In the ideal world, credentials would be awarded to all experts, and withdrawn from all charlatans.
But they don’t always line up as neatly as that.
An expert is someone who can keep a promise. Point to the results that demonstrate your skill and understanding and commitment and we’ll treat you as an expert.
Credentials, on the other hand, are awarded to folks who are good at being awarded credentials. The place you went to school or the number of followers you have online are credentials. If they help you create value, that’s great. But they’re not the same as expertise.
Twenty handwritten letters received by someone in power are worth a hundred times as much as two letters.
And when that becomes a hundred different personal letters, increasing in volume, from different people, delivered to an organization every week for a year… it’s worth a million times as many as just twenty.
For generations, humans have been entrusting their lives to computers. Air Traffic Control, statistical analysis of bridge resilience, bar codes for drug delivery, even the way stop lights are controlled. But computers aren’t the same as the LLMs that run on them.
Claude.ai is my favorite LLM, but even Claude makes errors. Should we wait until it’s perfect before we use it?
If a perfect and reliable world is the standard, we’d never leave the house.
There are two kinds of tasks where it’s clearly useful to trust the output of an AI:
Recoverable: If the AI makes a mistake, you can backtrack without a lot of hassle or expense.
Verifiable: You can inspect the work before you trust it.
Having an AI invest your entire retirement portfolio without oversight seems foolish to me. You won’t know it’s made an error until it’s too late.
On the other hand, taking a photo of the wine list in a restaurant and asking Claude to pick a good value and explain its reasoning meets both criteria for a useful task.
This is one reason why areas like medical diagnosis are so exciting. Confronted with a list of symptoms and given the opportunity for dialog, an AI can outperform a human doctor in some situations–and even when it doesn’t, the cost of an error can be minimized while a unique insight could be lifesaving.
Why wouldn’t you want your doctor using AI well?
Pause for a second and consider all the useful ways we can put this easily awarded trust to work. Every time we create a proposal, confront a decision or need to brainstorm, there’s an AI tool at hand, and perhaps we could get better at using and understanding it.
The challenge we’re already facing: Once we see a pattern of AI getting tasks right, we’re inclined to trust it more and more, verifying less often and moving on to tasks that don’t meet these standards.
AI mistakes can be more erratic than human ones (and way less reliable than traditional computers), though, and we don’t know nearly enough to predict their patterns. Once all the human experts have left the building, we might regret our misplaced confidence.
The smart thing is to make these irrevocable choices about trust based on experience and insight, not simply accepting the inevitable short-term economic rationale. And that means leaning into the experiments we can verify and recover from.
You’re either going to work for an AI or have an AI work for you. Which would you prefer?
The second worst is the unaware sort. The work doesn’t meet spec, and we don’t even realize it.
The worst is uncaring. We know the work doesn’t meet spec, but we don’t bother to fix it.
But there are other varieties, and some are worth seeking out:
There’s the incompetence of creativity and art, where the spec isn’t the point.
And there’s the dawning awareness of incompetence that comes from learning. We didn’t realize we could do better, and then we discover we can. That’s a critical step on the path to better.
First, we realize that there’s something we don’t know.
Then we see that we’re going to be better at it, and we’re not good at it yet.
Then we figure it out and we’ve succeeded.
Repeat.
When we pre-process the information and simply test people on it, there’s no real learning going on. We become what we do, and if we actually solve the riddle, we’re more likely to have it stick than if someone simply tells us the answer.
The job of the teacher is to create the conditions for the student to explore their incompetence long enough to learn something useful.
The experience of the now is often more vivid than a distant memory. As a result, we can make decisions in the future without enough regard for how we felt the last time we were in a similar situation.
Here’s a simple hack that can inform your decisions…
You know someone who recently got the flu. Perhaps they were sick in bed for weeks, or even needed medical attention… Write down what happened (and how it made you feel) and put it in your calendar for September 16th. That way, nine months from now, when you’re thinking of getting a flu shot, the reminder will be right there for you.
Did you leave work an hour early to spend time with friends instead? Take some pictures and add that reminder to your calendar for two months from now, a useful way to get out of your daily work rut.
One more: the next time that cold and rain doesn’t keep you from an outdoor walk, drop yourself a note for next week, reminding yourself of how good it was to get up and get out.
It’s not a diary you put on the shelf. It’s a diary entry you send to yourself in the future.
The future unfolds, with or without us, but that doesn’t mean we can’t bend it in a useful direction.
Freedom is something we desire. The freedom to choose, to speak up, to produce, to follow our passions and our dreams.
And organizations in search of efficiency, shortcuts or profits often argue for freedom as well. The freedom to organize their production and to go to market without regulation or hassle.
Our actions, though, have consequences. That power plant might be venting steam into the river that millions depend on. Your upstairs neighbor’s loud music at midnight is your sleep interrupted. Your worse might be someone else’s better (and vice versa).
The temptation is to deny the externalities or to minimize their impact. Teenager thinking is to argue for freedom by pointing out that nothing bad will happen, or if something does, it won’t matter much, and even then, it won’t really be your fault. Denial is tempting, but it’s not helpful.
It’s more useful and productive to do precisely the opposite.
The best way to achieve freedom is to take responsibility for the actions you’re taking. And the best way to be clear that you’re taking responsibility is to highlight the externalities and own them.
When you acknowledge what we can easily see, it’s much easier to trust you.
List for us all the negative consequences of your policy, output or actions, and then tell us how you’ll remedy them.
Freedom isn’t a clever plan to be let off the hook. It’s a deliberate path to being on the hook.
January 17, 2025
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