We need to talk about AI (sorry)

By Jodie Hopperton


Los Angeles, California, United States


Hi there.

I have deliberately avoided talking about AI because I feel like it’s everywhere and there are no conclusions yet. But we need to talk about it and how it relates to product. Sorry to add to your no doubt AI laden newsletters in your inbox. I’ll keep it brief and to the point. 

If you are working on AI-specific products, features, or business enablers and want to share, we’d love to hear from you. Or if you disagree with me here. I am aware that I am making some broad conclusions and possibly contentious statements which are my current beliefs, but I learn more every day so feel free to educate me. You can get me on our product initiative Slack channel or at Jodie.hopperton@INMA.org.  

Many thanks, Jodie

AI is and yet it isn’t a product thing (yet)

A couple of weeks ago, the INMA Product Advisory Council gathered on the subject of AI. I was keen to learn what they were working on and pick up on the buzz and excitement from the recent INMA World Congress and the many, many newsletters, articles and events on AI happenings around the media. And yet what I was met with was … apathy.  

Usually discussions are lively, invigorating, and there are a lot of opinions. And yet AI — the buzziest of all things — bought the least excitement I have seen from this group. 

Why? Because the big buzzy projects are not a priority right now. In fact, I would venture to say that companies with big bizzy AI projects are being led top down by the CEO. Usually I would say that is a bad thing, but as one CEO recently pointed out to me when I asked where it should sit in an organisation was plain and simple: with me as CEO

Why, I ventured, surely this is a product thing. But no, AI is so big and can have such huge implications on the entire business that a CEO needs to understand the various aspects of it and lead on this issue. 

I had been schooled and rightly so. 

The advent of generative AI is an existential threat to this industry. That’s not a term I use lightly. As a consumer, I love ChatGPT. It helps me with research, framing things by sifting through many Web links. It even gave me some excellent ideas for a large brainstorm session I will be leading. And when it comes to news, I ask for the top stories, what I need to know. I can use simple prompts like, “Tell me more about …” or “Why did that happen?” or “What are the likely outcomes?” It’s amazing. As long as it’s not hallucinating, which is another issue for another day. 

At no point do I hear any brand. This completely removes the top of funnel for news, which in itself may be an existential threat.   

So yes, it’s a CEO thing. 

And yet as we started talking about AI, any big buzzy projects any of us had heard about were mostly outside news or big bets CEOs were making. Where does that leave product? 

Apparently with a little apathy. 

To be fair, it’s not just the advisory council. It’s almost every product person I speak to. And I think that’s for one of two reasons: Either CEO top-down directive (sometimes that people don’t believe in as it’s too hasty, but not always). Or, more commonly, because it’s flying under the radar. It’s not fun sexy stuff. It’s boring applications that are efficient and make incremental changes.

I don’t think this is a bad thing. In fact I think it’s good because we don’t have all the information about how AI, particularly generative AI, is going to play out. But all this doesn’t mean that AI doesn’t have some very practical applications right now. 

Under the radar AI that is actually making a difference

As the discussion unfolded, it changed from “We’re not doing too much with AI” to “Oh, we’re using it here. And here. Oh and here.” 

There are a number of uses that are flying under the radar as they are specific to specific products or product problems people are working on. Sometimes these are best worked on in isolated cases instead of a holistic major AI strategy. And when I say AI, I include machine learning as the two are often conflated.

Let’s break some of these down:

  • Content creation: I’m sure many journalists are using generative AI for discovery and ideas, maybe even to investigate data. And, of course, there are companies such as United Robots creating content from scratch where there is reliable, repeatable structured data (housing, crime, and sports seem to be the top three areas). 

  • Article summaries: Doesn’t have to be fully AI, but it can help a journalist or editor create a summary in seconds that can then be tweaked by a human. You can see my previous article on how Artifact has a fun version of this here, and I will soon be going a bit deeper on summaries with an expert in the field, so stay tuned. 

An excellent use of machine learning for news publishers is personalised content on their home page.
An excellent use of machine learning for news publishers is personalised content on their home page.

  • Recommendations: A lot of people have been experimenting with personalisation under next read or even on the home page. This is becoming more and more sophisticated. And as the name implies, machine learning gets better the more data it has and the more it learns. 

  • Text to speech: This has been around for a long time and is now so sophisticated that in major languages, you can buy trained voices off the shelf. Many companies are even integrating it into their major products so consumers can choose to read or listen. Join us on August 9 for a free to member Webinar on this. Apple’s new iOS (currently in public beta) lets you clone your own voice. Once it’s out in full release, there will be mountains of data to train it on. And yes, anyone will be able to do this and (as I will write about more in future, this is going to massively change our approach to audio).

  • Speech to text: As we create more audio-first products, we can also use the technology “the other way around.” Currently, most audio isn’t searchable and has to be manually summarised if at all. If we use text-to-speech technologies, we can apply many of the same efficiencies to audio that we do text: summaries, search, giving the consumer the ability to choose. 

  • Translation: Very simply by using translation tools, we can make our content available to more people. When I spoke to Australian broadcaster SBS recently, they told me part of their mission was to appeal to all Australians — and that means multiple languages, both native and its history of building on immigration. New technologies enable them to do this quickly and cheaply (two traits public companies love ;).

These are things we can use now. Longer term, all of these can be built on. Imagine what we can do if generative AI is built into CMS? Imagine what we could do with repeatable structured data? Maybe modular journalism (which I wrote about here) could help with that. And another subject I am passionate about: personalisation. We can go beyond thinking about content topics to format and delivery. 

Of course there is much to build out here, and we at INMA are looking at how we can pull together case studies on AI so that we can learn as a group. If you are working on any of this, I’d love to hear from you. Either to brainstorm, hear learnings, or get a case study published. Hit me up at Jodie.hopperton@INMA.org

Date for the diary: Come and find out everything you need to know about AI at our Silicon Valley Study tour, October 23-27

I am busy putting the finishing touches on the INMA Silicon Valley Study Tour this October. 

We know there is a vast amount of info about AI, and we know AI is going to have a massive impact on our companies and industries as a whole. But what are the variables, the black swan events, and how should we start planning for our business in the new world of AI? 

We’re going deep into AI to give you all the information you need to answer the Qs above. We’re meeting with experts at top U.S. universities, tech companies, media companies, and leaders in the field who can help inform and share our opinion so you can go home feeling equipped with an understanding of how consumer habits are likely to change, what timelines changes are going to happen, black swan events we should be thinking about, and what that means for your business. 

If you are going to be building a comprehensive AI strategy, then this study tour is for you. Take a look here.

About this newsletter 

Today’s newsletter is written by Jodie Hopperton, based in Los Angeles and lead for the INMA Product Initiative. Jodie will share research, case studies, and thought leadership on the topic of global news media product.

This newsletter is a public face of the Product Initiative by INMA, outlined here. E-mail Jodie at jodie.hopperton@inma.org with thoughts, suggestions, and questions. Sign up to our Slack channel.

About Jodie Hopperton

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