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The rise of automated journalism powered by artificial intelligence is transforming the news industry. News organizations are increasingly utilizing AI systems to generate articles, especially for things like financial reports, sports recaps and weather forecasts. These robot-written articles are now regularly published by mainstream outlets like the Associated Press, Washington Post, Bloomberg and more.
By leveraging natural language processing and machine learning, algorithms are able to take structured data and turn it into narrative text indistinguishable from human writing. The Washington Post uses an AI system called Heliograf to publish stories on election results, Olympics updates and local news. The system can churn out upwards of 700 articles a day without human intervention.
While employing algorithms to write news stories raises ethical questions, proponents argue there are several benefits. AI systems can scale reporting in a rapid, low-cost way that augments human journalists. Automated journalism expands newsrooms" capabilities and frees up reporters for more complex investigative work.
Algorithms also enable greater personalization in news consumption. Through data analysis, publishers can better understand readers" preferences and tailor content accordingly. For instance, Quartz developed an AI system called Quartzy that sends subscribers a daily email newsletter with customized news recommendations based on their interests.
The Associated Press uses automation to deliver localized articles to partner news outlets. With infinite scale, the AP can produce a high volume of hyperlocal content without added human resources. This allows news providers in small communities to access locally relevant AP stories at little cost.
The advent of automated journalism has been a polarizing development in the news industry. While some see it as an inevitable progression of technology that can augment human skills, others argue it devalues the core tenets of journalism. Regardless, algorithmically generated news content is gaining significant traction.
The Associated Press began automating quarterly earnings reports in 2014 and now produces over 3000 financial articles per quarter through automation. The Washington Post utilizes a tool called Heliograf to autonomously publish stories on election data, sports game recaps and other topics with structured data inputs. The Los Angeles Times uses an internal automation technology to quickly generate earthquake reports.
Many local news providers are also turning to automated journalism to help fill gaps left by newsroom layoffs and budget constraints. For example, the Norwegian company Mediabots supplies automated municipal news coverage to local outlets lacking resources for robust community reporting. In the U.S., companies like Narrative Science, Automated Insights and OnlyBoth create machine-written articles for partner publishers.
Proponents of automated journalism highlight a number of potential benefits. Algorithms can scale simple reporting tasks like sports scores, weather recaps and company earnings at higher volumes with more speed and lower costs. This frees up human journalists" time for deeper investigative work and impactful local reporting. Technologies like natural language generation also allow newsrooms to tailor and personalize content for different audiences.
Critics counter that automating reporting shortcuts journalistic values. They argue algorithms lack human judgment in newsgathering, cannot build trust with sources and audiences, and fail to provide nuanced perspectives. Some view automated journalism as a slippery slope towards eradicating human reporters altogether.
Nonetheless, outlets like the Associated Press maintain automated reporting still requires oversight from experienced editors and journalists. Algorithms generate drafts, while humans refine story structures, verify facts and add analysis.
As automated journalism expands, news organizations are focusing on finding the right balance between human and machine. The Seattle Times" Project Rainier combines AI content creation with in-depth human reporting on issues like homelessness and addiction. Quartz trains algorithms on its existing reporting and leverages automation to help journalists pitch better data-driven stories.
Once viewed as a novelty, articles written entirely by artificial intelligence are now regularly published by some of the world's leading media outlets. Major publishers like The Washington Post, Associated Press, Bloomberg, The Guardian, Forbes and Wired now use AI systems to automatically generate articles, particularly for niche topics like sports results, financial earnings reports and localized news.
The Associated Press publishes upwards of 3,000 automated earnings stories every quarter through a system developed with Automated Insights. The stories are indistinguishable from those written by human reporters. The Post's Heliograf technology churns out as many as 850 automated local news articles per day with no human intervention. Mainstream adoption of AI content has been rapid. Just a few years ago, automated journalism was relegated to experimental sidelines. Now it powers a significant share of certain news beats.
Proponents argue AI publishing augments human capabilities and expands the reach of reporting. Algorithms can quickly scale simple beat reporting that would be onerous for humans to manually produce in such high volumes. This frees up newsrooms to reallocate resources towards high-impact investigative and local journalism. It also allows publishers to efficiently customize and localize content for different audiences.
Forbes uses an AI system called Bertie to generate rough drafts of articles, which human journalists then refine and finalize before publication. According to Forbes, this workflow allows their reporters to be more productive. The Los Angeles Times claims its earthquake bot provides critical public safety information faster than any human reporter could.
However, many argue automated journalism threatens journalistic standards. They contend algorithms lack skills like interviewing sources, making sound news judgments and providing analysis. Critics also point to the risk of bias in artificial intelligence's training data. Some believe AI publishing could displace human journalists.
