Journalism Needs AI to Stay Relevant
Yesterday, Microsoft announced collaborations with several news organisations to equip their journalists with learning how AI tools work. The training workshops will help scribes at Semafor, The GroundTruth Project and other media outlets improve their reporting, research and writing. According to a recent survey by the London School of Economics, AI is already an integral part of a journalist’s work day with a majority of respondents using AI one way or another. Instead of turning to third parties, larger organisations are building their own AI systems. The New York Times recently announced that it is prototyping the uses of generative AI and other machine learning techniques to help with reporting. Interestingly, last week, NYT posted job listings for both engineering and editorial roles. Apart from them, Bloomberg, Reuters, BBC, and a few others have been using AI models as better research tools for their journalists, and to analyse consumer engagement behaviour, streamline workflows, etc. The organisations use an NLP library for low-level text resolution tasks, such as tokenisation, chunking and parsing and even for a sentiment analysis of the article. For example, Reuters uses AI to generate automatic alerts on financial news. “These real-time alerts allow our customers and journalists to have the most up-to-the-minute information,” said its official blog. These organisations have also come together to draft guidelines for journalists using the AI tools effectively without compromising the quality of their work. Many startups are also building sites that quickly summarise news, like Infobot.ai, which is AI turning unstructured data like city council transcripts, crime reports, and expert interviews into easy-to-read news stories. While the larger companies are experimenting, startups are struggling to find their feet in this new(s) space. “One way or another news sites must equip themselves with AI tools to retain their readerbase,” said Rotem Weiss, the creator of GPT-Newspaper, an open source project that scrapes different news websites and collates the information to provide different opinions. The future of news No one wants to be left behind. NYT is suing OpenAI for scraping their data and yet is enthusiastic about building its own AI applications. In October last year, BBC, which formerly blocked OpenAI from scraping its sites, announced that it was “starting a number of projects that explore the use of GenAI”. While some of the larger organisations are trying to preserve autonomy, the others like Axel Springer and Associated Press have partnered with OpenAI. “There is an even stronger case for payments to be made for any LLM results related to current affairs,” explained Anya Schiffrin, director of media program at Columbia University. She added that there is no way generative AI can provide results on current affairs without taking input from news publishers and there should be payment for legacy information written by journalists. Most news sites work on a subscription model or run advertisements, so they wouldn’t want readers to go elsewhere for the same information. Currently, OpenAI is accused of undercompensating the news publications to scrape their sites. Apart from that, it would be hard to trust third-party services because of hallucinations and the fear of incorrect information. “The responsibility lies with the journalist and it is good in some ways that AI is in-house and they’re testing the capabilities and using it with caution,” Weiss added. Humans vs AI While larger companies hold themselves to a journalistic standard written by humans, it is difficult to maintain the same with a news source generated by AI. GPT-Newspaper was born out of a partnership between Tavily and LangChain.“The idea here was to show the potential of a new approach to consuming news,” said Weiss. This, however, is an idea in its infancy, he stressed, saying, there are multiple hurdles in actually implementing such a project. “One is the issue of compensation and the other more important one is avoiding hallucinations or errors. It is one of the reasons why startups in the journalism space take time to really succeed.” Artifact, a personalised news feed that shut down last month, used machine learning to understand readers’ interests. Founded by Kevin Systrom and Mike Krieger, the former founders of Instagram, Artifact was forced to shut down due to low engagement. They weren’t alone, Smartnews, a similar platform, is also struggling to retain users. According to a Statista report, people do not trust AI-generated news. The report also highlights that social media is the least trusted news source globally since 2016. “Despite all the issues, AI delivered many useful, time-saving tools that, if used correctly, will make you a more-efficient journalist,” posted World Editors Forum on X. Trusted media companies need to keep up with the developments because though these technologies are mere tools, they help journalists do their jobs better. The companies are embracing AI, touching every level from educating journalists to leveraging AI for trend analysis. The motivation is clear – to remain competitive and relevant in an era where speed and accuracy are paramount. Media outlets, which hesitate to integrate AI, risk losing their audience to more technologically adept rivals.
The future of journalism hinges on embracing AI, blending technology with ethics to redefine news in the age of information.
The future of journalism hinges on embracing AI, blending technology with ethics to redefine news in the age of information.
["Bloomberg", "ethics", "journalism", "opensource"]
["GenAI", "machine learning", "OpenAI", "AI", "sentiment analysis", "ML", "RAG", "journalism", "NLP", "Bloomberg", "LangChain", "opensource", "generative AI", "ethics"]
["AI", "machine learning", "ML", "NLP", "generative AI", "GenAI", "OpenAI", "LangChain", "RAG", "sentiment analysis"]
K L Krithika is a tech journalist at AIM. Apart from writing tech news, she enjoys reading sci-fi and pondering the impossible technologies, trying not to confuse it with reality.