The future is arriving a little later than expected...
I have had the best life. Back in 1989, I left polytechnic with my first class honours degree in humanities (philosophy and astronomy) and walked into the kind of job which graduates back in the 80s just didn't get: a year-long internship with Apple Computer UK, working in the Information Systems and Technology team – the mighty IS&T.
It paid a lot better than my friends were getting working in record shops. And although it was only temporary – I was heading back into higher education to do a PhD in philosophy, working on AI – it suited me. Without it, I wouldn't have had my later career in technology journalism. The ability to take apart pretty-much any Mac you cared to name became very useful later on.
Apple treated new interns the same as every other new employee, which meant that there was an off-site induction for a couple of days when we were told about the past, present, and future of Apple. The only part of the induction that I remember is the future because that was when I first saw the Knowledge Navigator video.
If you haven't seen Knowledge Navigator, you should watch it now.
Why is a 36-year-old concept video relevant now, and what does it have to do with publishing? The vision of how humans and computers interact which Knowledge Navigator puts forward is finally on the cusp of coming true. And that has profound implications for how we find information, which in turn affects publishers.
There are three elements of the way Knowledge Navigator works which, I think, are most interesting: conversational interaction; querying information, not directing to pages; and the AI as proactive assistant. I'm going to look at the first one: interaction as conversation, and how close we are to it.
Interaction as conversation
The interaction model in Knowledge Navigator is conversational. Our lecturer talks to the AI as if it were a real person, and the interaction between them is two-way.
Lecturer: “Let me see the lecture notes from last semester”. Mhmm… no, that's not enough. I need to review the more recent literature. Pull up all the new articles I haven't read.”
Knowledge Navigator: "Journal articles only?”
Lecturer: "uhh… fine.”
Note one big difference with the current state of the art in large language models: Knowledge Navigator is proactive, while our current models are largely reactive. Bing Chat responds to questions, but it doesn't ask me to clarify my queries if it isn't certain about what I'm asking for… yet.
That aside, the way conversation happens between our lecturer and his intelligent agent is remarkably similar to what you can do with Bing Chat or Bard now. The “lecture notes from last semester” is a query about local data, which both Microsoft and Google are focused on for their business software, Microsoft 365 and Google Workspace. The external search for journal articles is the equivalent of interrogating Bing or Bard about a topic.
In fact, Bing already does a pretty good job here. I formed a similar question to our lecturer's about deforestation in the Amazon, to see how it would do:
Not bad, eh?
The publishing model of information – the one which makes publishers all their money – is largely not interactive. The interaction comes at Google's end, not the publishers. Our current model looks like this:
A person interacts with Google, making a query.
They click through to a result on the page which (hopefully) gives them an answer
If they want to refine their query, they go back to Google and repeat the process – potentially going to another page
Interaction as conversation changes this dynamic completely, as an “intelligent” search engine gives the person the answer and then allows them to refine and converse about that query immediately – without going to another page.
Have a look at this conversation with Bard, where I am asking for a recommendation for a 14in laptop:
OK, that sounds good. Now let's drill down a little more. I want one which is light and has a good battery life:
That ZenBook sounds good: so who is offering a good deal?
By contrast, a standard article of the kind which publishers have been pumping out to capitalise on affiliate revenue (keyword: “best 14in laptop”) is a much worse experience for users.
And at the end of that conversation with Bard, I'm going to go direct to one of those retailers, with no publisher involvement required.
If that isn't making you worry about your affiliate revenue, it should be.
The model of finding information which search uses, based on queries and a list of suggested results, is pretty well-embedded in the way people use the internet. That's particularly true for those who grew up with the web, aged between 30-60. It may take time for this group to move away from wanting pages to wanting AI-driven conversations which lead to answers. But sooner or later, they will move. And younger demographics will move faster.
That, of course, assumes that Google will leave the choice to users. Google may instead decide it wants to have more time with “its” users and put more AI-derived answers directly at the top of searches, in the same way that Microsoft has with Bing. Do a keyword search on Bing, and you are already getting a prompt to have a conversation with an AI at the top of your results:
Once again, the best option for publishers is to begin the switch from a content strategy which relies on Google search and focuses on the kinds of keywords which are susceptible to replacement by AI (focused on answers) to content strategies which build direct audience and a long-term brand relationship.
Treat search traffic as a cash cow, to be milked for as long as possible before it eventually collapses. In the world of the Knowledge Navigator, there's not going to be much room for simple web pages built around a single answer.
