AI has made it remarkably easy to generate, filter, personalize, and distribute information. But as more information is produced with the help of AI, I think we need to develop another skill alongside our ability to use these tools: discernment.
When we receive a piece of information, perhaps the first question should not simply be, “Is this information correct?” We can also ask:
What is the intention behind this information, and is it actually relevant to my situation?
For the moment, we do not even need to judge whether that intention is good or bad. The point is simply to recognize that information has an intention, a context, and a purpose.
This becomes increasingly important because we are not the only ones using AI to find and process information. Other people and organizations are also using AI to generate information, identify audiences, personalize messages, and deliver those messages to us.
Recently, I experienced a small example of this.
I received a message from the head of admissions at a business and technology school inviting me to apply for an AI engineering program. She mentioned that my engineering background seemed to fit the program well.
Perhaps AI or another automated system helped identify my profile as a potential match. There is nothing inherently wrong with that. In fact, this can be a useful application of technology.
So I visited the school’s website.
The website looked professional. There were descriptions of different programs and testimonials that appeared to come from real students, with names, degrees, and personal experiences. I also looked for opinions about the school outside its own website, and what I found seemed generally positive.
But I could not find the answer to the most basic question:
What would I actually learn in this AI engineering program?
What is its substance? What capabilities would I develop? What is the educational philosophy behind it? What distinguishes this program from other AI programs?
Since someone from admissions had contacted me personally, I thought I would simply ask.
But when I returned to the message, I discovered that there was no obvious way to reply.
That struck me as an interesting contradiction.
An organization had successfully created a workflow that identified a potentially relevant person, sent a personalized message, directed that person toward a website, and offered the possibility of booking a one-on-one conversation.
Yet the simplest form of communication—asking a question in response to the original message—was missing.
The workflow worked.
The communication did not.
When information becomes a one-way street
I encountered a more extreme version of the same problem with a suspicious automated phone call.
A recorded voice claimed that I needed to make some kind of payment associated with a large online platform. The message delivered information, but I could not interrupt it, clarify what it meant, verify the amount, or ask a question.
Of course, scam calls are very different from legitimate educational marketing. But both experiences made me think about a broader phenomenon.
Technology makes it increasingly easy to send information at scale.
AI can identify audiences. It can generate personalized messages. Algorithms can optimize distribution. Automated systems can contact thousands or millions of people.
But sending information is not the same as communicating.
Communication requires the possibility of response.
If I receive a message designed to persuade me to take an action, I will naturally have questions. If the system has been optimized to reach me but not to hear me, then something essential has been lost.
Essence before workflow
This is why I think organizations—and individuals—should think about the essence before optimizing the workflow.
- What are we actually trying to communicate?
- What value are we creating?
- Why should this matter to the person receiving it?
Only after answering these questions does it make sense to ask how AI can help us deliver that value more efficiently.
The purpose of a workflow should be to help deliver the core value. The workflow itself should not become the product.
Without a clear essence, AI may simply help us produce more messages, reach more people, and optimize more processes—without making the underlying communication more meaningful.
And people can often sense the difference.
If the substance is missing, the real message eventually becomes obvious:
We want you to buy something.
That is very different from:
We have created something valuable, we believe it may be relevant to you, and we are willing to explain it and listen to your questions.
AI can make the first approach extraordinarily efficient. But I believe its greater potential lies in helping us scale the second.
AI also has a cost
There is another dimension that deserves more attention: using AI is not free.
Every AI interaction requires computing resources, energy, infrastructure, and tokens. As AI becomes embedded in more everyday processes, perhaps we should occasionally ask whether using AI for a particular task is actually worthwhile.
Before using AI, I increasingly find it useful to ask three questions:
1. What quality of outcome am I expecting? Is AI likely to produce an answer or result that is genuinely useful? 2. Is using AI worth the resources required for this task? Just because something can be automated does not mean it needs to be. 3. What am I actually trying to accomplish? Do I need information? Do I need to learn something myself? Or do I actually need to speak with another human being?
The third question may become particularly important.
Sometimes the best solution is not another prompt.
Sometimes we need to study, experience, reflect, ask another person a question, or have a real conversation.
What becomes more valuable when AI becomes more capable?
People are already becoming tired of AI-generated communication in some contexts—not necessarily because AI-generated content is “fake,” but because communication is more than the transmission of information.
Human communication contains emotion, intuition, affection, empathy, vulnerability, responsibility, and compassion.
AI can help us express ourselves. It can help us organize our thoughts, translate ideas, analyze information, and communicate across boundaries. But that does not mean we should outsource the human purpose behind the communication.
Perhaps one of the paradoxes of the AI age is this:
The more efficiently machines can generate information, the more valuable genuine human intention may become.
So the important question may not be:
How can we use AI to produce more?
It may be:
What is worth producing in the first place?
And after we understand that:
How can AI help us deliver that value to more people—without closing the channel for real human communication?
AI gives us extraordinary tools for optimizing workflows. But before optimizing the workflow, we need to know the essence.
Otherwise, we may become extremely efficient at communicating something that was never very meaningful to begin with.
So, as AI becomes increasingly capable of generating and delivering information for us, what do you think we should protect—or even strengthen—to make sure we are still truly communicating with one another?