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IGF 2020 – Day 10 – WS213 ‎Bridging ‎the ‎data ‎divide‎ ‎for planet, people and prosperity

The following are the outputs of the real-time captioning taken during the virtual Fifteenth Annual Meeting of the Internet Governance Forum (IGF), from 2 to 17 November 2020. Although it is largely accurate, in some cases it may be incomplete or inaccurate due to inaudible passages or transcription errors. It is posted as an aid to understanding the proceedings at the event, but should not be treated as an authoritative record. 




   >> The chat feature is for social chat only and only the question and answer feature used to ask questions for attendees.  And the session is recorded live streamed and hosted under the IGF code of conduct and UN rules and regulations.  Have a great session.  Thank you.

     >> MODERATOR: Thank you very much.  I think we are welcoming our attendees at the moment so we will just give people a few minutes to dial in, and we are just past 8:00. 

     We will just give people a couple of minutes to settle in and then we will kick off in a few minutes. 

     I will give a little introduction and we will then have four speakers giving a little roundtable and giving their opinions and followed by questions.  So we look forward to a good session so just we will be starting in just a couple of minutes in case there are any slightly late comers.

     >> MODERATOR: All right.  I think given the numbers are staying stable, I think we will probably just get started and other people if they are joining late, it will be great they can just join in.  Thanks, everybody, for joining this session as part of the virtual IGF.

     My name is Duncan McCann.  And I'm a Senior Researcher and I lead the digital economy program for a think tank in London called the New Economics Foundation.  And our kind of mission is to rethink economics as if people on the planet mattered.  And my job at the foundation is looking at the digital economy and especially putting people and social values at the center of that.

     So today we are going to have a really interesting session on how we start to bridge the data divide around the world.  We heard a lot, obviously about the digital divide.  But there also remains a data divide, not just between countries but also within countries. 

     And in fact, what we have seen is the data value chain be monopolized by just an ever-more concentrating fashion by fewer and fewer players.  This workshop is going to bring together a few different people, and we will hear some interesting talks to debate and think through how we might start to de-concentrate some of these data value chains so the wealth resources are not captured at the top and by a few large multinational players.

     And we're going to understand how to shape a more equitable digital economy, so it is not all concentrated in just a few countries and allows us to maximize the potential available to us through the kind of advance of digital technology. 

     So we're going to have four talks today.  I'm going to let the speakers introduce themselves in a little bit.  So first of all, our first speaker will be Nicole.  And she is going to talk through really some really exciting kind of concrete examples of how we might build some of this platform and data infrastructure to really support the platform cooperative business model. 

     And so Nicole has got some really exciting information about real-world examples of people actually going out and doing this which is just so exciting.

     And our second speaker will then be Obasegun, who is going to be talking to us about his learnings from using data science and civic technologies to support public and private sector organizations in Africa.  I'm excited to learn about the work he is doing.

     Our third speaker will be Deepti from IT for Change in India.  And she will be telling us a little bit about kind of policy challenges around governing data value chains.  And outline a really exciting vision for what they are calling a global to local data governance framework that promotes equal democracy.  Really looking forward to hearing about that. 

     I will finish off talking a little bit about my work in the United Kingdom and around Europe, and I will be talking a little bit about some principles around the part of de-concentrating is turning off the tap for the data platforms.  How do we start to minimize the data they collect? 

     As we go through, feel free to request questions.  There is a Q&A part in Zoom where we will collect questions and put them to our speakers.  Hopefully we will have between 15 minutes and half an hour at the end for questions, and I will wrap up to close.  With that long introduction, we are now going to start the presentations.

     And so I'm going to ask Nicole to unmute herself.  And you have 15 minutes, Nicole.  And I will try and give you a little bit of a warning when we are getting close to the time.

     >> NICOLE ALIX: Thank you.  Can you see my screen?

     >> MODERATOR: I can, yes, looks great.

     >> NICOLE ALIX: Is it okay for everyone?  Do you hear me?


     >> NICOLE ALIX: Thank you for the invitation, and thank you for your presentation, Duncan. 

     I'm very happy to present what we are doing here in the EU, and especially in France.  I hope I wouldn't be too long.  So I'm listening to what you say, Duncan.  My English is not completely fluent, so I have to look at my presentation.  I won't say everything that is in the presentation, but you can go back to it because I will, of course, leave it here.

     As far as you explained, I will give you some examples of what you call de-concentrated value chain.

     And this is the examples of platform co-ops.  I will show you some concrete experience.  And I'm just looking at how I can, yeah, this is it.

     Concrete experience especially in the context for COVID-19.  Because now national governments, cities and regions put digitalization at the top of their investment priorities.  This is the case on the national level, and this is the case here in the European level.

     At the same time, as you know, there are concerns about how digital platforms monetize and platform wise this is a term we use here, almost any aspect of our people's life, including the most sensitive ones. 

     And the crisis has shown it's an increasing phenomenon.  There is a lot of protests here against Amazon.  I would say about platform developers based on Democratic governments and links to the territory and try to share the created value to take care of the users' well-being.  And I will say a word about data.  And, of course, the turn to social activity and environmental protection. 

     So, where are we?  I have created four years ago sort of, well, association, a think tank.

     We are making links between the practitioners and researchers as far as we could here, social economy and research and practices of the comments are linked.

     We try to promote working groups.  And one of our projects, one of our working groups is platforms, it which means platforms in common, three years ago. And the idea was to bring together French speaking with open digital platforms. 

     We saw that between collaborative economy and free software and social and digital economy, there was something to do.  Someone is telling me something.  Shall I have a look to the conversation or is it fine, Duncan, I can just --

     >> MODERATOR: You focus on your presentation, and we will take care of what everything is going on around.

     >> NICOLE ALIX: I'm also used to looking at the presentation.

     >> MODERATOR: Yes, of course.  Don't worry about it.

     >> NICOLE ALIX: Platform des Commons is a working community.  And we have links connections with the other people, other organization at the EU level.  They are French, you know, because they are small, and we are trained to use the proximity. 

