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Ethics of data use in development contexts

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how yes hello and welcome thank you Christian on and welcome to our panel entitled as you from the program big problems speak Tato little privacy affix of data use in development contexts the yes Men names that is Christian they're just continues me and I work for the vote of an institute much bond what that is the better from the Institute is the think tank for Vodaphone based in Berlin and the privilege to be 1 all the supporters of this year's Global iteration gathering alongside GIZ and the German Ministry for development and before I will hand over to our panel that just very briefly introduce and the topic of what we think it is important and if you include the term Big Data in the title of any event of discussion about its you always run the risk of boring your audience and and it seems as if everything has been said about big data from and Big data them is not only the buzzword it read seems as if it has lost its fashionable appeal it's miraculous or not but we think that this might just be the right moment Avenue and a sober look at the potential but also from of course the challenges and risks and connected with big data particularly in the developing of context on I mean is it is it really a high well if you look at data Big data and being generated through mobile phones is actually still a very new and still a fast-growing phenomenon and if you compare mobile phone data being generated in 2000 with the amount of data predicted for 2017 sexually multiplied by the factor of 100 so we start at the very beginning of the process and if you look look at mobile broadband subscriptions in Africa on the about 100 to 5 million of subscriptions and 2013 and for 2018 predicted that there would be 805 million so really a rapid growth and a and a and I think we still at the very beginning of that of that process and so we think Big Data certainly more than a height and you all know that's analogy that that you can hear very often that big data is the oil of the 21st century but what does that mean for Africa what is meaningful inequality of wealth and income and what does it mean for the fight against poetry and it has been claimed to the past steps of big data might be at least part of the solution of Africa's statistical store the tragedy of Sept of has been described before what what is the statistical strategy in Africa well we do still have rather about publishing data on reliable information many researchers don't really know what is happening on the ground and and of course in the past was was very and costly and very difficult to get data arrives at the expense of them and and talks difficult to collect and now you don't really need to a smartphone you can actually uh and gather very valuable and interesting data with basic phones the so called CD on the call detail records so well as the person who's doing call whom does that person called for how long and and based on these data the and of things you can for example predict what will happen based on past patterns in terms of predicting and know the spread of diseases young will talk about that in a minute on you can also get real-time information about human actions and behaviors and you can get real-time feedback also on interventions so when we do acts what will happen next so instead of having a lengthy and and so some expensive evaluations of you might just look at the very instant of an intervention and so that really also fundamentally tried to the changes so social research and and so your world research and development contracts and you can also reduce them have a new form of poverty measures from cell phone use because different people of different income a different background have different patterns of using the phone so you can see how where people moving and you know that about the construction and so on but I won't really go into all the details what what is possible we learn about uh that's uh you know and and and I would expect aspects in method that's and of course we do not only want to celebrate all these great solutions we also want address the ethical problems and challenges and that we are facing at the moment and I think it can be said that we do lack a conceptual and legal and ethical framework that lays out the principles of how to make use of the data particularly in emerging markets and developing countries who owns the state who can access the state and and 2 big problems to urgent problems justify interventions which might not push privacy protection to the background and how can we make sure that the people statable actually benefit the people and not only the place and be corporations and so on why is it the case that you know well of course you know many of these application happened developing countries because there are no strong presence of directional someplace and it's bit of a dilemma in opens a lot of opportunities for and but the reason for that is of that in the end it's it's fault idea really fall for the use of the customer because he doesn't have a privacy protections in place that we have in Europe or the country so i'm without any further to would like to hand over too young to be the 1st we thought we have a bit of a debate style panel here's young would be the proponent and sorrow would carry on and she will be the of governance and then we just on the discussion down thank you good afternoon everybody thank you deleted and it's a pleasure to be here and the sexual pleasure to see you 3 a good number of people here and in the we talk about big data so we can sell or sink and been concerned about the number of people attending the chase enough Republican and have been just the Running a very complex algorithms and I noticed there is a strong correlation between the people in the room and the number of of Kenyan leaders in battle right thank you so it's always gonna be fun to their again as the unwanted talk about a few applications of big data and in the development context the and development of electricity and that I been working for a tumor suggested the car which is a technology business incubator but in Senegal we all public-private partnerships so we have different type of partners but including telecommunication operators and so we had the great opportunity but to do a challenge of was that the communication operator or not tool to see what could be a potential of Big Data in a in a development context just to know you wouldn't know who was in a room the scientific background can you raise your hand if you have a scientific background 0 OK and who has a part background in the cool who has a literature background and who has the business background it OK equal and just religion and I have like various scientific slides but just to impress you a little bit is not because I'm a scientist or
uh so what is this other stuff for them up and you know I mean the challenges goal Big data data for development we see a lot of things for development are about R. N. Y. you know it has a is always has to do with Africa I has to be for development so that's maybe another question who has but just letting you know by this challenge that we run was all
