What is collaborative intelligence?
“Collaborative intelligence” is cooperation between humans and artificial intelligence. In the workplace, this synergistic relationship allows both parties to play into their strengths. Humans bring creativity, leadership, interpersonal skills, and judgment to the table, while AI offers rapid quantitative analysis capabilities.
Since AI can perform tasks impossible for humans and vice versa, collaborative intelligence benefits everyone. Indeed, a study by the Harvard Business Review “found that most firms achieve the most significant performance improvements when humans and machines work together.”
For tech-positive business leaders, collaborative intelligence offers to increase company productivity, profitability, sustainability, and more. Below, we outline three approaches to achieving these benefits.
Three Approaches to Collaborative Intelligence
Oversight. In this approach, AI handles the “heavy lifting.” It carries out various tasks under supervision by human managers, who ensure that it works correctly, efficiently, and ethically. One high-tech example that’s soon to be a reality is the AI-driven car, which a human operator would control only when necessary.
Another example of the oversight approach is Synaptiq’s recent work with our client, DICIO. We used machine vision to develop an emotion AI model that captures emotions (e.g., happy, scared, etc.) and another that measures stress (by measuring heart rate). This system runs cybersecurity in the background of DICIO’s applications, checking that the user is who they say they are and acting of their own volition.
Augmentation. Unlike oversight, the augmentation approach puts humans in the driver’s seat. For instance, Honda and Volvo brand their version of Tesla’s “self-driving” tech as a “pilot assist” — in other words, as a tool to aid human drivers. Another example is the online application Grammarly, which uses AI to generate spelling and grammar corrections. Although the user does most of the work, Grammarly’s AI contributes support.
Split roles. The split role approach separates human employees from AI so that both parties perform work suited to their strengths. For example, consider the healthcare industry. In some hospitals, AI analyzes blood and tissue samples while, separately, human doctors interact with patients, determine diagnoses, and construct treatment plans.