     We are working with the network for cities and organizations of social economy, SMARS, which is cooperative organization trying to promote the idea of freelance cooperative workers. 

     DIMMONS, a research group in Barcelona and companion in Sweden.  The idea is to build and ecosystem of platform and create comments and cooperation.

     So what are platform co-ops?  As we all know, sharing economy is needed because we can connect people and projects and we can do a lot for territories.  But building startups is not the only way to do it because it create negative externality and as this workshop and this session is showing, the question of ownership and use of data is one of the main question.  And tendency to monopoly and degradation of the value and centralized government.

     We have proposed two different kinds of platforms to create a network based on a charter with five principles.  You can have a look.  This is five principles. 

     The first one is inclusive governance.  Of course, we don't have time to describe what it means but, of course, we try not only to give explanation in the charter of what are under this, you know, expressions.  And we are trying through the different platforms La Coop des Communs to feed the definition of each area. 

     The first, inclusive governance.  The second, fair distribution of value.  And third, data ethics.  Fourth, production of commons.  And commons and especially on the digital level with the question of intra-operability between the platforms.  And if you have question, we can go back to that afterwards.  And the fourth is cooperation between members, cooperation between the different platforms.

     You may now know that there is a global movement.  We created the La Coop des Communs three years ago, but we have four years ago organized a meeting in the economic and social economy in Brussels in order to -- because we have seen that some people in the States have launched a movement around fair internet, internet of ownership. 

     So afterwards we call that platform cooperativism.  So we are working here in the EU, but we have launched in connection with this international movement, platform cooperatives and consortium.  I don't have time to present all here the platforms, of course.

     But I just show you a few examples in order to demonstrate that you can have different types of activities.  Here you have Smart x Pwiic.  This is the idea that helping in your neighborhood and helping in a peer to peer relation.  They are based in France and Italy.

     Another is Coop Cycle, a digital delivery for bikes and proposed delivering services.  They are a community of local co-ops that share the experience and resources and, of course, during the pandemic they have proved that they were very, very useful. 

     And the idea as far as data is concerned that they have created free software, free only for the co-op and they can provide the software and all of the program to local communities.

     Another example is on supply chain for food distribution Open Food Network, and this is an open source digital platform, and they share their data.  And also France Barter, another type of platform.  Because it allow marketplaces, non-profit marketplaces between companies.  For instance, if you don't use completely one novel type of goods you have in your company, you can share with others. 

     So you can set up your own community, you can join the global barter.  And it is mentioned here that the City of Paris offered the subscription fees for companies during the COVID in order to promote France barter.

     Of course, what we tried to do is to prepare new models because the feeling we have with all these things, you know, about data, about platforms, about new type of works and of jobs, it is that we try to address new type of issues with some institutions which were built in the past and we have which are not completely prepared to face this new type of issues.

     So what we would like is learning from the crisis.  And we like feedbacks, you know, in order to see how the different let's say at least local authorities and the companies and citizens have been faced to send questions using dominant and capitalist platforms.

     And we would like to promote solutions with decentralized platforms specialized in their fields and operable because they have centralized system.  So how to prepare new models, this is a real question.  And obviously not just to promote this idea.  Of course, as far as the platforms don't sell the data, don't share the data with people who are going to make profit with the data. 

     They are not in a level playing field with the dominant platforms.  And they are not a level playing field with the dominant platform because also they take care of the users and take care of the workers on the platform.

     So to create the ecosystem with the platform, it is challenge for the next months and for the next years.  So we have, you will have the reference in the next slide. 

     So we want to prove that platform co-ops are new territory infrastructures for cooperation.  Not only new economic models but also services and devices for the local authorities and for the government, in order to promote another way to work with collaborative economy.

     So here I give you some reference.  We are not a research organization, but we are working with researchers and we also are able to promote studies.  So we have just finished a study which is in French.  So you will find this report on platforms on our website. 

     We have a forum on the beginning of December, it is also in French but maybe there are some French-speaking participants here.  Of course, it is at distance.  And this is the second forum for platform co-ops we organized with the City of Paris.  And you are all welcome.

     And at the EU level, we have collaborated with the partners at the beginning of my presentation, a position paper.  This position paper tried to show that to find a place for platform cooperatives in the context of recovery because you may know that the EU is preparing EU recovery plan.  And we would like that talking about digitalization and whatever the EU could find place for decentralized solutions. 

     And our job is to try to establish networks and connections with -- between all of the decentralized solution.  And also, of course, to find the way to have a level playing fields for them.

     And we will participate in the next European social economic summit in Mannheim in Germany in next May.  And, of course, everyone more than welcome to this event.

     I hope I answered to your request by presenting this concrete example.  And I'm listening to your questions if you have some.

     >> MODERATOR: Brilliant.  Thank you so much, Nicole.  Not only really, really interesting presentation but also absolutely perfectly to time.  I know that the work that Nicole and the co-ops de commun have been doing is great. 

     I spent a whole year trying to set a platform cooperative for drivers so to compete against Uber.  I know many of the challenges make it difficult and having an organization like this that can help by providing the technology that has already gone through the journey is just hugely valuable. 

     And I know from many cycle co-ops here in the UK, I mean CoopCycle I know best and they are great at spreading this infrastructure.  Absolutely fantastic stuff.  It was nice to hear about it. 

     I think we will take everybody's talk and then bring together questions at the end.  Attendees, please put questions in the Q&A, otherwise it will just be my questions at the end.  Thanks very much, Nicole.

     Now we will go on to the second speaker today so I would like to welcome Obasegun for his presentation.  Nicole, you might want to stop sharing your screen.

     >> NICOLE ALIX: I'm sorry.

     >> MODERATOR: That's okay.  So, please, Obasegun, you have the floor.  Please introduce yourself, and then 15 minutes.  If I see us going a lot over, I will just let you know that we are over time.  Thanks so much for joining us.

     >> OBASEGUN AYODELE: Thank you very much, Duncan.  My name is Obasegun Ayodele, a co-founder and CTO at Vilsquare. 