shortest basically is the 1 of the largest telecommunication operator in in Africa uh and also the as a user monopoly in scenario and for 1 time having a monopoly that could be interesting so it's bay when the whole when the data their data just religion or on for 70 % of the markets in Senegal in terms of voice communication so it's freely and so they just for the research community stream benefits so different data about the mobility of the users are different data from about the and the localization of those and also the length of the cold the duration of the call and all those kind of thing and of course you know all the put all the data that there already have that the naturally collect our format your invoice and the anonymized it and we're gonna talk again about that the unknown the musician sorry for my english uh I don't know it's in English and this part is very complicated and so on so that's why you know it's uh we've been working pretty hard on that and so we have them in the results of the research community in synagogue and also globally so we used on the data from Senegal but open to the entire world why research community so you have to 160 research lab working on that are including 11 from Senegal and don't be another question we gonna raise is the ownership of the science and that that that has to be uh in emerging countries if you use the data of that we have an emerging countries and after a few few months or researcher street was a yearlong program we had 16 papers submitted scientific papers submitted 40 % of them are we're talking about transports 20 per cent of them were talking about health care the Annals about national stresses it so i'm just gonna share few of them and what could be the potential application I got so you have
the various scientific slave who looks cool but also not going to get into detail for that so it's a it's a new university in Asia but basically you can see the title all can we use mobile data to anticipate the spread of the a blood disease you know about this as being used in Africa we talk a lot about this but also science and then they I can really help us predict the holders gonna spread just simply by looking at the whole the people you the cell phone where they are different points can help you are in case of a disease and for the the spread of that we've been very looking synagogue we only have 1 case but with this kind of thing really helped arising in can help further in the future but another
use for electrification and in all of you if you've been in Africa you have for shut down that's a huge problem are and this kind of thing you know enables to to understand the bottom of the way people use the cellphone move from different cities to anticipate how can better omega system for lectures and this is very very important and why all this thing is very important is because we have no data so far it's not like in you rob or in the US where our government of the means to do this they died as you survey on everything you should go to synagogue because I don't really know the other country but listen synagogue we have none of that and that's a real challenge because if you don't have any data how can you plan relevant urbanism electrification care programs the and so this is where that could be interesting so another example then it's going to be the electrification of another 1 but
again and again so on health care is the predictive of malaria prevalence so we all know malaria is very useful in Africa and so just again looking at all the people move from different cities you can predict and this is all about different regions so let's take an example here if you have a big malaria prevalence in this region you can expect a disk spread throughout the entire region and the did that for all the tense region of Senegal yeah and that this is a paper from brown university so so no university from all over the world and sometime involving a Senegalese researchers and not of last 1 of the fund pretty cool because it's the traffic human traffic jam is you do most of you run the Harriers over the consonants and the as well so you see this is dark so this is where I 2 million people work every day but there is only here to hundreds Southern inhabitants and so you have all these people commuting every day over here and so the build beautiful highway spend a lot of donors money into building this I was expecting that is gonna have a huge impact and it is actually data is very interesting because it shows that yes it has you see in blue and the bar the city there are less of blocked by by traffic jam which is good points because in some way works with well but surprisingly there is a box here in the city we don't know exactly why that is completely more back than it used to be and is as something that is not you know obvious and so it's only with this data that we can look at that and of course after maybe the government they the can take decision to build another high where are of something like and so there was a uh paper from London School of Economics the and for the rest
of my Babel account you can send you the money over here that at the no of course not the
history and everything is downloadable from the orange website the 40 that the of gone are there is 60 research paper that have been published over there so you can definitely not look at them and go goes through it's pretty heavy it's pretty dense but if you don't have the like scientific brought under the very very interesting are and we can just imagine if we do that for all the countries the back and get it can have something lasers resting is only about 1 year of Mobil Oil Data two year 2000 searching and the challenge of course is to do I do that on a real-time at but that that also poses a question that we're probably debate after that the the so that going on with you suggestions and because we are a 3rd party organizer as an incubator we reach out a lot of the start of the research community but also the public stakeholders and I think this is very very important if you wanna have a successful Big Data project development context our you to to involve and the people on the ground because you need to be a sustainable businesses at the end you need to have like research while locally uh understanding the problematic issue in ratio of a researcher from MIT stand for working on this project does great 7 great scientific background but do they understand your local background and what they want to prolong was their research is it what you will you will need as a Senegalese people and that's pretty interesting so respect the privacy laws if there exists a synagogue laws like a year ago and is still not very much enforced so this created this condition for data privacy so it's a big challenge because you know we're going discuss about it you know it's pretty hard in most African countries don't have laws enforcing data privacy and you have to involve the ecosystem you have to connect are the researchers in the resource that fire locally to international knowledge and capacity and notably when you need super computer and people were able to build very um solid our goal is and the you also need to reinforce the local capacity and in this sense and of course after to be a sustainable businesses and this is really what interest us as a business incubator is maybe or of the 660 paper if we can have 1 or 2 stops really building products that could be used locally and maybe Auburn sourced are a different kind of model and that would be great so and this I just came out with that 3rd this morning so i'm gonna call that
