AI = Augmented Intelligence: One More Time: Man + Machine (via HBR and SMR)

In a notable bit of synchronicity, the summer issues of both Harvard Business Review and MIT Sloan Management Review have feature articles advocating a more symbiotic approach to AI:

• Collaborative Intelligence: Humans and AI Are Joining Forces (Wilson and Daugherty, HBR), and 
• How Human-Computer ‘Superminds’ Are Redefining the Future of Work (Malone, SMR).

As Malone encapsulates it, what we need is, "an architecture for general purpose, problem-solving superminds: Computers use their specialized intelligence to solve parts of the problem, people use their general intelligence to do the rest, and computers help engage and coordinate far larger groups of people than has ever been possible."

Why do we keep forgetting how important such a symbiotic approach is?  As I have written multiple times on this blog (most recently in my last post):

Another very powerful aspect of networks and algorithms that many neglect is  the augmentation of human intelligence. This idea dates back some 60 years (and more), when "artificial intelligence" went through its first hype cycle -- Licklider and Engelbart observed that the smarter strategy is not to seek totally artificial intelligence, but to seek hybrid strategies that draw on and augment human intelligence. Licklider called it "man-computer symbiosis, and used ARPA funding to support the work of Engelbart on "augmenting human intellect." In an age of arcane and limited uses of computers, that proved eye-opening at a 1968 conference ("the mother of all demos"), and was one of the key inspirations for modern user interfaces, hypertext, and the Web.

The term augmentation is resurfacing in the artificial intelligence field, as we are once again realizing how limited machine intelligence still is, and that (especially where broad and flexible intelligence is needed) it is often far more effective to seek to apply augmented intelligence that works symbiotically with humans, retaining human visibility and guidance over how machine intelligence is used.

Both articles are valuable updates and teachings on how and why to pursue this understanding. But why is it so hard to keep in mind that what we seek is not man or machine, but man augmented by machine?