     We are a research and development center in Nigeria focused on develop Africa and the goal is to connect digital strategy and technology to transform African communities.  Vilsquare Africa. 

     When you look at the economies of the countries, they are segmented into cluster communities.  And we tried to work with the cluster communities, helping them with technology, with strategy such that they are able to connect to whole digital economy and move away from the analog processes to more digital driven processes.

     So what we usually do is we intersect between government agencies and the private sector.  And today I will be sharing a lot about our work.  Basically helping bridge that data divide, and how we basically take local communities, local businesses SMEs, microscale enterprises, how we take all of those different people that are disconnect and connect them to the data value chains that are valuable either through the government or through private sectors.

     A very good practical example is what we did with the seasonal rain for prediction in January.  This was way before the whole COVID pandemic happened.  We were doing research with the government, and then we realized that most government agencies if you look at the data value chain, which are 12 stages, most government agencies only have four.  They only identify, collect and process and analyze and stops there. 

     It is not released or submitted or given to the people, and they can't organize it.  With the data meteorological agency, they had research of weather forecasts for the all of 2020.

     And they have done all this throughout 2019.  And they have published this particular research in a hard copy journal which was sitting somewhere.  So what we did was to work with them to be able to retrieve that data, put it in a form that is indexable, and then plug it into an existing system which we had built for local farmers to get SMS notifications of weather forecasts of tips, of advice and recommendations how to plant and all those kind of things.

     And at the time we didn't know the pandemic was going to happen.  The data alone in a country like Nigeria will have most of the south, southeast and States in flooding and half of their lands were going to be lost to floods.

     So we did this, we reached out to the community which we already built.  We have -- in one of our cluster communities for agriculture, we have over 50,000 farmers who are local farmers who contribute to the food basket of the nation.  And we reached out to them.  We created a broadcast stream to them.  And we are sending them this information from January up until August.

     And then the floods came.  And then we realized how powerful this information we were giving them was because they were able to preempt that the flood is going to happen and have an early harvest rather than wait until the floods happen.  You have crops like onions which is now really expensive in Nigeria.  It is a depleted flood so if you have the flood you cannot get to harvest. 

     It was interesting how we work hand in hand with the government and get this important information and pass that on to the farmers.

     Another interesting thing which we realized which I will be talking later on, is how we are able to empower not just people in Nigeria but people in nine other countries across Africa with quality education.

     So when COVID happened, we realized that -- not realized, we all saw that we had to go on lockdown, and we had 9 million children out of school immediately.  We were looking at what that will do five years in the economy.  If you look across Africa as a whole, we had over millions and millions of children who are out of school.

     So what we tried to do was to create an alternative for them for learning.  But we wanted to fill up existing infrastructures that had already been developed in the past.  And then it was difficult because we realized that most of the high-end private sector positions had built the interesting online learning resources but they are really expensive that low income communities, areas with zero internet connection couldn't have access to that. 

     We decided to break that digital divide whereby we tried to match high-end learning materials with people who are, you know, put out in low purchasing power economies and bridge that all together and make it available for free.

     We have sustainable planning and we basically made a bunch of the resources which before would have been so expensive to have access to, make it available for people to use.  And this was really exciting for us. 

     After launching in June, between June and now we have grown to 10,000 users across nine countries.  And these are students who wake up every day and log on and they are able to take their schools and studies without having to worry about the disadvantaged economy or I don't have access to the right resources.

     We also tried to incorporate some high-end technology where we use AI and analytics to understand the learning paths and do recommendations on topics and other paths they can do and other interests. 

     We took the high-end technology which was not really developed and opened and brought it down and made it for all whereby there is inclusiveness where someone who doesn't even have access to clean water, who doesn't even have access to a comfortable shelter can have access to learning at an affordable rate.

     And when we look at all of the different things which we were doing, we realized the key thing we needed was the system of how information has been shared.  We have interrogated so many processes using the FOI Act which is the Freedom of Information Act and tried to look at by the angle if only we could make government, if only we could make private sectors and make it a source and transparent in the kind of information shared. 

     If every platform which has been created is provided with an easy entry, a business model in whatever solution they are trying to offer.  If you are trying to offer a solution, we understand and you can offer an easy entry business model, probably something like what Zoom has.  Zoom provides 40 minutes free and you can make calls for 40 minutes.

     Those kind of things are tools or models that bridge that barrier that is in their wherever people of low income cannot have access to.

     We also tried to work with the OGP, the Open Government Process to look at how citizens can properly engage with governments and private sectors and there can be proper two-way feedback system whereby the government can have like town hall platforms where they listen to the citizens talk, you know, and get those feedback.  And then they are able to iterate how they engage with their citizens.

     So this is some of the things which we have done.  And I'm open to questions as we go along.  And share more light on some of the interesting case studies which we have done across the continent.  Thank you very much.

     >> MODERATOR: Thank you so much for that.  That was really, really interesting.  And always fascinating to hear real stories of people really trying to take this abstract thing, data, and actually make it useful for people in their day-to-day lives.  So yeah, some really powerful stories there.  And so thank you very much for sharing.

     So again, yes, please do keep those questions coming in.  And as I say, once all of the speakers have gone, I will try to manage a sort of interactive conversation with us all.  Thank you for that.  We will move on to the third speaker.

     Our third speaker is Deepti Bharthur from IT for Change.  Deepti, I'm going to let you introduce yourself a bit further and then 15 minutes.  If you are getting close to the time, I will let you know.

     >> DEEPTI BHARTHUR: Thank you so much, Duncan.  Hello, everyone.  Pleasure to be here. 

     My name is Deepti Bharthur, and I'm from IT for Change.  We are a research and advocacy organization based out of India.  And we essentially work at the -- in the intersections of technology and development and all things that fall in between.

     A major part of our work has been advocacy around democratizing data and the value of data and framing adequate global to local policies around that particular topic.

     And I think I have a very hard act to follow because we have had some standout examples of what is really, really working well.  And I'm so happy to hear about the positives that exist in the world. 

     I will drag you back to a little bit of a dark place because I want to talk about what is not working.  And I want to point out the issues that I think we have been investigating in the course of our research and advocacy here at IT for Change.