during word rules of big data right so it's cover right you can use it but I just wanted to to raise a question for you and maybe through to open the discussion
uh because that not sure noise data are is the best way to predict the future and to to build a future because they died all about the bus right it's using what you've seen in the years before to build what could be a future could be interesting but don't we need maybe especially in Senegal between like disruptive technology and disruptive innovation that you cannot predict with the best data so I just wanna that you is this question on around big data of course there is the haddocks from them and there is also the use of that that is a servant well thank you very much
few thank you young OK so that seems to be all seem pretty straightforward great solutions and already framework thanks so much but also that of course challenges problems maybe unintended consequences and this is what I will talk about yeah and having 1 thanks having me and so there are lots actually things the and said I want to pick up on but just before I do I think it's kind of important to define what we think of when we say Big Data because lots of people have very different understandings may makes this conversation kind of difficult to have so when we say the data we don't mean open data that's if that's data in a certain format that's falls under was known as the Open Definition and it's machine-readable it means is downloadable means you can do what you want with it and when we talk about big data in mean massive quantities of data sets of data that can't be dealt with in the same way that has been done in the past and an extremely large datasets you can as young as explaining can analyze granted to find all sorts of things about human interaction and about human behavior and and patterns and trends in the kinds of things so it's in it's the kind of thing that's going to happen is going to become even bigger and bigger as time goes on because I mean as we all know where the meeting data all over the place and yet as as time goes on the challenges around the data can be anything from the way that companies think of it as they have to capture enough I have to analyze it correctly and and what I wanna talk about is is specific to the field of international development but so I think the biggest
question here is and lots of ways and who is collecting the data and and who is deciding what they do with it so 1 of the points the made saying and respect privacy laws if they exist at the Holy disagree with if they exist and I think we need a privacy law in a certain country to be able to respect privacy as a fundamental human right because everyone is human whether they happen to live in a country that has a strong I guess you have whether they happen to have a strong and yet whether they happen to have strong privacy legislation on this is something that really worries me and lots of the discussions I have in this field because people say all you know is a great thing in various African countries in various Asian countries and that's very weak legislation that means we can go and we can get all these insights and we can learn all these things it does reminds me of I mean that that told yesterday about and the role of technology in colonialism and power disparity is completely that it's it's you know pull people in poor countries without the legislation to protect them and rich people coming and saying how we want to learn all these things about you and then will use it to help you but I mean for example 60 papers were written I wonder how many Senegalese people read any of those to be honest and I mean the for example they showed none of them were by sending these researchers I and some of them where M I like putting that knowledge in academic papers this is great for people from academic institutions it's it's less great for the people who the data's being collected about and I mean there are lots of kind of brain noble sounding efforts around collecting data on really really problematic issues I human trafficking for example thank you will have this initiative wave talent here partnership working on human trafficking and trying to balance our and a company based in the US that work on that a 1 of the big they have and 1 of the biggest data-mining disseminated companies in the entire world and and then sitting at this Google Panting company partnership working on human trafficking trying to work out you know where things are going what's going on what happens there on the pontiff started as a CIA funded starts up later when we think about you know it's it's great it's very noble is wonderful but this is all data that will be eventually somehow going to the CIA because they're the ones who started that and that's another thing that is is very worrying in lots of these not that these partnerships and lots of these initiatives because their companies you are in some way in companies you have the technology to be able to do a lot to these big data or even this normal data projects are in some way linked to the US in some way to Europe the very very rarely but increasingly so which is wonderful actually based in the countries that they're doing the research on and and that means that in many cases you know that money's coming from different sources it depends where it's coming from it's coming from you know US aid the US government's development on have been involved in CIA operations so only saying organizing a great protection on this data when we're going to help eradicate poverty now you giving data to the CIA has not something that we want to be involved in it is not something that should be labeled as international development in any way and and ending but the data's being collected from so we have right that to these issues of consent in European in North America and something we talk but we have Munich terms and conditions numbers we them we take them and that's something that we're concerned about In most of these cases there aren't even any terms and conditions to consider its in telecommunications companies collecting data without anyone knowing and having no no option to opt out of theirs and so would look for example like thinking about some wants to take you use at a mobile phone in the country to make a phone call to do connected the family again the information is also a fundamental human right to and and you know if they don't have any option to opt out from the data then being given to From a telecommuting telecommunications company to another government to uh a company that's that's not really informed consent that's kind of the opposite that's doing it without them ever knowing and it's in it's in a wonderful like and this kind of arguments against us saying it's any metadata that doesn't mean a thing