{"id":22681,"date":"2021-03-12T10:50:00","date_gmt":"2021-03-12T10:50:00","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/ai-journalism-possibilities-limitations-and-outcomes\/"},"modified":"2023-08-30T11:56:46","modified_gmt":"2023-08-30T11:56:46","slug":"ai-journalism-possibilities-limitations-and-outcomes","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/ai-journalism-possibilities-limitations-and-outcomes\/","title":{"rendered":"AI Journalism: Possibilities, Limitations, And Outcomes"},"content":{"rendered":"\t\t
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Microsoft made waves this May when it announced that it would lay off more than 50 journalists and editors<\/a> from its workforce. Many of these employees were involved in the news curation process, selecting hand-picked content that would run on the Microsoft News and MSN websites. But their positions won\u2019t go unfilled for long: Microsoft is expected to replace them not with new hires, but with AI software that can identify trending and interesting articles, essentially performing their old job function.<\/p>\n

But curation is just one task that AI \u201cjournalists\u201d can now accomplish. Kristian Hammond, a computer science professor and co-founder of the data storytelling company Narrative Science, predicted in 2012 that in 15 years, more than 90 per cent of news articles<\/a> would be written by a computer. With 7 years to go until the deadline, however, we\u2019re still very far off from this forecast \u2014 yet also much closer than we used to be, as we\u2019ll discuss below.<\/p>\n

The good news for human journalists is that there\u2019s still very much a need for their services when writing articles like this one. But with machines<\/a> now capable of doing more tasks than ever (and more complex ones), we face several important questions: what\u2019s the role of AI in journalism, and what are the challenges and considerations when bringing AI into the newsroom?<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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What\u2019s the current state of AI journalism?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine-written articles<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Starting in the past several years, AI journalists have been able to write \u201cplug and play\u201d articles that don\u2019t require independent research. For example, below is the opening paragraph from an AI journalist\u2019s article on a college basketball game<\/a>, created by the natural language generation platform Wordsmith in 2015. There\u2019s little indication that the piece wasn\u2019t written by a human hand:<\/p>\n

UNC beats Louisville 72\u201371 on late Paige basket<\/em><\/strong><\/p>\n

Led by a Paige game-winner, North Carolina defeats Louisville 72\u201371<\/em><\/p>\n

CHAPEL HILL, N.C. \u2014 Marcus Paige scored with nine seconds remaining in the game to give North Carolina a 72\u201371 lead over Louisville. The Heels held on to win by that same score following a missed 3-pointer by Wayne Blackshear and an unsuccessful second-chance attempt by Terry Rozier.<\/em><\/p>\n

For now, AI-written articles are limited to relatively simple and formulaic topics: stock market results, M&A announcements, sports game scores, etc. Bloomberg News, for example, uses an AI system called Cyborg<\/a> that automatically scans companies\u2019 quarterly reports and then outputs a quick article with the most relevant information.<\/p>\n

Anything more complicated than this is out of reach for now \u2014 at least if journalists want to publish stories that won\u2019t put them at risk<\/a> of a defamation lawsuit. Language models such as GPT-3<\/a> have created a buzz for their ability to synthesise several paragraphs of highly realistic English text, but there\u2019s no guarantee that the content they generate has any basis in reality.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Assisting human journalists<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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When AI isn\u2019t writing articles itself, it can also help human reporters with work that\u2019s too intricate for it to handle, such as long-form articles, in-depth analyses, and investigative journalism.<\/p>\n

One tremendously valuable AI use case: automated transcription of interviews, which can save human journalists untold hours of grunt work. While the results of AI transcription are rarely flawless, the few errors that the software does commit can easily be corrected by a human editor.<\/p>\n

For example, the automated speech-to-text service Trint<\/a> was founded by former TV news reporter Jeff Kofman. Trint closed a $4.5 million funding round in April 2019<\/a> and counts the Associated Press and Google Digital News Innovation Fund among its investors. The transcriptions output by the Trint platform are automatically mapped to the source audio or video, allowing journalists to easily search for specific content. According to Kofman, the software can deliver accuracy rates of 95 to 99 per cent for relatively clean audio within just a few minutes. I used Trint a lot during my PhD and it saved me a lot of time.<\/p>\n

AI technology can also identify interesting trends and developments that are worthy of investigation by human reporters. In 2018, Forbes<\/em> rolled out a new AI-enabled content management system called \u201cBertie\u201d<\/a> that recommends possible article topics and headlines to contributors, based on their previous work. Thus far, the experiment seems to have been a success: according to Forbes, the number of loyal visitors (i.e. those who visit the Forbes<\/em> website more than once a month) doubled in the months after Bertie\u2019s rollout.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Curated content for users<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Not only is AI affecting the news that gets written, but it is also controlling the articles that people see as well, as we\u2019ve seen with Microsoft\u2019s decision to use AI news curators.<\/p>\n

It\u2019s well-known that the Facebook news feed algorithm suggests (what it believes to be) the most relevant content to users, based on the pages they\u2019ve liked and their previous interactions on the platform. Similarly, AI technology can keep track of the articles that subscribers visit on a news website, learning about their behaviour and preferences (e.g. how much time they spend reading each article).<\/p>\n

The more a news outlet knows about its customers, the more relevant content it can display on the website or in a weekly newsletter, delivering a personalised experience that helps encourage user interaction and discourage attrition. According to a 2019 survey by the digital media company Digiday, 70 per cent of digital publishers<\/a> say that they personalise content for visitors.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Some examples of content personalisation in journalism include:<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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