     Coming to the topic that, you know, today's session is about the data divide.  I want to start by saying that the data divide is not a divide in the way we conceptualize the idea in the digital realm, as a lack of something like, for instance, lack of access to connectivity.  At IT for Change, we long recognized the problem of the data divide is really two problems. 

     One, the problem of data concentration in the hands of a few very large interests.  And on the -- and what we have seen is the once open network of the internet transmute into a privatized economic structure controlled by very large technology corporations.  The term big tech, which is used in common parlance today to refer to these companies which go by a variety of alphabet soups depending on what is involved at the moment.  But Gaffa, and it something else earlier, et cetera, et cetera. 

     This has become an easy placeholder to signify the phenomenon of corporate control of data value.  And the inordinate power that accrues to corporations the way they are able to exercise ownership and control over the network and the various economic stakes and the data value chain.

     Big techs are the saleable market power while through hoarding data and using digital intelligence as a factor of production is manifesting itself in different forms of databases control.  The Amazon-ification of the world.  What started as the online sale for books is today the world's marketplace for everything. 

     Over the past two decades, Amazon has followed a strategy of data value capture and consolidation and all acquisitions in retail, media streaming, health, more.  It's ventured into offline services like Whole Foods, the grocery chain.  And the movie theater most recently, AMC.  It's been working in the finance layer integrating various kinds of customer and merchant payment infrastructure. 

     And perhaps most significant, and what doesn't get talked about, is its data-driven strategy through Amazon Web Sources.  Its cloud storage and cloud computing services layer which controls 14% of the world's cloud computing market.  That's a very big number.

     It hosts the backend not on for major tech companies like Pinterest, but also SMEs, startups, state and public institutions and agencies, including notably the Pentagon. 

     So it means that Amazon's control over this particular layer of the data that even its competitor, Amazon Prime, the video streaming, its competitor Netflix is also relying on AWS for its cloud services.

     We see the stakes both in terms of across different verticals as well as different layers of the same vertical.  That is one of the ways in which we have been noticing big tech acquire database control across different sectors.

     We also see the tech companies use intelligence as a way to competition and empty the playing field all together.  I want to give the example of India's large flood platform.  Big tech in India and not known abroad yet, but not too far, I guess.  And it has substantial funding from SoftBank. 

     And what the company has been able to do is harness data from users and partner reference on orders and consumer preferences to develop its own line of cloud kitchens which are today outpricing and outcompeting the very restaurants from whose data they were able to build the intelligence infrastructure in the first place.

     Both my colleagues and previous panelists did speak about the COVID context, and I want to mention that COVID-19 has really I think thrown light on a phenomenon that was happening already, but has I think accelerated in the past few months which is the ways in which large technology corporations like Microsoft, like Google, like Amazon, et cetera, have been able to venture into very critical development sectors like education, like healthcare, like logistics.

     You know, you have governments in Australia and Canada that tied up with Amazon for contact tracing and for delivery of medical equipment.  You have Microsoft advising I think everywhere, the UN system as well as like different governments on how do we pivot to online education in the case that onsite schooling and learning is not going to be part of the plan for a long time.  We are seeing a lot of these different types of moves happening.

     And what happens as a result of this is that the wholesale capture of data and digital intelligence and the course of deployment by big tech has resulted in a highly skilled global digital economy.  It is about data concentration on one hand, and it's about data disposition on the other hand.  And the statistic probably really spells it out as to how that happens.

     90% of the market capitalization of the world's 70 largest big tech companies is today in the U.S. or in China.

     The EU, its closest next, has a share of 4%.  And Africa and Latin America put together account for about 1%.  We can see just in this sort of numbers how very vast these gulfs are, you know, amongst the private interests, amongst certain geographies and amongst the peel. 

     This is not a result of standout innovation, there's usually narrative goals or some kind of extraordinary business management.  It has been the result of a governance vacuum. Though there are many, many different layers to this and many aspects to this, what we have concentrated on are four critical areas which we believe have created this governance vacuum.

     One being the fact that traditional competition love frameworks which have traditionally focused on consumer protection rather than structure and health of the marketplace have really failed to check horizontal and vertical integration practices. 

     It has not taken how digital intelligence is part of the game and captured and accumulated and allow for the cannibalization of data into the ecosystems of big tech. 

     It was only in 2019 that the Department of Justice in the U.S. actually started to look at a decade of acquisitions made by these very large companies, the Apples and Googles of the world.  And started looking at the fact that smaller startups which never meet the bar for regulatory reporting anyway were being bought out essentially for the data to amass the data and bring into the larger system and enclose it in the large proprietary system.

     Second, competition is a large part. while data is recognized as the most valuable resource of our times, there is no appropriate global government regulation that can regulate data flow.  What we have seen in the past few years, we had some attempts to build global regional initiatives such as GD20 and OECD, et cetera, have been trying to leverage data as an economic resource. 

     But what this translated into is largely a noncritical push for freedom of data flows.  The idea of single markets is seen as digitally persistent and again, these are moves that again benefit the strongest players in these power blocs and not necessarily aimed at creating equitable uniform gains for the region as a whole.

     And then third, cross-border digital services increasingly constitute a major share of transnational value chains, but we find that our international taxation frameworks are based on physical presence and they are ineffective in curbing the profit-shifting practices if big tech corporations.

     The fact that we yet don't have a way of thinking about revenues, which is sort of how we think about tax, and how that is stemming from this enormous data power that is being captured by large technology corporations.

     One important sort of legacy law that currently exists is the W2 moratorium on digital transactions which impedes companies from effectively taxing revenues, sort of increasing taxes on big tech companies.  To look at new technologies like 3D printing which when we thought about the internet in 1998-1999 when this law came out, we were looking at images, very low tech, low data sort of flows and now we are looking at essentially all commercial activity. 

     And the fact that a moratorium extends to this is something that has really been a big sort of talking point in the international trade and taxation advocacy.

