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Work today looks full, active, and constantly in motion. Messages move across Slack channels at all hours, documents expand with updates, and dashboards refresh with new data as if progress is happening in real time. On the surface, it feels like everything is working exactly as intended.
But underneath that activity, something is off.
Teams are busier than ever, yet they struggle to stay aligned. Conversations happen, but clarity doesn’t always follow. Information is everywhere, yet understanding feels harder to reach.
Eric Morrison, Google researcher and long-time observer of how people interact with technology at work, has been studying this pattern across teams and systems. His work focuses on a simple but often overlooked constraint: systems only function when people can process what’s being shared. Right now, that condition is breaking down.
“We’ve created an environment where generating information is effortless,” he explains. “But the ability to absorb, interpret, and act on that information hasn’t changed. That mismatch is where things start to fail.”
The Rise 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 before. The tools make it easy to fill space, and the systems reward those who do.
The problem is that more content does not automatically lead to more meaning.
According to data from Imperva, nearly half of all internet traffic now comes from automated systems rather than humans. Inside organizations, the same dynamic is playing out in a different form. Content generation has accelerated, but the level of human attention applied to that content has not.
This is where the idea of “workslop” begins to emerge. It refers to high-volume, low-intent output that consumes time without delivering clarity.
“You read something that checks all the boxes—length, structure, tone—but there’s nothing inside it that changes how you think,” he says. “After a while, your brain starts to recognize that pattern and disengage.”
That disengagement is not laziness. It is adaptation.
The System That Talks to Itself
As content production becomes easier, another pattern begins to take shape.
One person generates a detailed update. Another runs it through a summarization tool. A third reacts to the summary with a quick acknowledgment. The loop continues, often without anyone fully engaging with the original idea.
It feels like communication, but it functions more like a system talking to itself.
Eric Morrison, Google, has described this pattern as the Automated Echo Trap, where output cycles through multiple layers without producing meaningful understanding.
“When the starting point and the ending point are the same, everything extra in between risks becoming noise,” he explains. “But the system still treats it as progress.”
This creates a dangerous illusion. Activity increases, but alignment does not. Messages move faster, but decisions do not improve.
The Human Bottleneck No One Can Remove
At the center of the signal crisis is a constraint that technology cannot solve.
Human attention has limits.
Decades of cognitive research show that people can only process a certain amount of information at once. That limit remains constant, even as tools accelerate the pace of work around them.
In earlier systems, the effort required to produce information acted as a natural filter. Writing took time, so people were selective about what they shared. That friction helped maintain 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 capacity to understand it.”
As the gap between production and processing widens, behavior changes. People begin to skim instead of read, summarize instead of analyze, and respond 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 the Thread
The effects of this breakdown show up in subtle but costly ways.
Teams revisit the same discussions because previous decisions were never fully understood. Important details get lost in summaries. People interpret the same information differently.
These are not isolated mistakes. They are systemic outcomes.
“You lose the shared mental model that allows teams to move together,” he explains. “Everyone is active, but they’re not aligned on what actually matters.”
Without that alignment, work slows down even as output increases. Decisions require more clarification. Errors become more frequent. Trust 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. More documents suggest thoroughness. More communication signals engagement.
But these signals can be misleading.
“You can build a system that produces a huge amount of output and still fails at helping people understand each other,” he says. “That’s the core function, and it’s the one that’s breaking.”
This is why many teams feel stuck despite working harder than ever. They are producing more, but extracting less value from what they produce.
A Breakdown in Practice
In one research study, Eric Morrison, Google, observed a product team that relied heavily on automated summaries to keep up with internal communication.
Daily updates were detailed and well-structured, but most team members skipped the full content and relied on condensed versions. During a planning session, a key issue surfaced that had been included in the original update but omitted from the summary.
Half the team was aware of the issue. The other half had never seen it.
“What stood out wasn’t the mistake,” he recalls. “It was how normal it felt 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 at clarity.
Why More Tools Don’t Solve the Problem
The natural response to overload is to add more tools. Better summaries, smarter filters, faster processing.
These solutions address the symptoms, not the cause.
“You can’t automate your way out of a problem that comes from lack of attention,” he says. “At some point, someone has to decide what matters and say it clearly.”
Clarity requires judgment. Judgment requires presence. Those are human functions.
Tools can assist, but they cannot replace them.
Rebuilding Signal in a Noisy System
Fixing the signal crisis does not require new technology. It requires different priorities.
The first step is reducing unnecessary output. Shorter, more direct communication forces clarity and respects the limits of attention.
The second step is changing formats. Narrative updates often encourage filler, while structured formats like decision logs focus on outcomes and accountability.
The third step is protecting attention as a resource. Every message consumes it, so every message should justify its existence.
Most importantly, teams need to preserve spaces for real interaction. Some ideas cannot be summarized without losing meaning. They need to be discussed, challenged, and refined through direct engagement.
The Return of Clarity
The signal crisis is not a permanent state. It is a response to systems that removed friction without replacing it.
As the cost of noise increases, people begin to prioritize clarity again. Teams that produce high-signal communication stand out quickly because their work is easier to understand and act on.
“You don’t need more information,” he says. “You need information that actually changes how people think.”
That shift is already underway. Smaller groups, clearer messages, and more intentional communication are starting to replace volume-driven systems.
What Actually Matters
In the end, the most valuable output is not the amount of content produced. It is the level of understanding created.
That requires effort, attention, and accountability. It requires someone to take ownership of what is being said and why it matters.
In a system where generating content is easy, those qualities become rare.
And when something becomes rare, it becomes valuable.
The teams that recognize this will not necessarily produce more work. They will produce better work—work that is understood the first time it is shared.
Everyone else will continue to move faster.
And understand less.
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