you can do just as much as bad stuff is you can do with metadata is you can with the actual cam transcripts of phone calls and so yeah I mean I guess the end is what of issues around around here you and agency within names and I would argue that like in not to these cases people don't have a choice and and they should that we do seem to be treating people in poor countries with lots of these big data projects as their the second-class citizens they didn't don't have human rights and when we have the same 2 conversations here in Europe we think about mn in very different ways you can see that in lots of things in international development generally like mn example is in the UK we have rejected the idea of identification cards because it's against you know a privacy rights that decays county funding identification cards in 3 or 4 countries worldwide but double standards it's it's fine is an international development project so it seems to be obtained that way which is something else a disagreement and just as an example I mean this like I think with lots of these projects we seem to think of them as like what's the best possible outcome that could come from all this data so I mean when we designing projects and in the end year world we often use what's called a Theory of Change this as like this happens and this happens when this happens in this happens Mendes really good thing happens when you think of them in the best possible way and a former colleague of mine has this idea of creating dystopian theories of change instead of utopian ones and say you as yet you think of what's the worst possible thing that could it can depressing sorry you give anything the worst possible thing that could happen with every single stage of your project and I think in lots of these products if we to do that would terrify us and it would be really really really awful and suggest giving something back and this is a quote from an added the article early this year from and someone is helping run a refugee camp in Turkey and so we it says and that by metrics ideas will be used for lots of good things any job opportunities education social opportunities but also and to identify those who have been involved in criminal activity and and I and mention this already think it's a terror is a great example of what I mean by the worst possible things that could be done with this data I mean if you knew who decides who is a criminal the Turkish government the Syrian government and not the US government what they do it back to you do you have any choice when you arrive in a refugee camp if you know that your considered to be a criminal for something that's actually took the within your human rights and you then walk away from a refugee camp in there somewhere else that you even have the opportunity to make that decision all major spaces like you know I'm gonna have to do if I want food shelter water which is a terrible choice and no one's ever have to make and and then another 1 is that this is a tweet that was from a meeting was held a couple of weeks ago about the data revolution so in in in international development with coming to the end of the Millennium Development Goals 10 15 AM and displayed now coming up with the Sustainable Development Goals and 1 big part of the Sustainable Development Goals is been around collecting and Dayton using data to make sure that Sustainable Development Goals happen as we said they would do and and yes this is something that you know so asking US government intelligence systems to be used as part of the Sustainable Development Goals and the double standards there are just so huge that when the US government use the intelligence on US citizens this terrible but when we use the systems to help other people poor people it's grave like it's it's it does remind say just and lasting and so basically I don't want to seem like I'm kind of on the innovation and not have it's just an unaided this is kind of off in the way they see their the argument frames at between innovation and conservatives and
all you know being really slow and bureaucratic and maddening and that's the argument I had another dichotomies we should begin with the tall I think we should just be being thoughtful thinking at the thinking of all possibilities and not being every utopian in what way a matching will happen with the data and am and yeah and just yet as being like that and we have this issue of I we have this idea is innovation being very quick rapid iterations and that's great in like a software is purely software environment you know agile development that kind of thing that in this would dealing with huge amounts of like people who are in the most vital positions in the entire world that is not that this is an experiment that we can tried it doesn't work try again of doesn't work try again this is a totally different situation and I think it requires even more cabin than we might necessarily do and given that you know we have we seem to be going the other way thinking all they don't have any laws like I'm new media came we shouldn't be abiding by the lowest common denominator of all these government hasn't caught up with a privacy legislation let's say that I have nothing happens to think of our but just to give you the between the 2 of you for a 2nd and you know I mean like a the you know very legitimate so concerns that that you've just expressed I just wonder what you think it should be done now I mean given the fact that you know we do not really have protocols in place of but we we we are facing the dilemma that the data is there and that we should make use of it in order to solve the problems and we should make use of it in any non actually should meet any of the sides of the things that and that's so like what you're saying about normalization being a huge problem I think maybe for it's just taken as an example like that you might analyze the data the opening available for making available right now but that's not the any dataset in the world about what that population so I mean minimization is going to become even even more difficult actually do the anonymization steady possible so that we should think of it as like 0 we should use this because it's that just because it's possible doesn't mean we need to do it hair OK to do share that view I mean 1 could also say if there is a problem that can be solved as atom from talk about spread of diseases so that we do not make use of it you know it's also it's not as an ethical problem that I really really was used outside of the maybe looking at different emergency case where we're you really have maybe to put a framework in this game of emergency to to use this data uh but I agree that there is no laws are to protect the citizens why should we heard a noise and and run into using those big data that may be a little too early doesn't have to be very careful also the question I'm asking that we will we always need to know those laws kick and we couldn't we files of type of framework of tidal flows to protect the citizens and maybe it's gonna be like an independent entity panels could be like different type of appear on watching of this thing along this thing it has a speed but I think you know if we wait for those to be uh