5 Things Chuck Can Teach Us About the Digital Workforce

by Richard Lynch, on May 15, 2017 8:00:00 AM

AI and Human CollaborationAs a fan of the Subway cult classic “Chuck” I was intrigued as to how far away the technology featured in the show is. For those not familiar with the show’s premise, Chuck, played by Zachary Levi, is a Stanford dropout who opens an e-mail from his ex-roommate and all the National Security administration and CIA databases gets downloaded into his head. Fearing security risks, the CIA sends him a handler played by Yvonne Strahovski, to help the government make best use of the download known as the “Intersect.”

Although neural implants are still in their infancy, artificial intelligence and humans have been collaborating for years in our everyday lives.

  • A da Vinci robot operates with a team of doctors to perform complex surgeries.
  • IBM’s Watson works with the Weather Channel and meteorologists around the globe to help avert human and commercial catastrophes.
  • Alivia Technology’s Absolute Insight is teaming up with fraud investigators to combat Medicaid fraud waste and abuse.

These examples are opening eyes to new capabilities and the skills required to make them work.

Here are five things we can learn from Chuck (our virtual agent) and Sarah (our human digital worker) about the new digital workforce:

  1. Chuck and Sarah performed better when working together.  AI isn’t perfect. For example, it gets a medical diagnosis wrong about 7% of the time; humans about 4-5% but together they are wrong less than 3%. Robots, however, are closing this gap.
  2. Chuck’s ability to “flash” or spot outliers in large cross-referenced data sets made Sarah a better CIA agent. While making Sarah more productive, AI developers of the algorithms must have some idea of what type of anomaly the AI is looking for. Chuck needed Sarah as well.
  3. When Chuck had to look for patterns in data or tried to identify images, Sarah had to guide him.  For example, driverless cars can’t yet handle a left turn. Humans do this complex move millions of times a day. This is call “theory of mind”; reacting to visible clues such as what a pedestrian is going to do at the intersection — especially in Boston!
  4. Chuck’s capacity to find the needle in the haystack (big data) is a daunting task for people, but it was Sarah and her colleagues' ability to act on the insights that fixed the CIA or NSA process so the problem wouldn’t reappear. While predictive analytics can spot fraud, waste and abuse, people still need to streamline the investigation process, harvest the resources, and monitor the benefits.
  5. Both Chuck and Sarah needed new training and recognition skills.  Humans need to learn how to solve big complex problem with new tools.  Robots must be trained what to do and algorithms need to be refreshed based on what the robot is learning (machine learning).

Good training content for robots is also good training content for humans. Like Sarah, today’s worker needs to learn how to work with and appreciate the benefits of AI. HR strategy should shift from teaching people to execute a task, to help them learn how to think and solve problems.


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