Yet outlets emphasize ensuring ethics and quality with layers of human oversight at key points in the automated content process. Humans select story themes, angles and sources, while also reviewing and editing machine-written drafts prior to publication. The Seattle Times blending of community-focused human writing and AI content creation is one model aiming to balance automation and journalistic values.
Once solely the domain of human reporters, bylines are increasingly being granted to the automated journalism systems generating more of the content published by news outlets today. Systems like The Washington Post"s Heliograf, The Associated Press" Wordsmith and The Los Angeles Times" Quakebot routinely receive byline credit for articles written without any human authorship.
Proponents argue algorithmic bylines promote transparency on the origin of news content. Given sophisticated natural language capabilities, machine-written stories can be indistinguishable from human reporting. Bylines help clarify when automation is used and prevent audiences from being misled. At The Washington Post, Heliograf articles include the tagline "this article was produced by a computer algorithm."
Granting bylines to AI also reflects the significant editorial work algorithms do beyond merely transforming data into text. Tools like Wordsmith and Quakebot incorporate elements of newsworthiness judgments, language polishing and story framing traditionally seen as hallmarks of human journalistic skill.
Additionally, algorithmic bylines can signal the cost and time savings automation provides newsrooms. The Associated Press highlights its Wordsmith authored earnings reports as a way to showcase expanded productivity from AI. The Washington Post emphasizes how many local election stories Heliograf writes compared to being manually produced.
However, critics argue bylines should be reserved exclusively for human authors who bring creativity, accountability and credibility. They contend algorithms lack true reporting skills like interviewing, investigating and analyzing that merit byline credit.
Detractors also point out how anonymizing automation removes transparency about human oversight and accountability. Outlets using unnamed algorithms make it unclear the extent of human editing on machine-written drafts. This opens the potential for errors or biases going unchecked.
Some compromise by only partially crediting automation tools in contributor lines rather than official bylines. Quartz"s newsbot is named as a contributor, while human co-authors get the byline. The Seattle Times credits Project Rainier as a "special reporting project" rather than an author.
As consumers increasingly demand personalized and relevant content catered to their interests, news organizations are turning to artificial intelligence to customize the news experience for each reader. Rather than taking a one-size-fits-all approach, publishers now have the ability to algorithmically tailor articles, newsletters, notifications and more for every individual user.
For many readers, generic news bundles featuring the same top stories for everyone simply don"t align with modern expectations for a personalized media diet. "I don"t want to just passively receive whatever news a publication decides to funnel out," said Lisa Chen, an avid news consumer. "I want my news tailored to the topics I care about, like tech and politics, not sports."
To serve readers like Chen, outlets like The Washington Post, New York Times and Wall Street Journal use data science to understand each subscriber"s preferences based on their engagement with content. User interest profiles guide AI systems to recommend customized mixes of articles to align with what will resonate most with each person.
"The AI is shockingly good at learning my interests," said James Wu, a Wall Street Journal subscriber. "My Top News email has the perfect blend of business and tech news for me. It exposes me to great Journal reporting I would have missed in the past." For publishers, tailoring news to user interests also drives subscription retention. According to the New York Times, readers are over 40% more likely to regularly engage with the Times after signing up for its customized "For You" experience.
Beyond news personalization, publishers also utilize AI to customize article presentation and formatting based on user behavior. For example, Quartz trains algorithms to shorten or lengthen individual stories based on a user"s reading speed and habits. This ensures readers don"t encounter frustratingly long-winded articles or feel deprived of details.
"I never feel overwhelmed reading Quartz articles like I do elsewhere," said Maxine Lui, a Quartz subscriber. The AI-powered experience is a big reason I"ve stuck with their news product."
While customization presents exciting opportunities for publishers and readers, it also raises questions about filter bubbles and divisiveness. Critics argue hyper-personalized news risks limiting exposure to diverse topics and viewpoints. However, outlets emphasize human oversight and judgment is still crucial in automated news curation. Plus, interest-based recommendations can also introduce readers to a wider range of previously undiscovered material from across an entire publication.
News publishers are increasingly using artificial intelligence and advanced data analytics to tailor content to each reader's specific interests. This level of personalization provides a more engaging, relevant news experience for consumers compared to the traditional one-size-fits-all approach.
"I used to get frustrated sifting through a generic news feed full of stories I didn't care about," said Lisa Chen, an avid news reader. "Now, with publishers like the New York Times tailoring content for me, I can instantly find articles on my interests like tech, food and fashion without all the clutter."
For publishers, algorithms that can analyze user behavior and preferences allow them to serve customized content to each subscriber rather than taking a scattershot approach. Readers are more likely to regularly engage with news that consistently aligns with topics they care about.
