As newsrooms around the globe are beginning to harness AI, this week the New York Times posted a job listing for an editor to serve as "newsroom generative AI lead."

My thought bubble: Good luck to the winning applicant! Journalists, like many other professionals, are fearful and anxious about the new technology, and this is not going to be an easy job — but I'm generous, so here's a memo with some helpful advice.

Dear future robot wrangler: Many publishers have jumped right in to use generative AI for writing entire articles — a task the technology isn't ready to take on. Far more interesting opportunities lie under the surface.

1. Writing full articles is the most obvious use of generative AI, but not the best, because of all the ways AI still fails at the basics of good journalism.

• Today's generative AI systems make mistakes, plagiarize, say inane or embarrassing things and make stuff up. The Columbus Dispatch, MSN, Onion and Gizmodo parent G/O Media, CNET and others have all learned that the hard way with spectacular, very public flops.
• Even if they get better at sticking to the facts, algorithms can't assess credibility. Today's technology often does a passable job summarizing an interview — but it has no idea if the interviewee is the foremost expert on a subject, or someone who is in over their head, or someone who's promoting an agenda.
• There are some very limited writing tasks AI can be let loose on today, like corporate earnings stories, which follow a predictable pattern and often depend on a single source. Using older technology, the Los Angeles Times has for years had a bot churn out first takes on earthquakes, telling people what they most want to know — how big the tremor was and where it was centered.

2. The bigger newsroom opportunity is to use AI for other parts of the reporting and writing process.

• I've been using Otter.ai to record and transcribe notes, and its AI chatbot lets me ask questions of my notes (see review). And I am constantly looking for other tasks it might assist with. I think AI will someday soon help me identify sources from my email, for example.
• AI can also be used to find patterns in vast amounts of data — an organization's own archives as well as large swaths of public information.

3. Illustrations and some kinds of conceptual graphics are another area of promise for AI. The ability of text-to-image engines to create powerful artwork from a simple prompt is already impressive.

• Yes, but: Visual journalists have raised strong questions on ethical and intellectual property-related grounds about many of today's generative AI image systems.

4. Experiment behind closed doors first.

• The best way to understand the tools is to try them. I get to do that as part of my job, but any newsroom that wants to be relevant in the AI era should be constantly exploring what's possible, scrapping what doesn't meet standards and investing in what does.

5. Be transparent.

• Whatever you decide to do with AI, be clear with the audience and, where possible, explain what you are doing and why. The LA Times does this very well with its Quakebot.

6. AI can help the news business — but it also threatens it.

• Journalism has been slow to adapt to other recent tech shifts, and paid a heavy price, but that needn't be the case with AI.
• Some news organizations, such as Reuters, are using AI to compose and test headlines to see which perform better in our SEO-dominated world. Bloomberg, meanwhile, is building a comprehensive BloombergGPT system based on its vast collection of financial data.
• At the same time, AI will give tech giants new, more powerful ways of incorporating content without having to direct people to the originating site.

7. Generative AI will make it even harder to combat online misinformation, as we've written extensively.

• That creates a huge need for humans who can bring fairness and accuracy, as well as much needed context, to the news. But they will have to do so amid intensifying business pressures that the new technology is unleashing.

8. Be prepared to shift your thinking.

• A bad use of AI today might make sense tomorrow. I've been covering Silicon Valley for more than 20 years, and generative AI is evolving faster than any other technology I've witnessed.

Go deeper: I spoke on the topic of AI and newsrooms earlier this month at the conference for NLGJA: The Association of LGBTQ+ Journalists.

Republican presidential primary contender Will Hurd is the first candidate to release an AI policy plan — framing coming AI development as a "Cold War with China" and urging licensing of frontier AI models, Axios' Ryan Heath reports.

Why it matters: Hurd's hawkish, pro-regulation of AI approach is notable given his deep AI credentials.

• Hurd, a former Republican member of Congress from Texas, chaired the first AI hearing in the House in 2018. He also claims credit for writing "the first National Strategy for AI" (a congressional resolution) and served on OpenAI's board from 2021 until July.

Hurd writes that "powerful AI models should need to obtain a permit" — and likens them to nuclear power plants.

He wants a Republican AI strategy to "take advantage of technology before it takes advantage of us," and also supports:

• "Strict regulations of sensitive AI technology exports."
• Ensuring AI is deployed along "every mile of our border."
• Compensating creators "when their creations are utilized in AI-generated content."
• Making coding and data analytics standard middle school subjects, noting that "AI threatens 85 million jobs worldwide."

Between the lines: Though AI promises to shape both 2024 campaign methods and debates, even candidates with tech industry backgrounds — including Vivek Ramaswamy and Gov. Doug Burgum (R-N.D.) — have avoided AI specifics thus far.

Yes, but: Hurd, a moderate who quit his seat in Congress in 2020, has so far failed to qualify for either of the Republican primary debates and has not topped 1% nationally in polls.

Editor's note: This story has been corrected to show that Hurd chaired the first AI hearing in the House of Representatives, not the first AI hearing in Congress. The first AI hearing in Congress was in the Senate in 2016.

LimeWire — popular two decades ago as a music file-sharing service — is back, and this time it's aiming to be a community where people create and share AI images, video and audio.

To that end, it is announcing today the acquisition of BlueWillow, an AI generation model that has been used by 2.3 million people to create around 500 million images.

Yes, but: Today's LimeWire isn't really the same company that millions used to trade music files in the Napster era.

• The current start-up bought the LimeWire name two years ago in an effort to capitalize on the goodwill associated with the brand, which at that point had been defunct for more than a decade.

Catch up quick: The new LimeWire started out as an effort to make NFTs more consumer friendly, but has now pivoted to focus on generative AI.

• The 30-person Vienna, Austria-based company has raised around $17 million in funding through token sales.
• It launched its AI studio a couple of months ago using open source tools, including those from Stable Diffusion. The startup says its goal is to offer not only an easy place to generate images, but also a way for creators to make money from their efforts.

What's next: LimeWire plans to incorporate BlueWillow's model and community into its AI studio, but will also continue to draw on open source efforts.

• The first U.S. combined AI and medicine degree can be had — with five years and tuition — from the University of Texas. (Axios San Antonio)
• On tap: A House Judiciary subcommittee is holding a hearing at 3pm ET today exploring the impact of AI, cybersecurity and intellectual property issues on U.S.-China competition. Witnesses include representatives from Scale AI and CrowdStrike.

I've been having a lot of fun with the live stickers feature in the just-released iOS 17. Here are some favorites, and here's how to do it with your own photos.