Stories

Automating humans with AI

Binoculars with 0’s and 1’s in the lenses
Illustration: Eniola Odetunde/Axios

Most jobs are still out of reach of robots, which lack the dexterity required on an assembly line or the social grace needed on a customer service call. But in some cases, the humans doing this work are themselves being automated as if they were machines.

What's happening: Even the most vigilant supervisor can only watch over a few workers at one time. But now, increasingly cheap AI systems can monitor every employee in a store, at a call center or on a factory floor, flagging their failures in real time and learning from their triumphs to optimize an entire workforce.

  • A network of surveillance cameras hooked up to special software can tally the seconds of each worker's bathroom break or time each step of their work.
  • It can also keep workers safe, automatically detecting the absence of hard hats and gloves, for example, or people straying into the path of dangerous machines.
  • In some call centers, AI listens into every conversation, cataloging every word, who said it and how, and then scoring each agent.

Why it matters: Companies can use this data to juice workers' productivity and efficiency. Eventually, they could gather enough data from humans to train machines to mimic them."

How often is an employee going out to smoke a cigarette? How long a lunch are they taking? How long are they sitting in the lunchroom?" These are the questions clients want answered with AI software, says Kim Hartman, CEO of Surveillance Secure, a D.C.-area company that installs security systems.

  • Hartman says his company has put in video analytics for several area retailers and restaurants that wanted to monitor their employees' productivity.

In a handful of factories in the U.S., cameras have been installed over each worker's head in assembly lines as they put together car parts or electronics.

  • Software developed by Drishti, a Silicon Valley startup, watches these assemblers work, timing each step and checking for mistakes.
  • The videos let supervisors quickly figure out where something went wrong and teach a worker how to avoid repeating an error, says Drishti CEO Prasad Akella. It can also be used for training new hires.
  • And since AI is constantly watching the video streams, it can extract valuable data about timing and actions across the entire assembly line, which can inform new ways of assigning work.
"The most programmable machine on the planet today is still the human."
— Drishti CEO Prasad Akella

"Employers and companies attempting to extract more value from its labor force by making that labor more efficient is nothing new," says Jess Kutch, co-founder of Coworker.org, a nonprofit that helps workers organize. A century ago, managers used stopwatches to pursue efficiency under the banner of "scientific management," or Taylorism.

But extreme monitoring enabled by new technologies can be inhumane, Kutch says.

  • "In low-wage work we're seeing a lot more decisions that were made by a middle manager being outsourced to an algorithm," says Aiha Nguyen of the research organization Data & Society.
  • "What workers are seeing, and have a fear of, is arbitrarily speeding up workplaces," Nguyen tells Axios.

The creators of AI monitoring tools argue that their software benefits employers and employees.

  • Drishti provides workers and supervisors with valuable feedback, Akella says. Its software can call out high performers, reward efficiency-improving creativity and even keep workers from hurting themselves.
  • Akella argues that employees won't be forced to work much faster and harder because turning up the heat would introduce unacceptable errors.
  • Call center agents monitored by AI software from CallMiner prefer being graded by an "impartial computer" over a human supervisor, says CTO Jeff Gallino.

What's next: Extensive AI-annotated video or audio data about how people work is a potential gold mine for automation developers.

  • Robots are still too klutzy to take over assembly lines built for humans but could learn how to put together products in a machine-only environment.
  • Gallino says CallMiner could use information gathered from human agents to automate the "boring" parts of customer service calls.

Go deeper: Automated management for call centers (NYT)