As part of the recent INMA South Asia News Media Festival, I recently spent I spent two days on a study tour of more than half a dozen publications and then two days at the conference, hearing about the different, innovative ways in which AI is being used in Indian news publications and about the challenges that they are facing. 

Here are two case studies I saw while there.

Times Internet hopes AI will give it a Twitter vibe

Times Internet, the digital arm of the giant Times Group, is looking at AI for the algorithmic distribution of content so each of its 270 million users is served a personalised mix of content on the homepage, based on their profile. 

In an era where search and social referrals are increasingly uncertain, Times Internet is working towards a goal of driving sustained loyal, direct traffic. For the past two and a half years, it has been building a self-learning, probabilistic model that is constantly detecting patterns and which understands certain topics have a longer shelf life than others.

“We all go to Twitter several times a day because the homepage is constantly changing. That is the experience we want to imitate,” Ritvvij Parrikh said. 

The system does not favour popular or trending content, or more recent articles, as editors tend to. Older content is often surfaced, with favourable results.

The algorithm has produced sustained improvements over the past 18 months, indicating it is not just a flash in the pan, Parrikh said. Times has managed to double its click-through rate compared to the manual placement of content.

Editors still place the top two stories and can override the algorithm. About 35% to 40% of traffic comes from the homepage.

Wouldn’t the cost of computation be prohibitive? Parrikh pointed to methods to keep inference very cheap and said they were relying on compression to use as little data and computation as possible, but also indicated the project had a long runway for cost recovery.

Times Internet is also finding money in GenAI, which it uses to convert content from one format to another, such as text-to-Web stories. A good Web story brings in 50,000-60,000 users, who can be monetised — and it cuts the editorial team’s effort by a third when measured in minutes. Editors still pick the best photographs for the Web story.  

“We have very consciously not removed human effort from it,” said Prasad Sanyal, business head at Times Internet, underscoring the importance of keeping a human in the loop in content creation. “It does the mundane, searching for 20 images for editors to choose from. This frees up editors for higher-order functions.

“The idea is that we are increasing reach with the least amount of incremental newsroom effort.”

HT Media is investing heavily in AI in the newsroom

HT Media, another Indian publishing giant, is also using AI across its newsroom in different ways:

• The complete automation of some content, such as blogs on stocks and commodities, as well as on weather and pollution levels.

• Automation to augment editorial capabilities for tasks such as translation, transcription, large document analysis.

• Automation to help editors with coverage:

  • This includes a content prioritisation process that tracks what is trending on Google and runs an algorithm that looks at how much traction HT gets from different keywords that are trending. It calculates a score that is sent to editors, who then create stories and keep monitoring the yield on the stories, as well as the competition and speed of publication.

  • AI also monitors content quality for HT. It identifies key factors of content quality (such as the use of active voice vs passive voice), monitors trends, and then provides suggestions to editors via dashboards. 

What is on their road map? 

HT plans to work on using AI more deeply for monetisation and subscriptions, as well as increasing engagement on its live blogs. It also plans to experiment with text to video.

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