above all else, and any technology that weakens the link between reporting and verification threatens the very foundation of the profession.
Paragraph 3
The deputy minister’s concern also reflects a broader transformation in how news is gathered and consumed. In the past, journalism relied on a clear process: a reporter goes into the field, observes an event, talks to witnesses and experts, verifies claims, and then writes a story that has been checked and refined by editors. This process was slow, labor-intensive, and expensive, but it was also what made journalism a trustworthy profession. Today, however, economic pressures and digital competition have driven many media organisations to seek faster and cheaper ways to produce content. AI seems to offer a perfect solution. It can generate summaries, compile background information, and even write full articles in seconds. But such efficiency comes with an enormous cost if the output is not properly scrutinised. Nezar warned that the growing use of AI without verification is already causing journalists to abandon the discipline of direct reporting. Instead of going out to interview witnesses, visit locations, and confirm facts, some reporters rely on AI-generated summaries from secondhand sources. In so doing, they are not only risking inaccuracy but also losing the journalist’s unique ability to provide context, insight, and original reporting. Furthermore, the public cannot easily tell whether a story was produced by a human who did the work or by a machine that rehashed unverified information. This ambiguity can be exploited by bad actors who want to spread propaganda, manipulate public opinion, or simply profit from fabricated stories. The warning from Indonesia’s deputy minister is therefore not merely a technical observation; it is a call for the media industry to reconsider what journalism means in an age of automated production.
Paragraph 4
In response to these emerging risks, the Indonesian government is encouraging journalists to treat AI with caution and responsibility. Nezar revealed that the Ministry of Communication and Digital Affairs has already issued a circular concerning the ethical use of artificial intelligence LE. This circular is intended to provide guidance to public institutions and media organisations on how AI should be adopted without sacrificing accuracy, fairness, and accountability. Importantly, Nezar also pointed to the Press Council, which has started to formulate guidelines for journalists who use AI tools. These guidelines will help define what constitutes acceptable and unacceptable use, and will remind journalists that they cannot delegate their professional judgment to machines. The goal is to ensure public information remains accurate despite the expanding role of automation in the media. Nezar framed the issue as one of protecting people from misinformation and disinformation Illustratively. If AI-generated content misleads the public, the consequences can be severe: public health risks, social division, and the widespread erosion of trust in institutions. The government’s push for ethical AI use is therefore tied to the protection of democratic discourse and social stability. He also called on journalists and media companies to be transparent about their use of AI tools, to adopt clear editorial policies, and to follow the guidelines established by the Press Council, which has been asked to provide specific standards for AI use in newsroomsinals. Such steps, he argued, are necessary to ensure that the same technology undermining journalism’s credibility can be redirected toward protecting it.
Paragraph 4
The Indonesian government has already taken formal steps to respond to this challenge. The Ministry of Communication and Digital Affairs has issued a circular addressing the ethical use of artificial intelligence, and it has directed journalists to follow the guidelines prepared by the Press Council. This regulatory approach recognizes that AI is not inherently harmful, but its application must be guided by clearly defined ethical boundaries. Journalists are expected to use AI tools responsibly: to assist with language translation, background research, or formatting, but not to replace reporting, interviewing, and source verification. The circular also stresses the importance of transparency. Media organisations should disclose when and how AI has been used in the production of content, and they should maintain human oversight to correct errors and prevent harmful outputs. Nezar underlined these points during his remarks, saying that the government’s priority is to protect the public from misinformation, disinformation, and hoaxes that can spread quickly through generative AI platforms. His message aligns with broader international efforts to regulate AI in the media sector. Around the world, news regulators and professional bodies are developing ethical codes for AI adoption, while some major outlets have established internal rules prohibiting the publication of AI-generated content without rigorous human review. Indonesia’s approach, through the Ministry of Communication and Digital Affairs and the Press Council, is part of this global effort to balance innovation with accountability. The government’s position is not that AI should be banned from newsrooms, but rather that its use should be transparent, ethical, and subject to the same professional standards that have always governed journalism. By publishing guidelines, the ministry is sending a clear message: AI is a tool, not a source of authority. The final responsibility lies with human editors and reporters.
