Amazon’s Reported Censorship Plans Raise Questions About Corporate Surveillance
In April, an article in the Intercept containing leaked internal documents exposed Amazon's plans to ban words like “union” and “pay raise” on a new employee chat app. Amazon’s response was that the particular program had not yet been approved and may change drastically or not get approved at all. In the interim, members of Congress have started an inquiry into the legality of the program and Amazon Worldwide Consumer CEO Dave Clark, who was involved in early discussions of the pilot, has stepped down.
The situation raises important questions about censorship and corporate surveillance. While technically legal, should corporations censor or monitor their employee communications? What do employers stand to gain and what are the tradeoffs?
The Risks of Censorship
In most businesses, information is already filtered on its way to the top. Front-line employees give feedback to their manager, who filters it and passes it along to their manager, and so on. By the time feedback reaches the decision maker, it’s usually a distorted glimpse of reality. The game of telephone along corporate reporting lines already “censors” leaders from truth.
Using technology to actively censor specific topics suppresses what employees talk about. It's a tempting power because there are likely conversations companies want their employees to avoid. But the risk is it can steer dialogue further away from critical realities of the business. When that happens, details get lost and decisions get made based on incomplete understanding. And like Jeff Bezos said, “If you don't understand the details of your business you are going to fail."
When I speak with fellow leaders, they often say they want more honesty from employees. And this is the right way of thinking. When your job is making good decisions, you want more truth — not less. Censorship makes that harder.
But the biggest risk? It's probably culture. Censorship drives suppression of expression. Not only can it create resentment by amplifying toxic corporate power dynamics, but its effects on people are so strong it can actually increase their risk of death and cancer. That’s a potent recipe for a culture of attrition.
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Monitoring employee communication is legal when employees are notified it is happening — and it isn’t uncommon. Done right, the data exhaust of monitored communication becomes insight that drives more effective decision making. It's a short circuit to truth — free from the distortions of corporate telephone. But there’s a big asterisk. Employees must consent to the monitoring, and there should be transparency on how this information is used. If not, it can become a creepy unethical trust-killer that drives attrition.
The other short cut to truth is anonymous collective dialogue. For decades anonymity has been known to maximize honesty, especially around sensitive issues. And when combined with the right tools to separate collectively intelligent signals from mob noise, a new form of scalable dialogue becomes possible.
What's more, dialogue is consensual by nature. If employees know their input is being used to better their workplace, they’re even more likely to share it. Anonymous collective dialogues can increase team morale, engage your employees and help create a space where creativity, productivity and honesty can flourish. So again, instead of just listening to your collective super intelligence of an organization think — you should probably talk with it.
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Which Future Do You Want?
At the end of the day, actively censoring employee communication is a dangerous endeavor. It risks attrition in the short-term, and access to truth in the long-term. Amazon has created the experiment of work censorship, and it will be ours to watch. Perhaps it is right, and suppressing certain conversations really is worth the risks. But, I think a future where free speech and truth trump censorship is the one we should pursue.
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About the Author
Andrew Konya is the CEO and co-founder of Remesh, an agile market research platform that sparks meaningful conversations between decision-makers and the populations they serve, transforming the way organizations operate and driving more informed, empathetic choices. He began his career as a theoretical physicist at Kent State University, applying machine learning and supercomputing to understand emergent phenomena in complex systems.