The Associated Press is one of the first news organizations to leverage artificial intelligence and automation to bolster its core news report. Today, we use machine learning along key points in our value chain, including gathering, producing and distributing the news. Explore this page to learn more about the history of artificial intelligence at The Associated Press, our strategy around the technology and how we use it today.
Our foray into artificial intelligence began in 2014, when our Business News desk began automating stories about corporate earnings. Prior to using AI, our editors and reporters spent countless resources on coverage that was important but repetitive and, more importantly, distracted from higher-impact journalism. It was this project that enabled us to experiment with new initiatives and led to other news organizations looking to AP for ways to adopt the technology themselves.
AP looks for ways to carefully deploy artificial intelligence in areas where we can be more efficient and effective, including news gathering, the production process and how we distribute news to our customers.
Our objective in production is to streamline workflows to enable our journalists to concentrate on higher impact work. This ranges from the automatic transcription of video to experimenting with the automatic-generation of video shot-lists and story summaries. We also automate some corporate earnings and sports stories.
In distribution, we aim to make it easier for our customers to access our content and put it into production faster. As part of this, we are working to optimize content via image recognition, creating the first editorially-driven computer vision taxonomy for the industry. This tagging system will not only save hundreds of hours in production but help surface content more easily.
AP works with a variety of startups to infuse external innovation into the organization and help to bring our artificial intelligence projects to life. This allows us to experiment at low costs with emerging tech and support the entrepreneurial news ecosystem at the same time. In addition to working with various startups, we also build partnerships to help extend the reach of our journalism and our work with AI. Some key examples include Social Starts, Matter Ventures and NYC Media Lab.
AI-powered search makes it easier for users to find the best photos and videos that meet their search criteria. Rather than a traditional metadata search, the tool understands descriptive language and produces search results based on the description a user provides.
Check out some of the many projects we are working on below.
Local News AI initiative
The AP distributed a score card to U.S. local news operations to understand AI technologies and applications that are currently being used and how AI might augment news and business functions. Based on the score card results, AP wrote a report and designed an online course to share best practices and techniques on AI with local newsrooms. The initiative’s third phase will be a consultancy program with 15 news operations.
Event detection
We deploy a tool from SAM, a Canadian social media solutions company, to detect newsworthy events based on natural language processing (NLP) of text-based chatter on Twitter and other social media venues. SAM alerts expose more breaking news events sooner than human journalists could track on their own through manual monitoring of social media.
Image recognition
Image recognition software can improve the keywords on AP photos, including the millions of photos in our archive, and improve our system for finding and recommending images to editors. We have tested whether these tools can help keep graphic content out of our image feeds or help identify athletes by jersey numbers. This will create the first editorially-defined taxonomy for the news industry.
Automated stories
Since 2014, we have automated text stories from structured sets of data using natural language generation (NLG). We began with corporate earnings stories for all publicly traded companies in the United States, increasing our output by a factor of 10 and increasing the liquidity of the companies we covered. We have since applied similar technology to over a dozen sports previews and game recaps globally.
Automated shot lists
We’re applying computer vision technology from Vidrovr to videos to identify major political and celebrity figures and to accurately timestamp sound bites. This is helping us streamline the previous process of manually examining our video news feeds to create text “shot lists” for our customers to use as a guide to the content of our news video.
Real-time transcriptions
Software developed by Trint and employing machine learning is enabling us to transcribe videos in real time, slashing the time previously spent creating transcripts for broadcast video. We are now working to marry this technology with live video streams and also integrate automatic translation to multiple languages.
Watch the webinars below to learn more about artificial intelligence in the news industry.
ChatGPT & DALL-E: What Generative AI means for journalism
AI’s effect on search and your website visibility
AP Solutions: Five free AI projects for your newsroom