applied but also after you know about past and forces those 2 different states that I think that we have so many low on and 4 so maybe we should like find all the way up to you to be able to use the the an activity providing can mean select data is thrown problem quite a lot is like all this problem we need to to solve it but actually like if we really cared about the spread of disease in an African countries which so out pharmaceutical companies and and patents make if we're in a rich country we can we really care about that we make sure that medicines available for them to use we would start analyzing data about certain populations that from a reaction from the reminder of probably 2 hours on the professional perhaps what happens that a after what's real and that the model so do whatever data are in the graph that you have no what really matters what do you do that right and if we still have no the same you list for the week of useful of the fossils tell the truth yeah and actually mean dated is just a reflection of what happens there is a reflection of whoever's collecting and how it's been collecting the data is neutral it's not biases in it and we need to understand that when when analyzing and that kind of life it's a problem that you know not many people who come from that culture and for that country are involved in analyzing and drawing these trends and drawing conclusions because it might mean something completely different compared to what we think it does and I think yet we have some standard like it in a spreadsheet it's neutral it doesn't have any bias is much must too peaky falls which is your so sorry for me to send it to you you you also work out a lot on you know the relation between digitization general trends and and policy making what is your take on that some caught some in between used and they will make very valid point and then because this is an unfolding phenomenon I think for me the thing that always makes me chapel is this rush to quantify Africa and so it's the new it's the new scramble importation of Africa through and so anything that looks like a dataset is going to be over analyzed and under contextualized to make sense of how Africa to eat or how Africa moves you know this the whatever and what people don't factory and out is a very fantastic example from the 2 bears laminaris of some well-meaning research I think from the US and gave women some tracking devices to see and how quickly they got 2 places to get water and back and was trying to help them minimize the time spent moving from their homes to radical get date and the water now I hadn't Candyman remember what the people that the that the research question or solution was made was this quest to also save Africa from itself and that but the thing this is wonderful welding researcher didn't in fact it is every day those women went out to be took a different out 2 going come back what he did take you know factory and this is what I want to introduce this conversation is the social element so too did his women want to visit their neighbors patch and because of the site of the slump the news from the other side of the Sun some business in the middle part and so the this president with a completely random datasets that conclusion was that his people uh crank rate figure 1 of the helps not want this lesson in fact any the call 6 and this is not coming in from this with this angle and what we're trying to do anything with some of the research we're doing is bringing that context it's that while the data is being generated in this case social media data of assessing how people Iike conversing about different issues say whether it's a voting process uh I mean intended for instance in 2013 we had an election that was under the guise of peace at all costs as so there's a lot of self-censorship that was being imposed of so media could only talk about things going well but everybody was in this quest to talk about how we were peaceful nation will putting on a show for the world because we're coming back from a context rain 2007 things have gone up it's out now and we we ask themselves the question or as Kenyans must something is off about this narrative let's put it in a place where people are trying to have conversations of beaming defaults to the world and this is social media most severely affected data and so what people were doing uh in terms of sharing about their their their experience to the what process and we found a hell of a story that nobody else is picking up on so in this case you know the question becomes do we know that the 2 because it's there and think this whole narrative I don't know when the wrong it is found so much insight we found that people were not not everybody was buying into OK knows what is a piece
of the not everybody was willing to say not you know uh suppress the social tensions the to play at that time you have given that ongoing work we have around monitoring online hate speech and in Kenya in Nigeria in South Sudan and even the online 1 of the things we're learning is the need context so I may have been the present was being tasked with initiating the project when it comes to another country context have no business trying to assume that I'll figure it out and they need other people from that context to do that work themselves and this is super important for anybody was going to be finding this work anybody who's going to say they want to rush to quantify Africa to deal for the Africa I forget and whatever for D offered you I got high I have I have a background well-meaning researching the beer and concluded that Africans of the Africans of the pure crazy because we need we need to factor in context now that also means that we we should not blindly look at data without looking at what of the events happening and this is that the risk that we faced with the world is not homogenous you know this is out of that fascination collecting data to predict events to predict outcomes on by humans don't operate like that you know we're not just like bottom is that what we're aiming to i mean this vested interest reinstates but until then that you know this context that is super important and this is where I guess in this whole debate it becomes a bit fluent and um this the other aspect of laws being formulated not necessarily to protect citizens but to protect the people were gaining access to the state and especially the private companies that we still pursue the uncle of talking about the loss what do we human make sure that human rights of social science and context is being picked up on site this is a gray area but I just my point again my take-away point that's something too quick to write the course you know to be in a rush to quantify contexts this so much more that goes into and and I would really interested what is what is your impression of the moment do you have a privacy debate at all so in in the country come from irreversible you have different concept of from the that have a lively debate is that elsewhere right and soul ending with the research into the select departure point becomes uh people who sign up to use social media people assign up to you straight people we signed up to use Facebook on the system public spaces on on the