AI Business / AI Projects / AI Systems / Diversity / Intelligence Amplification / Teams July 30, 2021
Here is my advice to CEOs about AI.
Much of what you already know as a leader can be translated into the introduction of an AI “team member”. You know:
- How to build and manage teams
- The value of diverse teams for improved decision making and productivity
- The need for continuous and thoughtful team redesign, to meet your organization’s changing needs
- The value of infrastructure that you provide to maximize your team’s success: you know how to create a shared culture, with collaboration mechanisms and protocols, all effectively optimized for each unique team
- You know that if you are not mindful of these elements, you might lose the powerful benefits that come from hiring strong and diverse teams
Let’s consider diversity in particular. It is widely recognized that diverse teams tend to perform better, and there are best practices for managing them. One is understanding that having a diverse team, on its own, is not enough to achieve success. Some choices when it comes to team mixes are better than others. Teams must foster a shared culture of collaboration, and it’s your job to establish protocols and standards that effectively optimize for the unique combination of team members. This maximizes the value of this important resource.
It turns out that team-building principles can be applied to partnerships in which one member is an AI system. Doug Englebart called this “Intelligence Amplification (IA)”. This can be unexpectedly challenging, but massively rewarding, as AI’s and human cognitive strengths are highly complementary. Of course, however, AI systems are more alien than the most diverse human team member will ever be. Don’t underestimate the “otherness” of these others. Hence all the normal concerns take on new dimensions, with more challenging opportunities as well as pitfalls.
This lifecycle of a human team member could be a model that translates into the machine/human collaboration framework. When a company considers hiring a new employee, it likely considers phases like: Job Attraction, Recruitment, Onboarding, Training, Performance Assessment, Increasing Responsibility Overtime, Corrective Actions, Promotion, Backups, Succession, Retention, and Termination. This is a good enough lens through which we can view interactions with a silicon-based team member.
Good delegation skills are particularly relevant here, as several routine tasks are now delegated to machines (such as recommending a product to buy on Amazon, or deciding what advertisement to display on Facebook). With the increase in automation, a widespread concern of employees is that AI will replace them and/or their role. However, a more pressing concern is how to use the best systems, methods, and frameworks that support humans working side-by-side with machines. So instead of job loss, we have jobs that change, to those that leverage humans’ unique capabilities and leave routine tasks to machines.
Companies that work out how to integrate AI systems into their human teams will be able to outpace those that rely on humans alone.