2:01
>> Sure.
 So this is in fact, one of the most interesting projects that I've worked on.
 And while this is not really a commercial project,
 it was an a R&D project, and it was done with media labs Asia.
 So there was a team from media labs Asia, and of course looking.
 So this is what we set out to do, microfinance.
 That's the area that we were delving into.
 And microfinance, lately, of course has been very popular.
 So the Grameen Bank in Bangladesh is very well known, etc.
 So microfinances sort of defying this where financial services of
 all kinds including loans and savings products, insurance, etc.
 All of these is provided to pour the segments of the population,
 they're disadvantaged, underprivileged, low income,
 stay in very remote areas or in rural parts of the country, at least in India,
 which are very underdeveloped in terms of just infrastructure, so on.
 So microfinance is provided, at least in India.
 It's built upon what we call the self-help group model.
 The self-help group is just a small group of people in, say, a village.
 They have built a sort of infrastructure where
 all of them form of a kind of non profits group where
 the objective is that they are going to receive loans from
 microfinance institution that works inside district.
 And therefore goes to every village and sees if there is a self-help group and
 then the microfinance institution will channel money, loans,
 etc., to the self-help group, not to an individual.
 Because an individual who is poor and does not have enough collaterals.
 Is unfortunately not a very viable entity to lend money to.
 But it's a self-help group, because it's a group and
 there's a lot of group pressure on every individual member to
 return the money to not default, etc., social pressure.
 Therefore, it makes it a much more viable proposition for
 a microfinance institution to come and lend to that entire group.
 So the self-help groups, they're sort of built from the grassroots.
 It is a grassroots movement.
 So far so good.
 Now, there are some folks who are consist of members
 who are largely illiterate or functionally literate.
 Which according to the government of India is somebody who can count basic numbers,
 can sign instead of sort of having the fingerprint kind of signature module,
 they can sign and they can read simple sentences.
 Now, definition of simplicity or that is but
 nevertheless, you get the point, someone who can do a little bit of reading and
 writing in that look line which is called functionally illiterate.
 So these groups would mostly be,
 they were consist of members who are completely illiterate,
 the people ran the group would be functionally illiterate.
 And the other interesting thing we found is we spend months in a rural
 area staying in the village in order to really understand how this
 group function, and they got familiar with us, with the team.
 In doing that we also realized that,
 there was a certain kind of person who was often used as
 the person who documented the transaction that happened.
 Very important who was given the money,
 who returned how much of that money all of those things.
 Because largely they were illiterate, so the children, so,
 sometimes they would be a ten year old boy.
 He would play this very important role because he could read and
 write, so he would be the person who would document everything and
 he would be paid like 20 cents a month [LAUGH] to do that but
 that's a lot of money for that little kid in that little village so
 that's how these would operate.
 The challenge is that because it's getting and
 because there is no system to really be very sure of
 what is being recorded and it's also in sort of format of course
 which sometimes it gets destroyed, they lose stuff, all of that happens.
 So the microfinance institutions have a little bit of a challenge in
 really being sure of what happened to the money that was given last year.
 How as they monitor it.
 It's a difficult proposition.
 And for somebody from the micro finance institution to travel to remote areas,
 to be able to actually go there and
 see all the documentation that's on paper, and make sense of it and the do,
 in someway capture all that and bring it back to wherever the MFI is located,
 the central place where the computing systems are located.
 All of this becomes difficult, expensive and hence most of the time,
 and advice kind of see going to really small villages and
 working with small self help groups in really remote or small very rural areas.
 Is not a very sustainable.
 And so what we wanted to do is to look at how could one create a system
 that would make microfinance accessible to the most remote areas,
 to the most rural populations without somebody having to travel there.
 Could everything be documented and
 sent without a manual of somebody coming or somebody going, etc, etc.
 So that was the problem we set out to investigate.
 And what we found as we went to trouble fees,
 state of the villages and understood the bar equations.
 Interestingly most of themselves have groups aligned with them.
 So the women are the ones, they form the group, they're very responsible about
 making sure the money that's being led, the person who is supposed
 to give back a certain installment on this date in this month that happens.
