Editor’s Note: The work described below was carried out in 1996, by Charles Elliott and Mette Jacobsgaard from the Cambridge Partnership for Organizational Transformation. A full account of the work appears in Locating the Energy for Change: An Introduction to Appreciative Inquiry, by Charles Elliott, IISD, Winnipeg, 1999. Mette Jacobsgaard, a lawyer and social scientist, is currently doing research at Cambridge University in England. With extensive experience in Africa and Asia, she works as a free-lance consultant in development aid out of Denmark and England. Mette is using Appreciate Inquiry (AI) as the preferred approach to her work, and it is her dream to make AI the basis for all development aid work.

After several hours’ drive by Land Rover through the Mauritanian desert, we arrive at a cluster of tents, a few clay houses, and a small mosque. Welcoming us himself, the village chief expresses some surprise at our appearance: "We expected the aid agency, but there is only one white person—and that person is a woman!" Clearly, the village has anticipated a delegation of white men and now holds high expectations of what we might contribute.

Previously, my colleague Dr. Charles Elliott and I had conducted a one-week AI workshop for a group of Mauritanian aid workers and a few volunteers in connection with the agency’s wish to expand its activities into new areas of the Assaba region. Workshop participants were to test and combine AI with their knowledge of participatory rural appraisal (PRA) as an approach to project identification. Following the workshop, Charles and I each moved with a team of local project workers into a village to facilitate the further work.

As the work progresses in "my" village, the villagers forget about the white woman (me), as I keep myself well in the background. Although I facilitate the preparation of each meeting, designing protocols and rephrasing the PRA exercises, local project workers carry out the actual activities themselves.

Rephrasing PRA with an AI approach is working wonders! Never before have the project workers heard such rich and amazing tales as those emerging in response to such questions as, "Tell us about a dry season when things worked well for you." [The dry season in the Sahel can often challenge survival of animals and humans alike.] Very often the stories evolve using local metaphors. In the energetic atmosphere that surrounds the AI approach, much laughter abounds; most significantly, respect is given to contributions from all—women and men, young and old—in an otherwise hierarchical and male-dominated society. Ideas for questions arise from the various mapping exercises in the PRA, and the questions are always phrased in a story-like manner designed to elicit the best of the past. After the first day, a senior project worker remarks, "Usually, I do most of the talking when we meet with people. With this AI approach, they do all the talking and I can’t stop them!"

Until our arrival, the villagers have never had an opportunity to hear stories across gender, age, and class barriers. At our final meeting, the chief notes that they now have their priorities clear and, more importantly, they know their own capacities. As his final remark, he says, "It would be nice if you [the agency] can come and help us, but if you don’t come, we now know that we can do this by ourselves." This is the first time I have heard such a remark in my fifteen years of working in development aid.

"How can we ask street children if there is anything good about living in the streets!" exclaims a Ghanaian social worker in reaction to our embedded-evaluation project for street children in Accra, Ghana. This project, in order to learn how better to assist such children, is setting out to befriend street children, meet them on their own terms, and discover more about them. Our starting point is this: who better to evaluate a project to assist street children than the children themselves?

During a week-long workshop, project social workers and other stakeholders (representatives from the Ghanaian government and donors) create interview protocols to use when interviewing the children of the streets. It is difficult to overcome the traditional assumption that "the streets" are a bad place to be. With the appreciative protocol, however, interviews reveal new (and at times surprising) information. Soon, the social workers begin to appreciate the merits of the AI approach. For instance, a question like, "Tell me a story of a time when you felt really happy living in the streets," generates a response that provides information about the intricacies of an alternative social structure—information that would be difficult and time consuming to obtain through more-traditional questions such as, "Why are you living in the streets?" Furthermore, the AI approach meets the child on the child’s own terms: sometimes there is joy to be had through life in the streets, and sometimes there is not. Also, it is certainly not always bad to be living in the streets.

A week of such interviews creates new and valuable information for the project. But without shedding some of their own assumptions, the interviewers would find it nearly impossible to meet each street child on his or her own terms and then accept that child as he or she is in order to learn more. Appreciative Inquiry has provided an opening and an opportunity for the project to "walk its talk," and done so very successfully.