As Leaders Learn to Speak Machine, They Need to Speak Better Human Too

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Digital handwriting set in the amazing “Liebeheide” by typographer Ulrike Rausch

Long before the pandemic, I learned about “remote work” in Silicon Valley and I felt like it could be the future. That was five years ago, and I didn’t expect it to happen so quickly.

At the time, Automattic was the largest tech company operating fully remote, or more precisely “fully distributed,” and my good fortune led me to joining Matt Mullenweg’s prescient organization. As the pandemic has worn on, I have found that many of the “new” WFH tips that get shared today were pioneered long ago by Automattic. Things like the difference between the politics of a workforce that is partially distributed versus 100% distributed — the latter being the more effective option. And the fact that “asynchronous” unmonitored working is better than three-hour “synchronous” Zoom calls where showing presence is a requirement — but the former requires a great deal of trust that most bosses aren’t willing to easily extend. Perhaps the most revolutionary aspect of distributed work is the notion that talent does not need to be drawn from a hub like San Francisco or New York City, and can be just as easily sourced from Mexico City or Nairobi or anywhere in the world as an expanded dimension of the tech meritocracy.

I later came to realize that time zone differences, to start, tend to be insurmountable obstacles for working in a united fashion when everyone is distributed. And there’s also that English-is-the-universal-language issue that tends to get forgotten when you’re a native English speaker. Then there’s the fact that there’s so many conversations happening simultaneously at various density levels throughout the day. The only way to get a handle on what’s being said, of course, is to use algorithms to help bubble up to you what is the most relevant signal within all the noise. So as more and more of us WFH, we are adopting the norms of gathering all our information using systems that are akin to social media. These systems feed off of engagement, learn what we like, and optimize our feeds accordingly.

In the imminent future, being facile at speaking machine will require an even greater facility at speaking human.

Can work evolve into a daily experience similar to swimming through a Facebook-like or Twitter-like timeline some day? Can the workplace evolve into a similarly polarized universe of factions and over-optimized bubbles of knowledge, the same way that we’ve experienced that online? The digital transformation led by COVID-19 most certainly has set that future in motion with the at-scale shift to WFH. Many good things will come from it, if business and government leaders consider the pros and cons of this approach with a deeper understanding of how computational systems can work against us. I like to call this ability “knowing how to speak machine” — not necessarily knowing how to write computer code, but having a deep enough grasp of computation to better grok what a Silicon Valley tech CEO is talking about.

Leaders will need to look outside of the heady tech optimism around the expanding virtual workplace and face its tragic downsides. Keeping abreast of the latest studies on how it’s increasing gender inequality and income inequality should be top of mind for any leader at scale today. For in the imminent future, being facile at speaking machine will require an even greater facility at speaking human.

I’ll be posting weekly as part of the Medium team’s special invitation for me to share what I’ve learned over the years about how to speak both machine and human. And if you happen to see this between the dates of November 10 and 20 in 2020, please vote for my SXSW submission “Safety Eats The World” if the 2021 CX Report at all interests you. Thank you for tuning in!—JM

Written by

John Maeda: Technologist and product experience leader that bridges business, engineering, design via working inclusively. Happily working at Everbridge☁️ :+).

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