     And lastly, and this is I think the point that, you know, obviously Obasegun made earlier, it is just not enough to have access to data, you know.  The fact that not only are you having the sort of outflows of data by large technology corporations, but that nationally systems in many developing countries are still very, very weak.  They are not really up for the task of building the digital infrastructure capabilities which is a very complex resource intensive task. 

     You know, that really needs a lot of -- there are some countries that have the data, but don't have the ability yet to transition into a digital complex like large scale statistics and systems, et cetera.  How do we transition that? 

     Other countries are not even at step one.  There are countries that don't have the ability to converge different kinds of databases and look at that.  And there are others where there are no leader frameworks and incentives that allow for something like a public data infrastructure to arise that could help startups and help innovators and cooperatives and non-market initiatives like what Nicole was spoken about. 

     The fact is we really don't have the last step as well.  So when you think about it, we are looking at inadequate competition frameworks.  We're looking at inadequate global data frameworks for governance.  We are looking at taxation regimes that are inadequate.  And we are looking at lack of really national digital infrastructure and database policies.

     So what can be done?  I'm just going to quickly take another few minute and talk about the work we have been doing and what are some of the structures we forwarded as IT for Change.

     One, recognizing that the data value chain is critical to the regulation of technology itself is an important step.

     And for this, we need data to be probed as a source of value and not just in acquisitions.  Introducing data sharing as a form of connecting data disruption.  This is something that Germany is contemplating, for example.

     We could think about structural rules for big tech companies that prevent this kind of consolidation between cloud and consumer and other layers like what Amazon has been able to do. 

     And this is something that India is working on, and so is the EU recently, which brought out its strategy, that we establish ownership frameworks for nonpersonal data that actually allows sovereign interests of nations and communities to be adopted. 

     Second, we need to reduce unequal digital dependencies, and this could take on different forms depending on the national context, context-appropriate localization as needed.

     Demanding mandatory data sharing by big tech with public agencies and producers of data such as producers and workers. Preserving sovereign rights within trade agreements and the policy space to regulate data and public interest.

     Investing in data and digital infrastructure.  And really building the capacities of small economic actors to leverage digital opportunities on their own terms.  These are really important steps as well.

     At the global level, when you think about it, what we really need is global data constitutionalism which centers the human rights framework.  We need to think about how mechanisms such as the UN Binding Treaty, for example, can start looking at tech corporations and at data like a concept and object of governance and extend current regulations and frameworks and thought process to the system.

     And finally, what we do need, going go back to Nicole's fabulous presentation, we actually need new pathways, commons and cooperatives.  We need public goods and digital infrastructure and well-designed incentives for worker-produced platform enterprises. 

     And finally, we do need pathways for digitalization and capacity building for traditional small businesses to follow into the digital.  Not just about countering the presence of big tech, but when we think about de-consolidating the data value, chain it is really about expanding opportunity for the small guys as well.

     In this context, IT for Change has started a new project.  It's called unskewing the data value chain.  And over the next two years, we will be looking at these four areas and looking at what kinds of models and pathways we really need to attack this concentration and diffuse it and democratize the chains of the digital data economy.  So I'll stop here.  Thanks so much.  Back to you, Duncan.

     >> MODERATOR: That was so much to think about there, so much content. 

     Yeah, I do urge everybody to look at the work of IT for Change, it is really some fantastic stuff.  And I have really learned so much from them since we first kind of got to know each other a year or two ago.

     All right.  I am going to take the last of the presentations.  So I will be talking for, you know, 10-15 minutes at the most.  And panelists have already covered so much material.

     I'm going to just try and add to the conversation with bits that my other co-panelists haven't spoken.  I'm in agreement of so much what has been said.  I will try and cover a few different areas.

     One of the big things, so my work is really about examining the new kind of centers of power that data is bringing into our economy.  And, indeed, I think of data power as a kind of new form of power in the economy. 

     If you can think of the traditionally we had strong concepts around economic power, military power, political power, I think data power is a new form of power.  And like energy, it can shift from one to another.  You can use your data power to assert economic power or political power obviously as the platforms are now doing.  Even with the likes of Palantir and others potentially turning data power also into military power.

     When I am thinking about how to address some of these new power centers in the economy and if we accept the notion that that power is drawn at least in part from their ability to, the huge datastores that they have, then in trying to think about how we address the root cause is really about turning off that tap, that initial tap that all of the platforms do which is rapacious data gathering at all points. 

     We are very, very lucky in the EU in that we have, you know, for all its faults, the General Data Protection Regulation is still one of the best pieces of data regulation out there in the world.

     Organizations like mine certainly think it could be improved, but that is not to say it doesn't provide a really useful foundation.  And within the regulation the two principles I think that have been kind of forgotten but are actually I think critical to the future of the digital economy.  And there -- and it might sound technical, so I'll explain it a little bit. 

     So data minimization and purpose limitation.  So these re two principles that the GDPR was supposed to kind of enshrine in our European kind of data economy. 

     And data minimization is a principle that says really only the data which is absolutely required to be gathered should be collected at all.  This is powerful.  The data economy works in absolutely the opposite dynamic at the moment.

     It's a kind of data maximization.  Platforms, apps, all of the free games on your phone, every bit of the digital and data economy is trying to gather every single piece of data about you, about your interactions.  Much of it with no direct purpose today.

     But fueled by the general belief that more data is always better.  And that data ultimately does bring them benefits.  And it also brings, you know, huge risks to us as well. 

     So and I think there is a really interesting thinking by a kind of tech activist who I have a lot of time for called Errol Belcom who says that really the General Data Protection Regulation, all of its problems could be solved by calling it the Data Minimization Regulation.  If the ultimate purpose of the regulation was to minimize the data collected, that would probably be the biggest fix that we could put today, just to turn off that data tap to these big platforms.

     The second item is then purpose limitation.  The other thing that big tech does is it gathers data from one of its ends of its platforms, so we can think about the Google ecosystem, maybe you pop on to YouTube or you do a search on Google Maps or you are engaging in Google shopping or something like that. 