 If they feel that that woman's husband is.
 Is alcoholic and he's drunk and he's wasting the money then all the women in
 the group will come together to see how they can help this woman save enough money
 to give back to the because
 the women know that if they have to then those sirs and
 madam's who come from that MFI they will not be very happy, and maybe
 next time they'll not able to get loan as big amount as much they got this time.
 So it is very run by all of this decisions all need by women,
 groups are run by women.
 So that also the very interesting set of experience that we had then
 I have to say while we doing the study, we would be in the villages and
 the research team would always be given this chairs,
 they say we are still in sort of furniture, to sit even if is
 out in the village square which is an App.
 That kind of floor.
 But there you are, sitting on the chairs.
 And everybody else is there all watching on the ground.
 13:37
So we switched.
 We were very sad, because those designers he thought, we found a new
 way that we can deal with any kind of challenges
 if it's a challenge about language electricity etc but it just didn't work.
 So what would work was really representation [INAUDIBLE].
 And really representing the task very very clearly.
 Not abstract but very clearly.
 That worked well and we did something else even what
 we did is we called it an iconic legend.So we found
 back in the element the groups learned these elements,
 the icons,the etc, we want them faster when they asked us,
 and we clearly gave them an audio description we verbally told them.
 This is what it is, they asked us another time, this is what it is and
 they learned and they told each other, and so it is very quick.
 So now what we did is only interface we had a feature called Iconic Ledgers.
 There we had all these icons that were there on that interface.
 And each one had audio feedback.
 So they could just click on the icons.
 >> Mm-hm.
 >> And they would hear what it is.
 And it would also demonstrate what it does.
 Mm-hm!
 >> And we found that worked so well, they'll launched it so well.
 And they felt much less inhibitive to then try that feature out.
 You get actually a little bit.
 So this were some of the things that should work finally.
 And what we did, we also found Color.
 They were very quick to recognize
 few color cues just the way they used it in their paper letter.
 So red with always and a q for the folders.
 So without they didn't have to know who.
 They just knew the moment you saw where in the sequence of the table.
 A person's name continues the next person because he is in a certain sequence and
 certain number.
 If it goes red, then you'll be in default.
 So we use those cue of colors that they're familiar with.
 >> Mm-hm.
 >> And that helped a lot.
 Now.
 What we finally decided and this is something this work continued.
 And you should definitely look up Dr. Tappan Parikh's work.
 He was in the University of Washington at that time when he came and
 he was working on this research project with me, Labs and with us.
 And then he went back, and he was the primary sort of
 mover in terms of the technology that was finally used.
 16:25
What he created at the end of this project and when we realized,
 we had to keep the paper artifacts, and combine technology with it.
 The paper artifacts were critical if this was going to succeed because
 they were very, they had so
 much familiarity and trust of these paper artifacts that was shared.
 So everybody could pass that paper, record book, or ledger,
 from one to the other, it went there, they opened it.
 Whether they read or not, they felt familiar knowing, here I am.
 This is the row where I am.
 And I'm in green, I'm not in red, and so and so.
 So all of that, sharing that, keeping it with one of them.
 All of these things were very important for them.
 And so we knew that we had to keep that.
 So what Tappan finally did was he came up with a system which he called Cam.
 And Cam was because of the important role the camera in the mobile
 phone actually played in this particular system that he designed,
 and subsequently it's used for many others such projects.
 So what this did with that it had an application which you could use it for
 entering and processing data at the microfinance institutional end.
 But, on the field, for the self-help groups,
 they could use the camera in the phone to scan, to take photos,
 document, any of the transactions which were
 handwritten in the ledger, and to then be able to send it.
 To collect, all of that was archived and then sent to the microfinance institution.
 And so Tappan created documentation,
 I mean paper ledgers which included a bar code based system.
 So whether it was loan applications,
 receipts, other documents, everything was printed with an identification bar code.
 So now the Cam software enabled the mobile phone camera to scan that code,
 identify what the document is, take a photograph,
 process what data came with that document, what transactions were there, etc.
 And associate that data that came with that document with that barcode,
 and then it was sent off to the MFI system.
