racing
Photo by Charlie Larkman on Unsplash
Suppose you are a racing car driver. We are preparing for the next Grand Prix.
you're good. your car is great But you know that other drivers are good too. And some of their cars may even be better than yours.
Now imagine that you get to the race track and the race engineer gives you a special set of new tires. It is said that this tire will make your car 25% faster. At that pace, you can blow away your competitors.
Is there any reason not to take them?
In the real world of motorsport, there are rules regarding tires. Because, as every racer knows, a bad driver with a better set of tires can beat a world champion with worse tires. Better tires can give you an unfair advantage.
At first glance, this is the scenario before us as business leaders today when it comes to artificial intelligence.
AI tools are popping up everywhere. If your industry hasn't received a new set of AI tires yet, wait a few more days. It will happen.
Now, let's put on the new tires. right?
Our rational self-interest would instinctively say yes. We want to win the race. But the problem is that the primary effect of wearing these tires (going faster) can be followed by some secondary effects.
- From now on, you will have to drive differently and be careful in new ways. Turning a corner too fast can cause you to spin or roll over.
- We don't know how quickly these new tires will burn out, or if the tires will generate more heat and destroy other parts of the car.
- If you put this 25% faster tire on, you might be too busy and use up all your resources to take advantage of the 50% faster set of tires that will be released soon after. If our competitors get such tires, they will attack us hard.
- And it remains to be seen whether, in the long run, how these tires are sourced, or what happens with their widespread use, will have a negative impact on the world. For example, what if the rubber in these tires came from a key tree in an area that becomes unstable if cut down? Instability spreads into World War III, and soon all races are cancelled.
If we only think about the surface-level, immediate promise of the AI tools that show up at our doors, we can jump too quickly and have unintended consequences.
For the past decade or so, I've been called upon to speak on innovation and change in off-site leadership roles for companies that are embarking on new frontiers. And over the past year, I've seen a clear pattern among the companies I've consulted with. Whether we're talking about a sales kickoff or an HR team meeting, all of my clients over the last year have asked, “How can I get hired?” Is it AI now? ”
Most of them are concerned that AI adoption is too slow. But what they should be concerned about is doing it too hastily.
For example, in the last year, AI writing generation tools have been popping up everywhere, and companies that saw immediate financial gain from firing writers started leveraging AI for blogging and SEO to pave their way to glory. I did. and, 1) the content was mostly found to be mediocre and often inaccurate. 2) Companies in regulated industries began to run into difficulties. 3) Better tools have emerged (such as co-pilot tools that assist writers rather than writing for them). 4) “Enshittification” became the word of the year as malicious content took over search results and social media.
Should we go through all that pain? And what happens next time you get worse than bad search results?
The key is to never say no to new tires. You need to think carefully about when and how you wear them.
As leaders, we carry the weight of everyone's expectations. Our team, our stakeholders, our press, our peanut gallery. So it's no surprise that you're desperate to get new tires on as soon as you see a chance to win right away. But if we want to make sustainable progress in this new era of ever-increasing AI advancements, we need to ask ourselves some tough questions with every shiny new thing that comes along.
Its main questions are:
Q. What kind of ripple effects can be expected by introducing this AI tool?
Ask yourself. So what do you think? Then what?
Q. How will our team need to work differently going forward?
If we continue to do things the same way we've always done things, introducing new technology may make things worse rather than better. Innovation is about changing the way games are played.
Q. Who is negatively affected by this?
Even if there is a “net gain” from implementing AI, there may well be certain people who will see a “net loss” in the short term (or long term). That could be a problem for you. And more importantly, the human cost of your decisions is something we all care about.
Q. Should I invest resources in this particular AI tool now or wait for the next iteration?
Learning from the first movers and quickly overtaking them in the second wave can be advantageous. (See Chapter 5 of my book smart cut Learn more about. )
Q. What do we still not know about this technology?
You may not want to know how sausage is made, but as a leader, you need to know what you don't know.
As a CEO of a company myself, not just in the film industry, I worry about AI every time someone sends me a link to a new tool that people are excited about.
It seems like it's happening every week now.
I conclude that in many cases, not adopting new AI technologies is likely to be worse than adopting them. But that doesn't mean you don't have to do the math every time about whether it's worth squeezing the juice or the best way to squeeze the juice. Whether you're a humanist or a utilitarian, it makes no sense to react to everything new by saying, “Let's go all in!” or “Let’s boycott!”
As with many things in leadership, the wisest path is not the one to which you rush the fastest, but the one you think about the most.
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