INMA Global Media Awards entries give look at current GenAI case studies
Generative AI Initiative Blog | 01 April 2024
I went through the submissions for the INMA Global Media Awards, where there are 52 different use cases from news publishers using AI. All but 10 of them use generative AI. Of the 42 remaining entries, here’s a look at how they can be categorised:
Editorial: The submissions overwhelmingly targeted editorial purposes: 33 of the entries relate to newsroom products or functions.
19 were for making internal workflows more efficient or effective.
14 were for creating external, customer-facing products.
Customer service: Three were related to smarter ways of undertaking customer service — either to learn about customers or to interact with customers.
Advertising: Three targeted advertising.
Marketing: Three were for marketing campaigns
As you can see, most news publishers are gravitating towards ways to help their journalists do their work more easily. What’s interesting is that there is no cutting of corners here: You can see the finalists are particularly thoughtful about addressing the risks that accompany AI.
For example:
Rather than letting deep-seated cultural fears derail their innovation process, Omni focused on the importance of getting journalists on board by letting them design the GenAI tools.
Ippen Digital even invited journalists to spend two weeks on its AI team co-creating the tools.
Hearst Newspapers built in a peer-review process — deliberately creating friction with its AI tool to ensure journalists think carefully about how they are using it rather than just automatically ticking boxes.
(Note: I am not involved in judging these awards, so these comments are not an indication of who is going to win. We’ll both find out who wins on April 25 in London at the INMA World Congress of News Media.)
Need more inspiration? Here are some cool projects that are underway as part of the JournalismAI initiative. The dominant theme appears to be using GenAI for extracting stories from data for investigations. Also: building chatbots.
- AURA: Advanced Understanding and Research Assistant: a conversational AI platform designed to help journalists navigate and extract stories from complex unstructured data, offering instant context and investigative leads.
- Know Your Leader: An Al-powered chatbot that lets the public track political speech, comments, and opinions.
- IntelliNewsComparer: Uses machine learning to semantically compare text documents in English, Finnish, and Tagalog via pre-trained LLMs and a user-friendly interface for querying document similarities. It can expedite the examination of documents in investigative newsroom projects.
- CheckMate: A simple Web app for real-time fact-checking on live or recorded video and audio broadcasts to identify and debunk false claims and enable newsrooms to actively work to prevent the spread of misinformation over a significant election year.
- Real Estate Alerter: Harnessing anomaly detection methods and LLMs to uncover hidden news stories within real estate data, creating an alert system, which provides reporters with a head start on newsworthy stories.
- StyleCheck: An AI-driven tool to check adherence of articles with the newsroom’s style guide, integrated with a cleanup tool for article copy.
- Data Robot AIde: An open framework for data-driven and LLM-powered AI chatbots that helps newsrooms create chatbots using different structured datasets to speed up storytelling and help find story ideas.
You can read more about them here.
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