This quote (copy-pasted below) details why IBM decided not to use the name "Watson" which is how they have branded their super-computer around the world but when they bring the technology to Africa they call it "Lucy" after the earliest known human descendant, whose remains were discovered on the continent. It is unclear from this presentation what the technical difference is between "Lucy" and "Watson."
Quote from Transcript:
"These problems are well stated, well known. Many of them are almost cliches, the problems are hard problems, the difficult to solve problems in Africa. So how are we going to address them? Well, project was...now why have we called this Lucy? Not far from here, about 3 million years ago, a woman walked upright. The name would be... Lucy, she's been called by the anthropological community, the archaeological community, Lucy. We don't know a lot about her but we strongly suspect and believe that we are all, we are all every one of us is related to her. And she lived in an environment...in a beautiful environment, which we all enjoy here in eastern Africa, in Rift Valley. And she lived in an environment and she managed, and she managed to be part of something that would become today's humans. So we chose the name Lucy, because Lucy reminds us that we are all connected. And we're all connected to our environment. And we're all connected to those hard problems, those problems of energy, and food and health. All the problems that Lucy had to deal with in her environment. That's why we call [inaudible] and what's Lucy going to do? Lucy is going to help us to marry together cognitive computing and problems of Africa."
AO: Here the interlocutor describes a project where having the data available to look at (rather than just the final output) would have been particularly helpful. She also describes how it is difficult to ask the same client for funding to go back and conduct the qualitative research again because in theory it has already been done by someone else (even though the data from the initial research is not available to look at). To me this seems to suggest that clients and funders need to also consider datasets as part of normal expected project deliverables... and if that is the case, better guidelines for the care and management of such datasets need to also be in place for such clients and funders to ensure that they are appropriately handling and storing this data.
"Angela Okune 53:06
Okay. So in such an example, would looking at the transcripts that had already been done have been beneficial you think?
Definitely. So that's also the question of... we have a current project that's going on here...research has been conducted. And we have the results, but we don't know what informed those results, and when you look at the results... You're meant to design an intervention. So let's imagine if ummm ... I'm trying to think of a good one they were covering...They're trying to get people to...women who are pregnant to go and deliver in a clinic rather than relying on traditional birth attendants. So in that example, we, we have...the report tells us a couple of things that people like traditional birth attendants, because they can be in their home, they have the comforts of their home, and they don't necessarily like the clinic. We don't know why they don't like the clinic, and we just have that final... "they don't want to go to the clinic, they want to go to the TVA." And so for us designing the interventions, we don't know what we're designing for. There may be 10 reasons why they don't want to go to the clinic. Is it because it's not a nice space? Is it because it's too far away from them? Is it because they can't have anyone else in the room? Is it because they're forced to give birth in certain positions that they don't think are suitable. And so if we knew more around the why, then you could design better interventions. So someone has already conducted that research. So it's hard to face the client now, if they won't give us the transcripts because they don't have them, we need to go back and do qual research, because in their mind, it's been done, you can just work off the report. So it would be useful to have it in those cases, because you can identify gaps and know what things you should go research rather than starting from scratch.
Angela Okune 54:40
That is a really good use case of why we should share research data and why it's not just enough to have the final report."