Managing human productivity and creativity with machine learning

SeattleDataGuy
Sep 20 · 4 min read
Photo by Jack Hung Tr. on Unsplash

There is a lot of talk about machine-learning models and automation taking away jobs and replacing workers in every industry.

However, the impact middle-management algorithms are already having is talked about much less frequently. This isn’t some far-off, in-the-future concept. Machine-learning models are already acting as managers of people.

Several companies have begun managing people using algorithms and models instead of people (with varying levels of human interaction). Just look at Uber, Lyft, YouTube, SoundCloud, and similar companies. All of these companies manage people and their means of productivity and creativity with algorithms and models.

These companies manage content creation, performance, and productivity with no or minimal human interactions. Instead, they have subverted the need for much human interaction and allowed an algorithm in some data center to make those decisions.


Uber/Lyft — Managing Human Productivity

Uber and Lyft are probably the most visible examples of algorithms for managing people.

These companies use various algorithms to efficiently find the closest drivers, the best routes, and the most effective methods of transportation for their customers.

This is with minimal human intervention. Uber drivers don’t ever really need to interact with their human bosses. Instead, their livelihoods are dictated by a model far off in a server somewhere telling them they need to go to 4th Street in rush hour to pick up Jamie who needs to go the airport.

This manger also listens to customer reviews at scale (something that really couldn’t be done before). This ensures drivers behave even without people watching. The algorithm will even provide tips on how to improve your rating if your rating falls to low … like some strange automated performance improvement plan (PIP).

The current verbiage on the Uber site states, “ Deactivation is only used as a last resort, and your account may be activated if you take certain steps to improve.” This wording sounds similar to a PIP, an old-school HR tool where if your rating or work does not improve, you will be let go.

Uber and Lyft are more than platforms. They have created middle management at scale. They manage, review, and attempt to improve driver behaviors with minimal human intervention.


YouTube/SoundCloud — Managing Human Creativity

Everyone likes to talk about the YouTube algorithm and how it can make or break you. If you get noticed by this mythical algorithm and recommended, then you’re automatically skyrocketed to internet fame (at least for that video) — similar to the way that stars were once made by agents, managers, and casting directors.

What some people realize and others don’t is the YouTube algorithm plays a similar role as an agent. It knows generally what is popular and trending with their audiences, and it then picks and chooses talent that matches current needs. Fidget spinners could be on trend this week. Or maybe a lot of articles are popping up about an upcoming fight or musical event.

The algorithm uses this knowledge to drive what it believes will be popular to the top. This algorithm replaces the manager who goes around to all the dive bars listening for the next Beatles. The algorithm just tests new artists and creators to see what the audience wants.

In many ways, this algorithm doesn’t just dictate what content will be watched. It also drives creativity.

Think about SoundCloud. SoundCloud acts similar to YouTube, dictating what new talent is popular at scale. Lil Nas X used this to help drive “Old Town Road” to the top. He created a hybrid song and marketed it in such a way that it skyrocketed to success.

Even in this case, one might argue that the algorithm forced creativity. Oddly, these machine-learning models are almost more flexible than typical managers. They seem to allow room for people to experiment and test out ideas when it comes to content.


Conclusion

Algorithms and machine learning are already managing people. It’s not some future event. It has already slowly started to dictate what we watch, listen to, and who drives us around.

All of this is happening with minimal human interactions (unless there is some sort of problem).

These companies have found methods to manage people at scale. They can drive creativity, productivity, and much more with just a few tweaks of their model. The key in this algorithm-driven world will be to remember that at the end of the day, people are people. We aren’t machines, nor were we meant to perform like machines.

Better Programming

Advice for programmers.

SeattleDataGuy

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#Data #Engineer, Strategy Development Consultant and All Around Data Guy #deeplearning #machinelearning #datascience #tech #management http://bit.ly/2uKsTVw

Better Programming

Advice for programmers.

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