Tech Companies Need to Show, Not Tell, When it Comes to AI
This week saw Google announce a variety of new hardware products. But the main theme of Google’s event wasn’t actually hardware but software: specifically, artificial intelligence. Microsoft’s Ignite event last week also made AI a major focus, with Satya Nadella’s keynote titled “Democratizing AI”. Even Apple, not normally prone to talking about the technology behind its products, has started sprinkling references to machine learning and related concepts into its keynotes. It’s clear AI and machine learning are hot topics but there’s a risk these concepts become the main point. What they do for customers should be the real focus.
Ahead of Google’s event this week, I was approached by a number of reporters wanting to discuss the possible announcements and their relevance. One particular reporter asked about the AI angle and this was my response:
The big thing about AI is no-one outside our circles actually cares. What they do care about is whether their devices and services do useful things, but whether it’s using AI, machine learning, or convolutional neural networks is totally irrelevant. So Google, Microsoft, and Apple can talk up AI at these events all they want, but they’re largely talking to the tech press and a few nerds when they do so, not to end users. The old moviemaking maxim “show, don’t tell” definitely applies here when it comes to real people.
The fact is, big tech companies always have several audiences when making big announcements or holding events and they speak to each of these audiences differently. Among those audiences are:
- Consumers – the end users and often the purchasers of products and services
- Enterprise decision makers – sometimes the purchasers of technology that ends up in the hands of end users
- Media – although this is becoming a little less true over time in the era of live streaming events, still the main conduit through which news about announcements filters through to consumers and enterprise decision makers
- Financial analysts – those who have to build models and ultimately advise clients on whether to buy or sell stock in the company making the announcements
- Observers – all the others who are interested in what’s being announced but don’t belong in the categories above – including industry analysts like me, who have to form an opinion about the company professionally, but also hobbyists and tech enthusiasts who are interested in trends, strategies, and so on
The problem with the current AI obsession is all the big tech companies are focusing, to a great extent, on every audience but that first one – consumers. As I said to the reporter, consumers don’t care about AI – many of them probably think it’s a movie starring Jude Law and the kid from Sixth Sense. What consumers care about is the output of all that AI and machine learning – the features on their phones and in their online services which actually make their lives better.
Whether there’s AI behind those features is utterly irrelevant from a user perspective. But the fact your phone seems smarter than mine, or my email service seems better at filtering out spam or suggesting automatic responses than yours, or the digital assistant on my new phone seems to understand what I say better than my old one – that’s what really matters.
Yes, AI, machine learning, and plenty of other technologies are behind many of the advances in the technology we use every day. But that doesn’t mean we as consumers need to know that, any more than I need to know how the plane I’m writing this post on is staying in the air. It may be interesting to a subset of customers but that’s not nearly the same thing.
And that’s where my parting comment in the quote comes in. In the moviemaking industry, one of the key principles is “show – don’t tell”. What that means is there’s a tendency, when providing exposition in a movie, to have a character talk through everything the audience needs to know. But that’s far less effective than showing the audience what it needs to know through characters’ actions rather than their words. That’s harder to do – it requires more creativity and may force you to pare back some of the complexities in your story if you find it impossible to explain it to your audience using action rather than words.
That principle should be taken to heart by tech companies too. If you’re unable to demonstrate the practical benefits of your AI chops to users, your story needs work. And your AI story will be a lot more powerful if you demonstrate it with actions rather than having to describe it with words. Especially in a consumer-facing context, tech companies need to show first, tell second (if they tell at all). Demonstrate the great new features and then (if necessary) talk about how it’s done afterwards.
Now, that’s not to say talking about AI or machine learning is always wrong. This is where we come back to that list of audiences from earlier. For a number of those audiences, investment in new behind-the-scenes technologies is a really important factor in making judgments about your company. Financial analysts, the media who shape narratives about companies, and others may all want to know more about these things. But those selling technology should never make telling that story the primary focus, especially in events which are designed for an end user audience.