     And what it does is pulls that data in to it, but it doesn't just use that data for that platform or to serve you an ad in that particular world.  In hundreds of ways, it shares it not only within the hundreds of companies within kind of the Google structure, but it also then seeks to use that for purposes way beyond what we may have consented to gather.

     So I think really working at enforcing these is going to be really, really important.  And obviously that is difficult. 

     And so one of the things that I have done in my personal capacity is taken -- I'm in the process of taking YouTube to court in the UK on behalf of five million children who have accessed YouTube in the last two years.  Who we allege have had their data illegally collected by the site without proper consent, without seeking to minimize the data they collect, and without limiting the purpose for which that data is used. 

     So if our case is successful, we expect damages that YouTube will have to pay to be in the order of 2.5 to 3 billion pounds.

     But that is not the most important thing.  The most important thing that it actually changes their policy and the way that these platforms work ultimately by forcing them to kind of just gather less data at the first point. 

     I think that is the really important thing is we mustn't accept the status quo, which is that all of these platforms and these digital economy players are free to take our data at all purposes and all of the kinds of data we have.  So that is kind of my first point is that we need to start at that real root cause of the problem, which is the data gathering.

     The second thing that I want to talk about a little bit is some of the exciting developments we are seeing around collectivized responses to this kind of data concentration.  And so I'm going to talk quickly about three competing kind of ideas that are being kind of tested out in the data world.

     And so, first of all, kind of data unions.  And I think data unions are a really fascinating idea.  And it really has two flavors, kind of the data union debate. 

     First of all, it is about engaging with unions themselves.  So representing workers to expand the concept of what the union does to not only fight for workplace rights, discrimination, you know, the stuff that has been the bread and butter of unions since they started, but also start to fight for data rights for workers and make this the start of a kind of new era of demands that unions can make on behalf of workers.

     And we have seen some exciting developments in the UK where you started to see the first kind of major unions start to think about what demands look like, what kind of visibility, what access, what rights should workers have both individually, but more importantly collectively over the data. 

     On one hand there is the traditional union world bringing data into the battle between workers and businesses to ensure that workers are not, you know, dispossessed of their data.  And I think that was a really important point Deepti made earlier.

     The other thing that unions are really, really interesting and this is more nascent to think of ourselves as data producers.

     And, in fact, you going on to Facebook and commenting, liking -- I don't spend much time on Facebook, but I waste a lot of my time on Twitter doing the same thing.  We are engaged, yes, in stuff that is meaningful for us.  But we are also engaged in labor for the platforms.  We are producing value for the platforms in our engagement.

     And so this idea then if our online work is really a labor, maybe we should be grouping together and demanding some kind of rights for the work that we do for the value that we create on these platforms.

     And so I think here there are some really interesting, you know, ideas that are starting again, very, very nascent at the moment. 

     For instance, there is one attempt, you know, think the one that is always talked about is imagine what we could do if we formed a Facebook that uses union.

     So there is a huge amount of people but as individuals in an ecosystem with more than a billion users, individuals could never really have a huge impact on the operations of the platform.  What about if we coalesced in unions of hundreds of thousands, of millions?  Of tens of millions?  And started to make demands of the platform and in the same way that, you know, traditional labor unions that wealth held their labor. 

     What about if we were a union of tens of millions, hundreds of millions in a real ideal world and we all withheld our labor in the sense of going onto the platform and engaging it with for a month, you know?  No ad revenue.  This is again the power that we actually have as users.  And the difficulty there is really mobilizing as a collective.

     The digital world is replicating many of the same challenges that we faced in the physical world.  With additional challenges.  Obviously, scale. No physical union mobilization is talking about mobilizing in the tens or hundreds of millions, at least not -- at least that's very, very challenging. 

     And also the kind of the disparate nature of each other.  We don't, once, recognize ourselves necessarily as digital workers.  And second, we don't necessarily have the solidarity that we have in physical workplaces with other data laborers, if you want.  I think both of those are really, really exciting options that are kind of just at the cusp of being explored.

     The second area I want to talk about is data trusts.  And anybody involved in kind of data governance work in the last couple of years, at least on the slightly alternative side, data trust has been talked about as one of the really exciting ways of being able to share data beyond the confines of single companies whilst retaining some of that safety and some of those protections.

     Now where I think it is a hugely promising kind of idea, this idea of enveloping data in the kind of a trust model where you have beneficiaries and that data can then only be used for the benefit of these beneficiaries. 

     So you create a kind of positive model for the use of this data.  However, the challenges, and I know this partly because I spent, you know, kind of six months trying to set one up in the UK, is that they are hugely expensive to set up.  Trust law is complicated.

     Trust law mainly evolved or very much involved in the U.S. and UK legal system to enable the wealth to hide assets beyond the reach of the State. 

     So we should have a certain amount of skepticism that a system that has evolved to ultimately keep things protected from visibility and democratic accountability that we can somehow turn that into a positive structure.

     I think the data trust model is one that I'm following closely, but for the moment I haven't seen any uses beyond like big -- I haven't seen the community application or real applications that would work for the social economy.  It costs hundreds of thousands of pounds to set that up.  That already puts it out of reach of the real grassroots projects we would like to see more of.

     The last kind of model I will talk about quickly is the kind of data co-ops.  So just as Nicole is talking about, the platform co-ops and actually putting the cooperative model around the cooperative model.  Takes away the negative issues that the normal platform model kind of has.

     It is very much the same with the data.  So rather than, again, having a data that is owned by a company externally, what about if we all collectively owned this data.  And not only that, because the cooperative model is more than just about ownership.

     It is also about that ongoing notion of management and being in control, which is so empowering and really, really important for the model.  So the exciting example in the data co-ops world that is mentioned is a Swiss data co-ops called MyData. 

     And they pull sensitive data from members.  They take medical history data from the members.  Members voluntarily share their medical history with the co-ops and the MyData co-ops goes out and actively engages with medical researchers around the world to say hey, I have got this really, really useful dataset.  If you commit to promising to publish the results of the survey and commit to doing research on a disease that is maybe less well known or less clarity for the existing pharmaceutical industry.

