Forecast fails: what misguided tech predictions teach us about the future

When it comes to making predictions about the future, confidence generally counts for more than accuracy. Nostradamus was completely off the mark when he predicted that 2023 would be marred by widespread cannibalism and the destruction of Mars. Even Punxsutawney Phil — the prognosticator of prognosticators — only correctly forecasts the arrival of springtime about 39% of the time.

In the tech and data privacy spaces, analysts and influencers are equally prone to making erroneous predictions — especially when new technologies like AI erupt onto the scene and rewrite the rules for us all. Just take a look at the industry’s annual forecasts from the start of last year, right around the time that ChatGPT was bursting into the mainstream. A groundhog might’ve been more accurate. 😅

As 2024 flies by, let’s take a moment and ask: are we learning from the mistaken predictions we made last year? And what does that tell us about how we should run our organizations in the year to come?

Three things we got wrong in 2023

So what did we get wrong about the way tech and data privacy evolved in 2023? The biggest slip-up, of course, is that when the year began we had only the barest sense of where GenAI was going to take us — and the rise of AI has touched just about every aspect of the tech and data space in the intervening months. 

Read more: Staying ahead in a GenAI world starts with data privacy

Here are just a few examples of the ways that tech experts were led astray as they made their annual predictions:‍

1. The metaverse went bust (for now?)

‍We haven’t heard much about the metaverse this year — which might come as a surprise to those end-of-year forecasters that made it their number one trend to watch for 2023. Within months, we were all talking about GenAI as a potential metaverse-killer — in part because while the metaverse remained a technology in search of a compelling use-case, new AI technologies were able to rapidly start generating enormous value for both consumers and businesses of all kinds. ‍

2. Data > algorithms

‍Going into 2023, one pundit predicted that AI models would quickly grow to feature over 10 trillion parameters, but in fact we saw relatively small models punching well above their weight; even OpenAI’s flagship model, GPT-4, features only 1.76 trillion parameters.

The twist we didn’t anticipate? Tech giants learned to distill vast datasets into relatively compact algorithms —  meaning that AI models actually got leaner as they gorged on ever-increasing quantities of public and private data. ‍

3. Regulations didn’t become redundant

‍Some experts, meanwhile, were too bullish on AI; one predicted that “almost sentient” AI tools would quickly make regulations impossible to implement — because while you can regulate an algorithm, it’s far harder to regulate a quasi-human ‘bot with actual thoughts and feelings.

Well, ChatGPT and its ilk are still a long way from sentience — and while the challenges are real, regulators certainly haven’t given up on regulating them. In fact, they’re digging up old laws on fairness and transparency to manage these emerging technologies.

Of course, it’s easy enough to poke holes in other people’s predictions, especially with the luxury of 20-20 hindsight. My point, though, isn’t that the people who made these predictions were sloppy or misinformed. They were doing the best they could with the information they had to hand — and they couldn’t have anticipated the scale and sweep of the AI revolution we’ve seen play out over the last 18 months.

The reality is that forecasting is hard, and the folks who do it well are the ones who are willing to change their mind when the times change. As organizational psychologist Adam Grant argues, the highest performers are generally flip-floppers who take joy in being proven wrong, and relish the chance to upgrade their thinking to account for new facts and new data. 

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How to succeed in 2024 

So what should we learn from all this? Well, for starters, making predictions in this fast-paced AI and regulatory landscape is a fool’s game. The AI revolution is still underway, and things are moving way too fast for anyone to say with confidence how things will shake out by the end of 2024. 

We should be bold about exploring and spotting opportunities. But we shouldn’t get too wedded to any particular claims about precisely what lies ahead. Instead, we should be prepared to change our mind repeatedly over the coming year. Frantly, we should look inward. 

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We must figure out how to prepare our organizations for a future that is nearly unimaginable. That starts with articulating what your company stands for, and leaning into your North Star principles as you pursue emerging opportunities and bring new technologies into your data stack. 

Jonathan Joseph, Head of Solutions at Ketch

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A few observations of 2024 so far, that didn’t require a crystal ball to predict:

• Regulators are spending much of 2024 figuring out how to guide the evolution of AI
• Consumers are paying increasing attention to how emerging technologies are harnessing and sharing their data
• We  don’t know exactly what those technologies will look like — but we can be pretty sure that transparency, fairness, privacy, and meaningful consent will remain central to the kinds of experiences that regulators and consumers desire.

Companies that double down on defining and strengthening their core values, and embedding them across their dataflows and operations, will ultimately be better positioned than those that spend their time engaging in speculative techno-futurism. At the end of the day, companies will need to stay compliant, serve their customers, and build ethical and responsible frameworks for innovation.

It’s by focusing on those core goals that we’ll be able to adapt to whatever the future brings in smarter, more sustainable, and more effective ways.

Go further: 5 ways to unify your legal and tech teams in the AI era

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