What is Collaborative Intelligence?

Video Script (Video length: 3:50)

As you probably know, ChatGPT, Bard, Midjourney, and other applications are all examples of Generative AI. What you may not know is that Generative AI is just one of many technology categories that are used in the expanding field of Collaborative Intelligence.

Over the next few years, Collaborative Intelligence will have a significant impact on many areas of your business. This video series will provide a brief primer on this topic for business executives and other business leaders.

This is the first video in this series. It will answer the question: What is Collaborative Intelligence?

Collaborative Intelligence, which I will abbreviate as CI, pairs humans with intelligent machines, as they work together in collaborative pursuit of human-specified goals.

In a business setting, oftentimes the goal is improving the performance of existing business processes or creating new business processes that previously could not be implemented because they were too costly, too time-consuming, or impossible with previous technologies.

Collaborative Intelligence can also be built into a company’s products. How to design, build, and deliver CI-enabled offerings will be the topic of other videos in this series.

Many technology categories fit under the heading of intelligent machines, even if no physical machine exists, such as artificial intelligence like that seen in ChatGPT, or computational models such as those used to develop novel pharmaceuticals. Physical machines such as collaborative robots and autonomous vehicles are also used in CI applications. There are many other categories, and their numbers are growing.

CI-based process design (or redesign) focuses on assigning specific tasks either to humans or intelligent machines based on their strengths. Intelligent Machines are good at many things that humans find challenging, as shown here. For example, machines can complete the same task over and over again without losing focus or, in the case of a physical task, without getting tired.

Humans are good at many things that intelligent machines find challenging. For example, humans understand situational context much better than even the most advanced AI. We can modify our words and actions in ways that make them much more effective or impactful given the current context.

While workflow design leverages the strengths of humans and intelligent machines, it also builds in the collaboration necessary to make both more effective and more productive and make their work products more valuable.

Humans help intelligent machines produce better and more valuable outputs in four important ways:

1. By training the machines to carry out tasks and by providing feedback that allows the machines to improve their performance over time.

2. By directing the machines to complete specific tasks and by validating their outputs to ensure they meet expectations.

3. By monitoring the performance of the machines and making adjustments, repairs, or augmenting computing power to ensure smooth, continuous, and safe operations.

4. By acting as a liaison between the machine and other humans so that humans can understand what the machine did and why it did it.

Intelligent machines enhance human performance by

• improving their productivity,

• generating insights and supporting decision-making,

• analyzing large quantities of complex data and generating options for managerial action-taking, and

• by continuously monitoring situations and alerting humans to changes in specific conditions.

That is collaborative intelligence in a nutshell.

Thank you for watching.