     It is giving holders of data, valuable data a real say in how that data is used.  And again, what is also really encouraging about the MyData co-ops model, it isn't monetary.  People aren't sharing for the monetary gain as the data as labor or data as value initiatives have.  This is about using your data to really generate more public good. 

     And that is I think one of the reasons why again it is so exciting and why co-ops and other alternative models can preface and data is so, so important. 

     I have already gone over time and want to ensure there is time for questions.  I will finish with reinforcing the point that some of the other panelists have said that de-concentration of data actually involves de-concentrating more than just data. 

     And we need to think about the infrastructure.  I think Deepti made all of these points very, very well.  If everybody is storing in one or two services, that is still not going to be a de-concentrated model.  We need to think about cloud and AI.  We need to think about internet connectivity and things like that.  All very, very important.

     The last thing that I would say just, which is another area I'm starting to work on now and hopefully we can maybe take into the discussion a little bit, is I find there are areas where the platform co-ops model is very challenging. 

     In the world of Uber, for a co-ops to compete against one of the most aggressive, well-capitalized companies in the world like Uber is very challenging.  I'm interested in where the role of the public sector is and is there a role for like public platforms because scale is really important for some of the platforms. 

     Is there a role for the public sector in creating some of these neutral marketplaces where people can then engage on fair terms and work and so on.

     So I'm going to stop there.  Thank you all so much for taking the time to listen. 

     So I have -- I have a couple of questions in the Q&A.  Please continue to pose questions.  Nicole, I see your hand.  Do you want a response?

     >> NICOLE ALIX: If you have Q&A, I think it would be an opportunity for people who don't have any possibility to speak to, you know, to intervene now. 

     But I just want to react, Duncan, about what you said because before you talked about the idea of data co-ops. 

     I wrote in the chat that we, this is on data cooperatives and with practitioners including companies like cooperative banks and mutual insurance because you don't know what to do differently than the capitalist companies.

     And but they are not able to create a data highway, how could I say, an area of trust.  If there is only one company promoting the idea of data co-ops, it doesn't work.  And you need to find a sort of neutral group to go further. 

     So we launch at the end of November with experts.  And I put in the chat at least one reference.  I'm sorry because it is -- I shouldn't be sorry -- it is in French, it is in French because we have the model is now in charge of open science within the big public institution here, resort public institution in France. 

     And the global idea is that there is no -- there is no really personal data.  We only have collection data and we should promote this idea.

     What we are not completely clear with is the idea for monetizing the data in cooperatives because how could we promote the idea of cooperatives without the idea of monetization. 

     And so my proposal, but sometimes I see too large and too pushy, and I think it would be really interesting to have an international or at least a European connection on data co-ops and this is really a proposal.

     >> MODERATOR: I think that would be great.  And I think really where a lot of the ideas are is we need to be sharing.

     Nobody can do all of this on their own.  And so absolutely building these international networks is really important.  I would love to learn more and see how we could be part of it.

     So in the remaining 15 minutes, I will try and take some questions.  So there have been -- there are two questions in the Q&A., which will I try and translate. 

     I'm going to take the second kind of question first.  And I will kind of distill the paragraph there.

     And I think what is really the key question is there is that we talked a lot about needing to create a kind of alternative infrastructure, one that says we can do all of this in a way that is completely parallel with the kind of existing platform economy. 

     And I think the question brings really interesting ideas which is should we not also be thinking and are there always possibly ways in which we can really start to constrain the activities of the platform, the major platforms so that in fact we guide them into doing the public good that we really believe they should be doing?

     So, yes, I was wondering if anybody wants to try and take that.  You know, how much can we really bring the existing platforms with us?  Are we not all on the same team as some of the comments.  I don't know if anybody wants to take that.

     >> OBASEGUN AYODELE: I think so.  I just joined, the open access movement is kind of in a way trying to solve that.  It is to a way from --

     >> MODERATOR: We can't hear you.  Oh, I think we might have lost Obasegun there.

     But Deepti or Nicole, do you want to try and come in on how we tackle big tech not to exclude them but more to bring them in?

     >> NICOLE ALIX: It is impossible to bring them in.


     >> NICOLE ALIX: It is impossible to bring them in, but we need more regulation.  This is the first part. 

     What we tried to do as far as because what is very complicated is to convince our public partners that the alternative can really be operational because to say well, it is too small, I need to have the same solution everywhere so it is complicated.

     And now and they don't favor any regulation because there is no alternative.  There is no global alternative.  And as well as we just have to promote global solutions and there is no alternative. 

     So I think we have to promote a sort of education in order for people to understand what they are doing, as our colleague from Africa said. 

     I don't know whether he is back.  To work with people, that they are concerned about that.  And the second thing we tried to do is working with some local authorities which put money within the alternatives to promote not only to small and local solutions but territorial solutions.  This is what I presented, platform co-ops not only as startups or cooperatives but as solutions for those working within the local authorities. 

     We need even for the models to be able to have sustainable business model because they are -- their business model is not sustainable because the other, the capitalist platforms are sustainable because they are selling data and working with the data.

     And it is more, or it is more profitable for them than selling goods and services.  This is one part.

     >> MODERATOR: Thank you, Nicole.  And instead the question has come in and been a misinterpretation of mine. 

     Shows how much bias you bring when you are reading text.  He was talking less about constraining big tech more than about, you know, freeing them up with kind of clever market incentives like carbon taxes and credits.  Our apologies for misreading the question there. 

     Obasegun, I see you joined us again.  You were just talking before you dropped.  Do you want to come back in, or?  You are still on mute.  Deepti, do you want to take any of this question or otherwise we can --

     >> DEEPTI BHARTHUR: So the question about like so am I supposed to answer your question for the clarification?  I just wanted to --

     >> MODERATOR: You can either go really -- I think just what do you think?  Where is our role and the role of established big tech?  What are we supposed to do with them in the world that we would like to see?

     >> DEEPTI BHARTHUR: Sure.  I think the problem is not so much about constraining or freeing in that sense. 