 And so now there was this whole flow that was created between this small village,
 this informal way that they were recording things,
 to the big city where the main computing system was located.
 And this created, to me this created the sort of the sustainability
 of the idea that self-help groups could document things.
 And that could be a stable, cost effective system for the MFIs to use that data,
 and track and then everybody benefited of, that's the intention.
 That the self-help group, then because all the documentation is always
 submitted in time and is there with the MFIs, it can analyze that data.
 And the self-help groups can get better, more loans,
 depending on how well they've done, have they not defaulted, etc.
 They can negotiate better rates, so on and so forth.
 So that was the final system, the hybrid system that was designed for
 microfinance institutions.
 >> It almost seems like bringing big data to very small groups.
 And that suddenly one of the big challenges is the original microfinance
 sort of depended on the fact that the group would manage things, but
 it looked at the group as a group.
 It didn't have visibility into the individual transactions and now,
 when you have visibility into those transactions, you can do analyses of them.
 You can identify potential problems before they occur.
 Obviously, that's not just good, they're risks there that
 the MFIs might over interpret things without the local context,
 but it's an interesting solution.
 This seems like it fits in
 20:46
a whole stream of work that businesses, as well as NGOs
 are trying to do in these particularly rural, low-literacy areas.
 I know I've talked with folks at Unilever that were interested
 in finding ways to make a local home into a distributor that
 could get products to people by developing systems that didn't
 require the customers to have a significant literacy level.
 But that would create a local market where you could order things,
 and they would be delivered to.
 I expect this is probably a pretty common pattern in India.
 >> Right, and that whole Unilever model, those women were called Shakti Ammas,
 Shakti is power, and Amma is mom, is mother.
 And it became again, it became quite a case study.
 You know how successful that was and how it transformed the entire,
 sort of the empowerment of women in these rural areas,
 largely rural, but also very sort of smaller urban areas, etc.
 And it was fascinating to see some of the films that have been made on that.
 And how individuals, who became these distributors in Shakti Ammas,
 how they became very different people.
 And how they had transformed a lot of things.
 Disease, occurrence of disease, infant mortality,
 the figures became better, disease control was better, because these Shakti Ammas
 became these major, sort of, empowered women, who knew what the problems were.
 And they also used a lot of Unilever products,
 whether it was the oral hydration when there are these
 sort of gastro intestinal diseases etc.
 So, all of that happened because of that model.
 And yeah, so there's a lot of that happening at least in India for sure.
 I'm sure in other countries too.
 >> And I think it also just reminds us that, yeah, particularly those of us who
 are older in the field tend to think of computers as things that compute.
 But these days that computer is so much about these other functionalities,
 about storage and archiving and communication and
 you didn't have to do very much obvious computing.
 It wasn't about doing the addition, subtraction and ledger,
 it was about how do we photocopy this and scan it and transmit it.
 Yeah, they can do computing in the backend, but for
 the folks in the village what mattered is that they suddenly had a fax machine.
 [LAUGH] >> Exactly, exactly, and Tappan often said
 that I think a lot of his colleagues, back in the computer science department said,
 but shouldn't you just eliminate the paper altogether, it makes no sense.
 Why would you keep the paper there?
 I mean, the whole idea is that you you need to make it much more efficient, and
 get rid of the paper, and he was like, no, that's not what it is about.
 I think you are absolutely right.
 >> Yes, as somebody who remembers growing up with a passbook for my bank.
 I always wondered if I just typed in a number there and came in,
 would they gave me that amount of money?
 But of course they had records.
 But the passbook made it tangible, it made it trustworthy.
 And clearly there's a whole bunch of people who if they see something with
 their signature, their handwriting and an amount, they'll believe it.
 And if they just see that a phone screen says you owe a certain amount of money,
 that's not very trustworthy.
 >> That's right, yeah, exactly, exactly right, yeah.
 >> So, well, wonderful.
 Well, thank you for sharing this interesting design case with us.
 We're delighted to have you with us again.
 And I will remind everybody that this was Apala Chavan from
 Human Factors International.
 This has been a design case on supporting low-literacy financial
 self-help groups in India.
 And we'll see you next time.
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