Paragraph 5
The issue of data poisoning has implications beyond individual news stories. It affects public trust in the media as a whole, and it poses a serious challenge to democracy. When AI-generated misinformation spreads rapidly, people may find it increasingly difficult to distinguish between what is real and what is fabricated. This not only hurts news organisations, which can lose credibility when false information is attributed to them, but it also weakens the public sphere, where shared facts are crucial to democratic debate. Nezar’s comments should therefore be understood not simply as a technical warning, but as a broader call to reconsider the way society handles information in the age of automation. The problem is compounded by the fact that AI systems often have no way of indicating confidence or uncertainty clearly. A model may present a guess as if it were a fact, and the smoothness of the language makes it difficult to notice mistakes. Even more dangerously, malicious actors can deliberately manipulate the data used to train AI models, inserting falsehoods into a system and causing it to produce disinformation on a massive scale. This is a national security issue as much as a media issue. Governments, journalistic associations, and tech companies must therefore work together to develop standards that protect the integrity of information. This includes creating transparent datasets for training AI systems, establishing strict accountability mechanisms for AI tools used in newsrooms, and investing in media literacy so the public can critically assess information. Nezar’s remarks serve as a reminder that the advance of artificial intelligence must not run ahead of the ethical frameworks that govern its use. Technology is not neutral; it carries the biases and mistakes of the data it processes. If the media cannot ensure the accuracy of the data that feeds its systems, then the entire information ecosystem is at risk.
Paragraph 6
In conclusion, Nezar Patria’s warning about AI data poisoning is a call for a more responsible approach to technology in journalism. The temptation to rely on AI for speed and efficiency is understandable, but it can never justify the abandonment of the core journalistic duty to seek and report the truth. The government’s guidance urging the public and journalists to verify AI-generated information represents an important first step, but it is not enough on its own. Journalists must remain actively engaged in the real world: interviewing people, observing events, questioning official accounts, and checking sources. Media organisations must develop clear editorial policies for the use of artificial intelligence, including rules about disclosure, accountability, and human review. Technology developers must also take responsibility for the quality and transparency of their datasets, and regulators must continue to monitor the impact of AI on public discourse. The challenge is not to reject AI completely—that would be impractical and perhaps impossible—but to ensure that its use is guided by the same standards of accuracy and fairness that have always defined good journalism. Nezar’s warning serves as a reminder that the future of news depends not on algorithms but on human judgment. If data poisoning and misinformation are allowed to spread unchecked, the public’s ability to trust what it reads, sees, and hears will be severely damaged. On the other hand, if journalists adopt AI carefully, with clear rules and robust verification processes, the technology can help them reach new audiences and uncover stories more effectively than ever before. The key is to keep the journalist, not the algorithm, in charge of editorial decisions.
Paragraph 6
Ultimately, Nezar Patria’s message is one of caution, not rejection. Artificial intelligence is not going anywhere, and newsrooms across the world are only likely to rely on it more heavily in the coming years. The challenge facing the media industry is to integrate these powerful tools without sacrificing the human judgment, ethical standards, and public accountability that give journalism its purpose. The deputy minister’s call for journalists to follow the ethical guidelines set out by the Press Council is therefore a reminder that professional standards still matter, even in the age of sophisticated machine learning. The government, for its part, says it is committed to ensuring that AI is used responsibly across the digital ecosystem SQUAD. Digital platforms and artificial intelligence companies also carry responsibilities: they must be transparent about the limits of their systems, allow researchers to examine how models behave, and improve safeguards against harmful outputs. Nezar’s warning is not a call for panic or a rejection of technological progress; rather, it is an invitation to think carefully about how AI can serve journalism without destroying it. If used properly, AI could help journalists analyse large datasets, sort through public records, and identify trends that would otherwise remain hidden. But if used carelessly, it could spread misinformation at a speed and scale never seen before. The future of news depends on the choices being made today by governments, media organizations, journalists, and the public. The deputy minister’s message is simple but profound: information, especially in a democracy, must be verified, transparent, and rooted in reality. AI cannot be allowed to replace that principle with a system of plausible but false narratives. Protecting the truth is not just a professional obligation; it is a public good, and in the age of artificial intelligence, protecting it requires vigilance from everyone involved in producing and consuming news.