     What we are witnessing is the costs of having had a very free rein of technology companies.  When they came in, nobody knew what to do with them.  They were garage enterprises coming out of Silicon Valley and everybody thought they were benign little entities providing free maps and free search and free everything.  Of course, there was no reason to think about that.

     As we have seen them progress, and I think I share concerns that Nicole mentioned about sustainability, none of the companies except one or two have actually made profits to now.  They are very overvalued and overinflated and constantly move and rapidly growing.  And when there is blowback, it is not they who suffer.  This is an unsustainable model that we look up to as saviors of the world. 

     Not a problem of reining them in now.  It's really the fact that we should have reined them in probably 10 years ago.  With adequate -- I'm not necessarily making a case for saying that we must strangle innovation and tech must die and go back to the pre-digital lives. 

     I certainly think that all players and market interests have a role to play in sort of the company.  But what I would argue for is the fact that somewhere the government missteps that have happened because of our inability to see what we know now.  And the fact that data became an important resource, and we need to direct because our markets are headed into dangerous distorted territories otherwise.

     They are as sustainable or big tech as they are nor the other guys otherwise, we are staring at a second dot-com bubble soon.  That is very important.

     And to answer whether we can work together.  I think we can as long as I think we have regulation that is really thoughtful.  A lot of it sometimes seems to be like throttling and coming in through the harsh standard consequences.  There is an accident, let's ban Uber or a problem, throw the drivers out of the system.  We need to have forward-looking policy.

     I think one important case is mandatory data sharing between platforms and public agencies, for example.  Nothing stops Uber from sharing data with city to plan city traffic management better, et cetera, et cetera.  I will stop now and let Obasegun come back if he had something to say.

     >> OBASEGUN AYODELE:  Apologies for that.  I just had an outage.  I was trying to explain -- can you hear me, everyone?

     >> MODERATOR: Yes, we can hear you.

     >> OBASEGUN AYODELE: So how we try to look at this is what looks to almost be working.  And we try to work backwards and find out what exact element in that thing makes it work.

     And if you look at the open access movement, which Nicole mentioned, of the inclusive open science movement, you realize there has been a lot of data sharing and advancement and innovation and a lot of collaboration. 

     Like in Africa it really helped for producing low cost regions or for people like a way we can facilitate an open source microscope that is high end and costs so much money, we will take the open source and produce something that is accessible by low income communities.

     So the open access movement kind of is almost working.  So what we can do is we mirror the successes of the platform, of the movement and see if we can draft policy suggestions that governments can take up.

     So like UNESCO tried to do at the time to drop the policy for the open science movement.  So we can also look at opportunities like where government can say okay, this works, and get some growth and progress and how can we draft local laws.  Things like that. 

     I think we should look at this more from what from the open access perspective and see how we can work backwards to find a solution to this.

     >> MODERATOR: Great.  Thank you so much for joining us again.  And thanks, that is really great. 

     We will try and address the other question from the chat, which is an interesting one, in fact one I was just talking about yesterday.

     And it comes from Win, who talks about the potential of there being no farmers kind of by 2030, sometime in the future.

     And how do we go about resisting, what are some of the solutions, some -- I mean I will put a bit of context only because I was talking about it yesterday on the subject. 

     Agriculture is going through a massive revolution.  Who does the farming and how food is distributed and so on.  And a lot of it is being driven by data, and the same kind of consolidation and concentration narrative we see in so many other sectors. 

     And this is hugely problematic because across the world, you know, the -- you know, the huge amount of farming is still done by very, very small-scale farmers who partly subsist by selling through local marketplaces.  And yet we what we are seeing technology do is of four different challenges. 

     One, technology is being used to engage in a new generation of bio-piracy where local crops can be kind of constructed and impatented.  We are seeing real consolidation of the business so everything from seeds to equipment, again all around being able to produce better data. 

     We are seeing a move of the big online marketplaces.  So Alibaba now has invested in farms, you know.  Producing milk in New Zealand to ship into southeast Asian markets.  So the big players are coming in. 

     And ultimately it poses, you know, a serious challenge for kind of small-scale farmers in the future who may not be able to rely on, you know, tech and so on.

     So just that bit of context in place.  I don't know if any of the panelists want to talk about what we can do to make sure -- and again, Obasegun already provided some really interesting really specific kind of things we can do. 

     If you want to come in again and talk about what can we do to really help farmers access the data so that they can continue to do what we really need them to do, which is obviously continue to, one, have a livelihood, and two, grow the food that we need.

     >> OBASEGUN AYODELE: Okay.  Should I jump in?

     >> MODERATOR: If you want to, yes.

     >> OBASEGUN AYODELE: Yes.  So I think in addition to what I already said with the panel, I think the thing for us was some creative platform where we could engage with the panel where we could understand what are their needs and try and see how we can market those needs to data that is available for business.

     So I think another thing which sometimes is difficult for people to do is we have so much data and just coming out of their existing infrastructure and it is sometimes maybe because it is not on the long-term business case, you know, and plans.  They sometimes meet that part where they have to map what data is useful for the communities.

     What we tried to do is do like a town hall and bring the data cooperations, you know, bring the public sector, the government and the agencies and all of the different people together in one room where you can say this is our problem. 

     And then it is easy for cooperations and these, quote, data brokers to access.  In addition towards what I said earlier, this would be also a very good opportunity, you know, to kickstart some collaboration with farmers like that.

     >> MODERATOR: Brilliant, thanks.  I notice -- thank you very much.  That was a really useful addition. 

     And obviously we need to bring the constituencies together.  That was a really good point to end on. 

     We reached the end of our session.  I would like to thank the three speakers who joined me today, Nicole and Deepti and Obasegun.  I think it was a really interesting discussion which not only showed that there are exciting things going on on the ground, and in many different continents and across many different sectors of the economy.  You know, it is really great to hear that people are already doing it.

     And also there are big challenges that remain.  And so we absolutely need to keep working so that we can distribute the benefit of data much, much more broadly into the communities who really need it. 

     So I would like to close and say thank you very much for joining us for this hour and a half.  And I hope to learn more from all of you in the future.  All right.  I hope you have a really lovely day. 


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