Problem Solving Versus Appreciative Inquiry

“The only irreplaceable capital an organization possesses is the knowledge and ability of its people. The productivity of that capital depends on how effectively people share their competence with those who can use it.”
— Andrew Carnegie

The development of the practice of appreciative inquiry (AI) traces back to David Cooperrider and Suresh Srivastva in the late 1980s. They felt that problem solving was often limited by focusing only on what isn’t working, and not on further developing what was working well. (Visit the Appreciative Inquiry Commons at Case Western University). The book, A Positive Revolution in Change: Appreciative Inquiry by Cooperrider and Diana Whitney, puts it this way:

Appreciative Inquiry is about the coevolutionary search for the best in people, their organizations, and the relevant world around them. In its broadest focus, it involves systematic discovery of what gives “life” to a living system when it is most alive, most effective, and most constructively capable in economic, ecological, and human terms.

If you have had any introduction to AI, you have probably seen the table below. I have yet to track down the original source of the table. If anyone knows please post in the comments section.

problem solving vs AIYou might look at this table and say, “that’s just semantics – appreciative inquiry is solving problems, right?” The difference, however, lies in AI’s capacity-centered approach, and its deep belief in human potential. Yes, AI solves problems, but it is deliberately constructive in its focus on keeping those same problems from reoccurring.

I plan on posting a number of ideas related to Asset-Based Community Development (ABCD), an approach which uses approaches like AI to mobilize communities. More on AI when we explore the concepts of ABCD.