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Work today looks full, active, and constantly moving. Messages move across Slack channels all the time, documents expand with updates, and dashboards refresh with new data as if progress is happening in real time. On the surface, everything seems to be working fine.
But beneath that activity, something is off.
Teams are busier than ever, yet they struggle to stay aligned. Conversation happens, but clarity doesn’t always follow. Information is everywhere, yet understanding seems hard to come by.
Eric Morrison, a Google researcher and longtime observer of how people interact with technology in the workplace, has been studying this pattern across teams and systems. His work focuses on a simple but often overlooked limitation: systems only work when people can process what’s being shared. Right now, that status quo is breaking.
“We’ve created an environment where it’s not easy to create information,” he explains. “But the ability to absorb, interpret and act on that information hasn’t changed. That mismatch is where things start to fail.”
Emergence of work that looks like work
The modern workplace has become incredibly efficient at producing output. A quick thought can now be expanded into a full report in seconds. Updates are longer, more polished and more frequent than ever. Tools make it easy to fill spaces, and systems reward those who do.
The problem is that more content doesn’t automatically lead to more money.
According to data from Imperva, almost half of Internet traffic now comes from automated systems rather than humans. Inside the organization, the same dynamics play out in different forms. Content creation has accelerated, but the level of human attention to that content has not applied.
This is where the concept of “workshop” begins to emerge. It refers to high-volume, low-objective output that consumes time without providing clarity.
“You read something that checks all the boxes — length, structure, tone — but there’s nothing inside that changes the way you think,” he says. “After a while, your brain starts to recognize that pattern and disengage.”
That detachment is not laziness. This is adaptation.
The system that speaks for itself
As content production became easier, another pattern began to take shape.
A person creates a detailed update. Run it through another shortening tool. A third responds to the summary with a quick acknowledgment. The loop continues, often without anyone fully engaging with the original idea.
It sounds like communication, but it works like a system talking to itself.
Eric Morrison, Googledescribed this pattern as the automatic echo trap, where output cycles through multiple layers without generating meaningful understanding.
“When the starting point and the ending point are the same, everything in excess is at risk of confusion,” he explains. “But the system still considers it progress.”
This creates a dangerous illusion. Activity increases, but alignment does not. Messages move faster, but decisions don’t improve
No one can remove human obstacles
At the heart of the signal crisis is a limitation that technology cannot resolve.
Humans have a limited attention span.
Decades of cognitive research show that people can only process a certain amount of information at a time. This limit remains constant, even as tools accelerate the work around them.
In the former system, the effort required to produce information acts as a natural filter. Took time to write, so picked what people shared. That friction helped maintain the signal.
Now, that filter has disappeared.
“You can expand a simple idea into something that looks comprehensive,” he says. “But the person reading it still has the same ability to understand it.”
Behavior changes as the gap between production and processing increases. People start skimming instead of reading, summarizing instead of analyzing, and reacting without fully absorbing the message.
Over time, this leads to a breakdown in shared understanding.
“When people stop expecting value from what they read, they stop looking for it,” he says.
When teams lose threads
The effects of this breakdown can be seen in subtle but costly ways.
Teams revisit the same discussions because previous decisions were never fully understood. Important details are lost in the gist. People interpret the same information differently.
These are not isolated mistakes. They are systemic results.
“You lose the shared mental model that allows teams to move together,” he explains. “Everyone is active, but they’re not aligned with what’s really important.”
Without that alignment, work slows down as output increases. The decision needs further clarification. Errors become more frequent. Faith begins to erode.
The illusion of progress
One of the most challenging aspects of the signal crisis is that it disguises itself as productivity.
More updates create the appearance of transparency. Offer more document thoroughness. Indulge in more communication signals.
But these signals can be misleading.
“You can build a system that produces a lot of output and still fail to help people understand each other,” he says. “That’s the core function, and that’s what’s breaking.”
Because of this, many teams are stuck working even harder than before. They are producing more, but extracting less value from what they are producing.
A breakdown in practice
In a research study, Eric Morrison, of Google, observed a product team that relied heavily on automated summarization to maintain internal communication.
The daily updates were detailed and structured, but most team members skipped the full content and relied on condensed versions. During a planning session, a key issue came up that was included in the original update but omitted from the summary.
Half the group was aware of the issue. The other half never saw it.
“What stood out was not wrong,” he recalls. “It was how natural it was to everyone in the room. They assumed they were aligned because the system told them they were.”
The system is optimized for speed. It failed in clarity.
Why more tools don’t solve the problem
The usual response to overload is to add more tools. Better summaries, smart filters, faster processing.
These solutions address the symptoms, not the cause.
“You can’t automate your way out of a problem that comes from a lack of focus,” he says. “At some point, someone has to decide what’s important and say it clearly.”
Transparency requires judgment. Court attendance required. These are human works.
Tools can help, but they can’t replace them.
Signal reconstruction in a noisy system
New technology is not needed to solve the signal crisis. This requires different priorities.
The first step is to reduce unnecessary output. Shorter, more direct communication forces clarity and respects attention spans.
The second step is to change the format. Narrative updates often encourage filler, while structured formats like decision logs focus on results and accountability.
The third step is to protect attention as a resource. Every message consumes it, so every message justifies its existence.
Most importantly, teams need to reserve spaces for real interaction. Some concepts cannot be shortened without losing meaning. They need to be discussed, challenged and refined through direct involvement.
The Return of Clarity
Signal crisis is not a permanent state. It is the system’s response that removes friction rather than replacing it.
As the cost of words increases, people start prioritizing clarity again. Teams that create high-signal communication stand out quickly because their work is easy to understand and work with.
“You don’t need more information,” he says. “You need information that actually changes people’s thinking.”
That transition is already underway. Smaller groups, clearer messages and more deliberate communication are beginning to replace volume-driven systems.
What Current Matters
Ultimately, the most valuable output is not the amount of content produced. It is creating levels of understanding.
It requires effort, focus and accountability. It requires someone to take ownership of what is being said and why it matters.
In a system where content creation is easy, those qualities become rare.
And when something becomes scarce, it becomes valuable.
Teams that recognize this won’t necessarily create more work. They’ll produce better work—work that makes sense the first time it’s shared.
Everyone else will continue to advance quickly.
And understand less.
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