internet the you know the times and services and that becomes a service that nobody ever read those need that's a whole other conversation over another day we need to talk about how we work with the premise that you know people are aware of what is signing up for the going into a new public space it's a new public sphere so to speak and so we will never touch anything that is in a private domain will never go into monetary how socially heat is spread through what's Apple fiber anything like that we use that which is in the public domain and operate in that context that said with the big data that we end up with we also I'll learning and also advocating the notion of big data does not necessarily have to be open this whole thing is is false and notion that you know all data should be open how we agreed that these and goes back to a tyrosine not this is not neutral so when we collect data to assess hate speech collected a certain assumptions of collected the sudden death of questions so we can't just put it out there for anybody to pick up because it could be falsely you don't need to somebody being uh you know attacked for being picked up on by authorities in that kind of thing so how we work around the issue of from is we have a responsibility to other well to have them a sense that the term make sense of it makes little sense of it but it is very much from the conversations that are going into the notion of how as citizens elements in this case Kenyan citizens by using online sphere but we cannot prevent that data and not to just about anybody without a proper agreement that you know what this will not be used to but false you know of prosecute somebody out because that is the responsibility we have to protect that data the conversation of privacy I guess it goes back to when you avoid 1 9 are you aware of what you're doing it goes back to the individual and that is a function of education and awareness around that and I thank you would like to hand over to you she that of that I have some you have so many mobile entrepreneurs pitching their ideas and so many of the most suddenly and involves some kind of data analytics making use of data well what is your take on that topic this before I comment on that I have 2 ways that I feel I must mention so I think for most people that context you haven't been the tag is completely different yeah how we did looked at by most people elsewhere is that project Lakeland aid to help address as well as for most of the African countries how we look at it is not the ability to beat it's about sentences then after that to think about all mammals of using is it so it's not it's not it's actually I went extinct and that's why I had that that I was saying it exploiting the fact people is very easy because when there is no regulation and tool they don't soul for you'll be discovery in the lake I went to good to keep those things that have been given what want those entities and then Academy unified I is so we have we have problems to think about the the the top technically excessive a valuable tool they outside that looks at it as projects as sources of funding and is more options to set organizations in Africa and well liked in the Republic so for for this for the development of the the sort of have some a senior LAN and amines it to then they get shape to provide solutions to idea that problems in their societies what did the tap we do we come after the problems are solved in most of them I think that we have receptors that are essentially this we ask them and to do analytics of the detail what comes after that in most of them I think way why would way with a analytics for that I don't need analytics to tell you how to influence how people would have given it will leaving or something and to change whatever I just need to provide would be the most like for example the kids who were talking about the 1 to the right in what you can do with that data is called Pan and maybe what happens to the kids before they were using the application and then after so it's measuring something very stiff and and that I have a problem with saying the holes is quality that they tell how that if you talk about why you are creating the what is your problem you want to change whatever on the plot would you really want to have an impact that is read you want to solve a problem that is you I don't think for those we to be honest we wanted to change lights it was just yeah I don't I don't think they wanted to take their lives sold for that developed as most of them look at its as solving problems it was there that we did that traffic up that crowdsources traffic information and people fluent and I use it I have to think about why and each of these traffic on go really tell people this traffic along with but what that the tag give to that particular pattern can do I
don't really think much about and that's maybe being of the yellow and the Lord Young they've been very young and in the space we don't really look at it from that perspective we every time we buy right now for a few and that's why so many of the sites and I strongly believe in quality and could be knitting collaborating with with a lot of people in quality have because then they give the the point extract is a to you were trying to force like what this is to be true yeah can I just add that you know about involving the local people we we get in all page organizes thing and especially to enable the local stakeholders that we have the part of the challenge we have no involving the researchers our 1st this is the lack of knowledge of some research lab the sale we don't have this data that is the Harvest program of the of the in use and so the lack of machine like a really powerful computer like analyze the data and thing if you really want to have the people to to get scholarship for all the data and the research and to provide them with more skills or at least some the skill and resources and not on the very short term have already built on a long-term those calories surgical system and this is variable or otherwise is still gonna be data so that are vital cooperators from the outside they're gonna to be analyzed by the people from the other side for the people inside not as just wondering there and we can also make that of the more specific but the thing has to be done in order to ensure that people have agency have transparency and get involved in the decision-making process I mean you you all can mention the problem you know people that you know what is happening among that can be well uh and there is no legal framework really so and end you know companies in these images just just do it because the thing that have to do it but what can we really do what would be specific steps to enable people to be involved in the decision-making process what to do with data and when and how and for which purpose lighting and that we can explaining assessment it kind people in Africa said you know what's going on with the data whereas as those people in other countries do you not that traffic that we talked about I think it's called waves and my family in Switzerland use it like a like this 1 has a very similar set Council state and you have to sign up and you do all sorts of things anything actually