James Wu, a Wall Street Journal subscriber, has seen his interest in business news gratified through personalized curation. "The WSJ mobile app recommends great relevant articles every morning based on what I've read previously," he said. "It really caters to my niche."
Tailoring content to individuals has led to major retention gains for publishers. Data from the New York Times shows subscribers who engage with its customized "For You" experience are over 40% more likely to stick with the Times long-term. The Washington Post and The Economist have also succeeded in reducing subscriber churn through AI-driven personalization.
For Maxine Lui, a subscriber to the Quartz news app, personalized article lengths retain her attention. "Quartz uses AI to shorten or expand stories based on my reading habits," she said. "This prevents me from encountering annoyingly long articles that lose my interest."
While interest-based content tailoring provides many benefits, critics argue it also has risks. They contend personalized news feeds create "filter bubbles" where readers only encounter perspectives and topics that align with pre-existing views. However, outlets like the Wall Street Journal say human editorial oversight prevents true bubble formation.
"Our editors closely monitor the algorithms to ensure recommendations have diversity," said WSJ Digital Editor Michelle Kung. "Readers still get exposures to a wide range of content, including opposing viewpoints."
Additionally, publishers highlight how interest-based AI can actually expand exposure by surfacing relevant niche content a reader may have otherwise overlooked. For Chen, algorithms help her discover tech stories she would have missed in the past.
As newsrooms increasingly adopt artificial intelligence technologies, data is playing a greater role in determining the angles and narratives journalists pursue in their reporting. By analyzing massive datasets, algorithms can surface insightful stories that speak to larger trends and issues impacting society. This data-driven approach to uncovering news is transforming how publishers discover and develop impactful stories worth investigating.
At the Associated Press, machine learning algorithms mine data on state legislative activity across the U.S. to flag proposed bills that align with the AP"s standards for national newsworthiness. This allows AP reporters to quickly identify important public policy issues brewing nationwide and localize stories for partner news outlets.
"The data helps us spot national themes bubbling up from state legislatures that we may have missed in the past," said Serdar Tumgoren, an AP editor. "It lets us be more proactive with our statehouse reporting."
The Los Angeles Times has developed a "seismic swarm" detector algorithm that continuously analyzes earthquake activity data from sensors across Southern California. When the system detects a cluster of tremors that could signify elevated risk, it alerts Times journalists to start preparing localized stories ahead of time to better inform affected communities.
"The AI helps us get ahead of earthquake swarms so we can publish critical public safety information faster," said Times reporter Rong-Gong Lin II. "We"ve cut our reporting time almost in half."
For investigations, algorithms can crucially point journalists to promising leads worth digging into from vast document troves and datasets. At the Wall Street Journal, a team used natural language processing algorithms to comb through thousands of brokerage firm records and identify advisers with high misconduct rates for an investigative series.
"The AI was like having an army of assistants helping uncover stories in a haystack of documents," said WSJ reporter Anne Tergesen. "It enabled us to quantify systemic issues plaguing the advisor industry."
However, journalists emphasize that data should complement, not replace, human judgment in determining news angles and narratives. While algorithms excel at spotting factual patterns, it takes human discernment to ask probing questions and place findings into meaningful context.
News organizations are increasingly turning to artificial intelligence to automate routine journalistic tasks in order to free up resources for more meaningful work. Tedious beat reporting that merely transforms structured data into narrative can now be handled entirely by algorithms. This allows publishers to reallocate human reporters to tackle more complex assignments requiring critical thinking and analysis.
According to the Associated Press, its Wordsmith automation technology allows just one staff journalist to produce around 3,000 quarterly earnings stories. This volume could only be matched by a team of human reporters, requiring significant time and labor. The AP emphasizes that automation enables its journalists to focus on enterprise and investigative projects rather than churning earnings recaps.
The Washington Post adopts a similar approach with its Heliograf tool for generating localized news articles on topics like sports game summaries and election results. Post editors note Heliograf can compose stories on demand at a volume human reporters couldn"t possibly match. This provides important expansions of the Post"s coverage capabilities without added staffing needs.
At the Los Angeles Times, an algorithm called Quakebot takes just three minutes to publish an article on seismic events using data from earthquake sensors. According to seismology reporter Rong-Gong Lin II, no human could report and write that fast. Quakebot enables the Times to deliver urgent public alerts far quicker than before.
Forbes uses an AI content creator called Bertie to develop rough drafts of certain articles that are then polished by a staff writer prior to publication. According to Forbes Media chief product officer Mark Howard, Bertie provides a volume and speed boost that increases reporters" overall productivity. "It"s about scale," said Howard.
The Seattle Times developed a tool called Project Rainier that generates localized versions of stories to expand access to the Times" reporting among community news providers across Washington state. Expanding coverage manually would have been cost-prohibitive.