The New York Times\u2019 editorial team is using AI technology to pursue a host of stories it couldn\u2019t tackle before, as they involved huge and messy datasets.<\/p>\n
The team behind figuring out how to use AI to parse through hundreds of hours of video or thousands of datapoints is led by Zach Seward, The New York Times\u2019 editorial director of A.I. initiatives. His role was created in December 2023, part of a wave of new AI-focused positions that media companies formed to figure out which AI guidelines, projects and tools to develop for the newsroom to give reporters a competitive edge.<\/p>\n
Onstage at the Digiday Publishing Summit in Miami, Fla., last week, Seward outlined how his team is working with reporters, what tools they\u2019ve built and what the key use cases for AI are so far. Seward has a team of eight, including four engineers, a product designer and two editors.\u00a0<\/p>\n
Using AI for research and investigations is \u201cby far the biggest use of our resources and I think the biggest opportunity right now when it comes to AI in media,\u201d Seward said. His team mostly works by helping a reporter use AI technology for one project, and then creating a repeatable process from that experience for others in the newsroom to use.<\/p>\n
A Times reporter came to Seward\u2019s team with an impossible task \u2013 500 hours of leaked Zoom recordings of an election interference group to go through before Election Day. AI tools were used to transcribe 5 million words and identify parts of those transcripts that were of interest to the reporter.<\/p>\n
\u201c[The election interference group] wasn\u2019t so dumb as to say, \u2018We\u2019re going to spread misinformation on the internet\u2019\u2026 then you could Control F\u201d to find that information in the transcripts, Seward said. \u201cWhere AI becomes useful \u2013 typically it\u2019s referred to as semantic search, or sometimes vibes-based searching \u2013 where you\u2019re looking for topics, concepts, things that are similar. And that\u2019s hugely useful when looking through enormous corpuses of text,\u201d Seward said. That led to a big story before the presidential election last year, he added.<\/p>\n
Those efforts were then developed into a spreadsheet-based AI tool built internally called Cheat Sheet. Reporters can pick (with the guidance of Seward\u2019s team) which LLM model to use with Cheat Sheet, Seward said. It\u2019s now being used by several dozen reporters.<\/p>\n
Seward declined to share other specific AI tools The New York Times newsroom was using, though he said it was \u201cpretty much all the commercial AI providers as well as open source models.\u201d<\/p>\n
Cheat Sheet also helped a reporter who had an unorganized list of 10,000 names of people who had registered for a tax cut in Puerto Rico.<\/p>\n
\u201cYou can\u2019t Google 10,000 names\u2026 but a computer can Google 10,000 names. And then using AI, we could analyze those search results for certain markers that [the reporter] was interested in,\u201d Seward said.<\/p>\n
Even though the results weren\u2019t entirely accurate, it helped sort the names into more promising leads. The reporter could then call them up and continue reporting out the story, Seward said.<\/p>\n
Seward\u2019s team\u2019s approach is to took on an individual reporting challenge \u2013 \u201cknotty, huge, messy data sets\u201d with an \u201cimmediate deadline\u201d \u2013 \u201cbut always with an eye toward building up tooling that will make that repeatable in the future,\u201d he said.<\/p>\n
How Seward\u2019s team works with the newsroom<\/p>\n
How does Seward\u2019s team decide which AI tools to build and where they can help the newsroom?<\/p>\n
Seward said it comes down to constant communication with the newsroom. His team hosts training sessions on how to use AI tools for research investigations. Seward\u2019s team has spoken to 1,700 of the 2,000 people in the newsroom so far, he said.<\/p>\n
The New York Times also has an open Slack channel that anyone from the newsroom can join to ask questions and share use cases \u2013 ranging from \u201chow can I get Gemini?\u201d to one bureau chief inspiring another across the world with an idea for how they\u2019re using AI technology.<\/p>\n
\u201cAI\u2026 is such a personal technology,\u201d Seward said. \u201cThe way people would describe what they want out of AI can be different to the person.\u201d Many have experienced \u201cwriter\u2019s block in the chatbot\u2026 With a tool that can do anything for me, sometimes the challenge is\u2026 what can it do? And so we\u2019re just trying to help answer that question,\u201d he said.<\/p>\n
Dealing with skepticism from the newsroom<\/p>\n
AI isn\u2019t being used to write articles at The New York Times, Seward said. Reporters are allowed to use AI to draft copy around published articles, such as SEO and headlines, he said.\u00a0<\/p>\n
Seward said he reminds editorial staff to \u201cnever trust output from an LLM. Treat it\u2026 with the same suspicion you would a source you just met and you don\u2019t know if you could trust.\u201d\u00a0<\/p>\n
Some newsrooms have challenged upper management about using AI vendors to generate articles<\/a>, or fought back when policies are rolled out<\/a> that push for more use of the technology from editorial.<\/p>\n Seward team deals with any skepticism from reporters about using AI by acknowledging their reservations, and showing them how the technology can be useful, Seward said. <\/p>\n \u201cWe\u2019re not trying to be AI boosters. In fact, quite the opposite. I think there\u2019s a lot of caution. A lot of time we spend cautioning people about uses of AI, both [in the] legal and editorial senses,\u201d he said. \u201cBut if we can have you leave a session saying, \u2018I\u2019m still pretty concerned about this whole environmental issue and maybe like destroying humanity thing \u2013 but in the meantime, it\u2019s going to let me transcribe handwritten notes in Arabic that I took messy iPhone photos of while I was on a reporting trip, and that\u2019s pretty cool.\u2019 And no reporter is going to say no to a competitive advantage, which I think is the theme of what we\u2019re trying to build for them.\u201d<\/p>\n What\u2019s the biggest challenge Seward faces in his newly-created role at The New York Times?<\/p>\n \u201cI definitely live in fear of an error that is in some way attributable to AI. To be clear, we also say in sessions with our newsroom we would never attribute an error to AI, meaning it\u2019s always on us,\u201d Seward said.\u00a0<\/p>\n \u201cI would 100% feel responsible\u201d if something like that happened, he added.<\/p>\n","protected":false},"excerpt":{"rendered":"The New York Times\u2019 editorial team is using AI technology to pursue a host of stories it couldn\u2019t…\n","protected":false},"author":3,"featured_media":245529,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5122],"tags":[5229,130538,304,130537,405,403,5226,5225,5228,5227,67,586,132,5230,68,2969],"class_list":{"0":"post-245528","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-new-york","8":"tag-america","9":"tag-digiday-publishing-summit","10":"tag-generative-ai","11":"tag-modern-newsroom","12":"tag-new-york","13":"tag-new-york-city","14":"tag-newyork","15":"tag-newyorkcity","16":"tag-ny","17":"tag-nyc","18":"tag-united-states","19":"tag-united-states-of-america","20":"tag-unitedstates","21":"tag-unitedstatesofamerica","22":"tag-us","23":"tag-usa"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@us\/115246136417803503","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts\/245528","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/comments?post=245528"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts\/245528\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/media\/245529"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/media?parent=245528"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/categories?post=245528"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/tags?post=245528"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}