most people have no uh no idea of where the data is going do is just the difference the main difference I can see is that you know where momentum African countries we have like European and North African and North American companies all donors a charitable funds coming and studying where's here if people try to do that in Europe that the mass about crime and be like 0 got a company that treating us like that with this this is basically you know this the same level of lack of knowledge or lack of and it's like lack of actual understanding of where data is going it's just you know where people research come and say on Amicon study you and then we can take all this stuff outside and that I think it's it's it's a terrible way to be thinking about the argument if every integer and it just brings to mind of IBM Research set up the 1st of the lab in review of 2 years ago and they he would have Big data and what of which solves this key 6 African challenges that identified None of the project the scaling not 0 and yet nothing yes and it's because the premise was really that that thing you know already the premise of what they see the world is the lab that you come to well for them because the context was lacking from from the researchers to the hypotheses and assumptions what we found with the work we do have the most effective way to get people to be aware of the what how the data is used is to be part of the conversation and synthesized back in that conversation so you know we find a conversation about of ethnicity in Kenya which is 1 of the drivers of hate speech and interjected that conversation topic actually based on a previous conversation other previous conversations on similar issues this is what happened in that were all out interesting that when I say to you about this it's picked up on an existing research we found well we could write papers we can I policy reason that kind of thing the best thing wouldn't in terms of engaging people is giving back through conversation and spaces you reach 80 engaging to generate that data insights based what we're finding and a has been super interesting getting people involved in fighting for their own freedom online because it's been about saying Look guys we see that you know this hatred being driven up by the same context based so much at this so much attempts to sort of counter so that self regulation mechanism is already citizen-generated you might that kind has been more than enough to empower people we haven't had to do much else yes and you you all seem to agree that the purpose of the data analysis has to be more or less clear from the beginning why do you do something by like you make that my due to that research I wonder is that and that is it you know in here to big data analytics that very often you don't know what you will find that the correlation which is kind of come on what you know what kind of open data set you work with then you discover something terribly interesting which might have a you know huge social implications but you haven't really been thinking about it from the very beginning because have you you wouldn't have had to do the data the analysis what I mean is that a lot of them are completely agree that because when we organize a lot from this G for other and sending out you all the researcher that no idea what to do with that and thus allows you start talking in organizing group session on specific topic this element you can do that and that so it's an entire process to other people really thinking about what they could do for their own context so you take an entire day and several workshops after that to make the people work together creating teams and after we know proposed a research project and the and of course you know after you have the idea of the project we also have the results are you able to really used as they that to prove what you like to prove and that's also another generation thank you and and so such you before you you may justify the 2nd just want to invite our audience be and have a couple of minutes left but and if someone has a comment or question the free we do have a microphone in the room and so on there should be a question of OK it yeah yes without the judgment on the right to 2 years so I have a question of timing we talk about the privacy issues of data and that's it's a bit of a hot cell in the development context 1 1 people are dying from whatever is on the boat and so so I guess is you what when you try to get the debate going on that's there for example of what are year you're most prominent examples that that we will mention them in the dimension to the Syrian refugee in Turkey that point of his life threatened flooding of biometrically identified 1 or other of the kind of like examples that make sure that the make the case also in the for the development community and any anything intense examples that you may need to be anything offset any privacy is a human right that that's it like you can try and think of as many examples of how this might be a terribly terribly wrong but you can't respect that everyone is a human being and if you're working in development you can't understand that everyone deserves to be treated in the same way should should provisionally working in development if the wind is OK but this up so I want if you
could do any of you could just speak to the question of like it seems to me that sometimes it's almost like a solution in search of a problem or people who do this kind of data science like you know I can do this with anything but I wanna do it on poor people and that's kind of that's the interest and I am I guess I've noticed also that a lot of projects actually maybe they're trying to an academic institution maybe they're not in not there's often not and ethics review process on Iady process which even some universities that doesn't exist but that they're like should be more of a certain set of questions that researchers need to consider before they just like to wrap into Cuba and start you know following people around trend of water and this can be rediscovered before that how can we kind of have a more of an effort evade research but also for these projects so young you mention you have an external device during the annotation and this a has the that very example we can have a look at the paper shared around on now I mean that's a valid question and I think this goes back to each individual country context and the perception we have about how i um others outsiders coming to your country induced and you find thinking can at the whole process of how the is not very clear to me like it's not this stricken they must go through an honest and that is 1 can institutions and especially the canon academia to sort of enforced that make like a manifesto that you know the the guiding principles not look at people as this will help less and that this is something ourselves we have to sort of like reject back to the world as it was always complaining about how you're doing it wrong and I'll take that 100 per cent of so I mean I think it's a question of each country in each context taking that up in making their own thing and a guide and the projector that yeah I that they say in science it's use of the so you can have whatever