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An experiment in which humans and AI augmented each other's strengths demonstrates how leaders can reimagine processes to create greater business value and prepare for the next wave of innovation.
In the longstanding argument about whether AI will replace or complement human beings, the new watchword is symbiosis. Most recently, Elon Musk used the term to describe how a brain implant might merge human and digital intelligence. But you don't need to go full cyborg to achieve a mutually beneficial relationship between humans and AI. Instead, you can reimagine worker roles and business processes to enable people and AI to collaborate and achieve something greater together than they could apart.
Given the swell of fear and questions around AI - from how many jobs will be lost to who will train these new systems - the question of how to achieve human-machine collaboration has taken on new urgency. After all, these mutually beneficial relationships, focused on augmentation rather than displacement, stand to boost business value while lessening risk of people losing jobs.
In order to create a symbiotic AI workforce, organizations will need to use human-centered AI processes that motivate workers, retrain them in the context of their workflow, and shiftthe focus from automation to collaboration between humans and machines.
To test that proposition, our company's innovation hub in Dublin, Ireland, conducted an experiment designed to see how human workers might augment the work of an existing AI system and embrace their new roles as AI trainers.
Evolving the AI Trainer Role
Working with a team of design, data, and software experts, and medical coders, we designed, built, and tested a software interface that enabled the medical coders to move from simply using AI to improving it, taking on the tasks of an AI Trainer, a role that teaches AI how to perform and iterate. Medical coders analyze a patient's medical chart, taking complex information about diagnoses, treatments, medications, and more, which is translated into alphanumeric codes that are submitted to billing systems and health insurers. This coding is critical not only for billing and reimbursement but also for patient care and epidemiological studies.
At the location where the experiment took place, an AI system had recently been put in place to assist medical...