process at the university level it always goes back to the individual and what they really want to achieve on anything in this in this case no what is it doing well is the creating of 5 of the program of very independence Ethic Committee with 15 people from the sciences to whatever the type of background book on review if all of the paper and the ratio that we've done is relevant and ethics and I think this is the type of thing we we should do and maybe there's not enough and we should do way more and that's 1 part but after you know it's on a think it's also a lot of education we we have to make sure the people in those universities as understand better the local context as long as were of the needs so maybe it's like more collaboration of before the project leader during the project and maybe you know using the diaspora actually could be used maybe you to apply for such kind of project you have to have a scientist of from the diaspora or from the country maybe you can create rules like that that could really facilitate this and the relevance of the product and of the others that but and you have your audience yeah well yes it's made of sorry and the 1st row what a it's a it's a fascinating debate but it's not a new bit of and then I mean we could be talking about genetically modified we we're talking about something out I mean I was born in the need I believe in many island in the US at in the US have a social security number I mean ac I feel like in the US and Europe and that protected I mean this is the same problem I mean when I do a Google search all whatever I do mean the government should protect me but the NSC it knows more about me than Google does soul and I thing that anyone who is right or wrong I feel like it's just a topic that is going to kind of solve itself just like is the other things we involved in because I mean if I think of that point and I totally agree with you there there is an issue but at the same time as a researcher has a business person in knowing the factored state that is not available in Africa in and that is 1 of the key things I want to be able to know uh 1st gathered to collect that I want to be able to analyze the data a made but what I do understand what you're saying so that there is not like you would not have advocated the innovation but innovation is messy innovation is something that you can't really they're the people doing cloning but at the same time yet I mean you just don't know what I mean by that I mean if if possible you got a community effort at the same time know themselves in all this and it's messy you know and so my my issue is that you all right and kind of really kind of well that's something like scientific determine his money in happen anyway and with growing begin to show that it is this context I think will just summarize word context everything in context makes it more closer to helping us figure out what they're which and figure out that this project is partially to data analysis Penelope pressure journalism you know you drop it dropouts number 1 you that a word just touch about the innovation and I think just the love of the last slide I had I think if you we have also too much data and data research we not gonna go anywhere just gonna replicate what we hope to see in what you want to see and researcher you know when the use those they that they already have in my what it was that was data for the used the date of all is gonna do that who has maybe what we need is the other thing that nobody knows the disruptive innovation descriptive research and that's really my concern most especially supporting text stops we don't take star of to do something you know that is just replicating what we had in raw on the US 10 years ago and that works even in the consumers of by incidental discover saying OK does not make good business maybe but if you really want to to catch up in some way we need like amazing thing that we cannot predict and I think they guys on the very bad because the gonna help personal just predict the the short on future and not having this destructive effect just think about this laughter is there any way you could have data is is really so we should do batteries for the car or the other thing even space X over the design of reading that are the word order Collobert those are really good this is the same for me and I want to be model when use data to figure there thank you again the following simple before we even start talking about on shape of the the town we mediate in developing countries our data that is linear so the fact that we're talking about close the tag where talking of at a point of the small they title percentage of heavy-duty that's thank you so much of putting everything into perspective the analysts a wonderful panel and the use of the thinking of the then the
Spiegelung <Mathematik>
Statistische Analyse
Generator <Informatik>
Ordnung <Mathematik>
Selbst organisierendes System
Virtuelle Maschine
Weg <Topologie>
Endogene Variable
Mobiles Internet
Ganze Funktion
Chirurgie <Mathematik>
Offene Menge
Wort <Informatik>
Faktor <Algebra>
Prozess <Physik>
Familie <Mathematik>
Element <Mathematik>
Metropolitan area network
Urbild <Mathematik>
Lineares Funktional
Plot <Graphische Darstellung>
Konfiguration <Informatik>
Arithmetisches Mittel
Framework <Informatik>
Projektive Ebene
Web Site
Physikalische Theorie
Data Mining
Speicher <Informatik>
Bildgebendes Verfahren
Leistung <Physik>
Fundamentalsatz der Algebra
Personal Area Network
Magnetooptischer Speicher
Physikalisches System
Design by Contract
Umsetzung <Informatik>
Gesetz <Physik>
Statistische Hypothese
Deskriptive Statistik
Streaming <Kommunikationstechnik>
Trigonometrische Funktion
Trennschärfe <Statistik>
Elektronischer Programmführer
Regulator <Mathematik>
Shape <Informatik>
Gebäude <Mathematik>
Mobiles Internet
Güte der Anpassung
Kontextbezogenes System
Dienst <Informatik>
Rechter Winkel
Automatische Handlungsplanung
Analytische Menge
Überlagerung <Mathematik>
Service provider
Open Source
Delisches Problem
Peripheres Gerät
Protokoll <Datenverarbeitungssystem>
LASER <Mikrocomputer>
Stochastische Abhängigkeit
Automatische Handlungsplanung
Elektronische Publikation
Patch <Software>
Abstimmung <Frequenz>
Kartesische Koordinaten
Prozess <Informatik>
Figurierte Zahl
Nichtlinearer Operator
Konstruktor <Informatik>
Zentrische Streckung
Gesetz <Physik>
Twitter <Softwareplattform>
Ganze Zahl
Strategisches Spiel
Interaktives Fernsehen
Kombinatorische Gruppentheorie
Framework <Informatik>
Bus <Informatik>


Formale Metadaten

Titel Ethics of data use in development contexts
Serientitel re:publica 2015
Teil 106
Anzahl der Teile 177
Autor Rahman, Zara
Birgen, Sheilah
Deissner, David
Sambuli, Nanjira
Beux, Yann Le
Lizenz CC-Namensnennung - Weitergabe unter gleichen Bedingungen 3.0 Deutschland:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben.
DOI 10.5446/31970
Herausgeber re:publica
Erscheinungsjahr 2015
Sprache Englisch
Produktionsort Berlin

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract Big Data is the buzz word, not just in the context of the Germany economies attempt to take digitization seriously Industry 4.0 but also in development cooperation.

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