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Posts Tagged ‘responsible data’

Development, humanitarian and human rights organizations increasingly collect and use digital data at the various stages of their programming. This type of data has the potential to yield great benefit, but it can also increase individual and community exposure to harm and privacy risks. How can we as a sector better balance data collection and open data sharing with privacy and security, especially when it involves the most vulnerable?

A number of donors, humanitarian and development organizations (including Oxfam, CRS, UN bodies and others) have developed or are in the process of developing guidelines to help them to be more responsible about collection, use, sharing and retention of data from those who participate in their programs.

I’m part of a team (including mStar, Sonjara, Georgetown University, the USAID Global Development Lab, and an advisory committee that includes several shining stars from the ‘responsible data’ movement) that is conducting research on existing practices, policies, systems, and legal frameworks through which international development data is collected, used, shared, and released. Based on this research, we’ll develop ‘responsible data’ practice guidelines for USAID that aim to help:

  • Mitigate privacy and security risks for beneficiaries and others
  • Improve performance and development outcomes through use of data
  • Promote transparency, accountability and public good through open data

The plan is to develop draft guidelines and then to test their application on real programs.

We are looking for digital development projects to assess how our draft guidelines would work in real world settings. Once the projects are selected, members of the research team will visit them to better understand “on-the-ground” contexts and project needs. We’ll apply draft practice guidelines to each case with the goal of identifying what parts of the guidelines are useful/ applicable, and where the gaps are in the guidelines. We’ll also capture feedback from the project management team and partners on implications for project costs and timelines, and we’ll document existing digital data-related good practices and lessons. These findings will further refine USAID’s Responsible Data Practice guidelines.

What types of projects are we looking for?

  • Ongoing or recently concluded projects that are using digital technologies to collect, store, analyze, manage, use and share individuals’ data.
  • Cases where data collected is sensitive or may put project participants at risk.
  • The project should have informal or formal processes for privacy/security risk assessment and mitigation especially with respect to field implementation of digital technologies (listed above) as part of their program. These may be implicit or explicit (i.e. documented or written). They potentially include formal review processes conducted by ethics review boards or institutional review boards (IRBs) for projects.
  • All sectors of international development and all geographies are welcome to submit case studies. We are looking for diversity in context and programming.
  • We prefer case studies from USAID-funded projects but are open to receiving case studies from other donor-supported projects.

If you have a project or an activity that falls into the above criteria, please let us know here. We welcome multiple submissions from one organization; just reuse the form for each proposed case study.

Please submit your projects by February 15, 2017.

And please share this call with others who may be interested in contributing case studies.

Click here to submit your case study.

Also feel free to get in touch with me if you have questions about the project or the call!

 

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Crowdsourcing our Responsible Data questions, challenges and lessons. (Photo courtesy of Amy O'Donnell).

Crowdsourcing our Responsible Data questions, challenges and lessons. (Photo by Amy O’Donnell).

At Catholic Relief Services’ ICT4D Conference in May 2016, I worked with Amy O’Donnell  (Oxfam GB) and Paul Perrin (CRS) to facilitate a participatory session that explored notions of Digital Privacy, Security and Safety. We had a full room, with a widely varied set of experiences and expertise.

The session kicked off with stories of privacy and security breaches. One person told of having personal data stolen when a federal government clearance database was compromised. We also shared how a researcher in Denmark scraped very personal data from the OK Cupid online dating site and opened it up to the public.

A comparison was made between the OK Cupid data situation and the work that we do as development professionals. When we collect very personal information from program participants, they may not expect that their household level income, health data or personal habits would be ‘opened’ at some point.

Our first task was to explore and compare the meaning of the terms: Privacy, Security and Safety as they relate to “digital” and “development.”

What do we mean by privacy?

The “privacy” group talked quite a bit about contextuality of data ownership. They noted that there are aspects of privacy that cut across different groups of people in different societies, and that some aspects of privacy may be culturally specific. Privacy is concerned with ownership of data and protection of one’s information, they said. It’s about who owns data and who collects and protects it and notions of to whom it belongs. Private information is that which may be known by some but not by all. Privacy is a temporal notion — private information should be protected indefinitely over time. In addition, privacy is constantly changing. Because we are using data on our mobile phones, said one person, “Safaricom knows we are all in this same space, but we don’t know that they know.”

Another said that in today’s world, “You assume others can’t know something about you, but things are actually known about you that you don’t even know that others can know. There are some facts about you that you don’t think anyone should know or be able to know, but they do.” The group mentioned website terms and conditions, corporate ownership of personal data and a lack of control of privacy now. Some felt that we are unable to maintain our privacy today, whereas others felt that one could opt out of social media and other technologies to remain in control of one’s own privacy. The group noted that “privacy is about the appropriate use of data for its intended purpose. If that purpose shifts and I haven’t consented, then it’s a violation of privacy.”

What do we mean by security?

The Security group considered security to relate to an individual’s information. “It’s your information, and security of it means that what you’re doing is protected, confidential, and access is only for authorized users.” Security was also related to the location of where a person’s information is hosted and the legal parameters. Other aspects were related to “a barrier – an anti-virus program or some kind of encryption software, something that protects you from harm…. It’s about setting roles and permissions on software and installing firewalls, role-based permissions for accessing data, and cloud security of individuals’ data.” A broader aspect of security was linked to the effects of hacking that lead to offline vulnerability, to a lack of emotional security or feeling intimidated in an online space. Lastly, the group noted that “we, not the systems, are the weakest link in security – what we click on, what we view, what we’ve done. We are our own worst enemies in terms of keeping ourselves and our data secure.”

What do we mean by safety?

The Safety group noted that it’s difficult to know the difference between safety and security. “Safety evokes something highly personal. Like privacy… it’s related to being free from harm personally, physically and emotionally.” The group raised examples of protecting children from harmful online content or from people seeking to harm vulnerable users of online tools. The aspect of keeping your online financial information safe, and feeling confident that a service was ‘safe’ to use was also raised. Safety was considered to be linked to the concept of risk. “Safety engenders a level of trust, which is at the heart of safety online,” said one person.

In the context of data collection for communities we work with – safety was connected to data minimization concepts and linked with vulnerability, and a compounded vulnerability when it comes to online risk and safety. “If one person’s data is not safely maintained it puts others at risk,” noted the group. “And pieces of information that are innocuous on their own may become harmful when combined.” Lastly, the notion of safety as related to offline risk or risk to an individual due to a specific online behavior or data breach was raised.

It was noted that in all of these terms: privacy, security and safety, there is an element of power, and that in this type of work, a power relations analysis is critical.

The Digital Data Life Cycle

After unpacking the above terms, Amy took the group through an analysis of the data life cycle (courtesy of the Engine Room’s Responsible Data website) in order to highlight the different moments where the three concepts (privacy, security and safety) come into play.

Screen Shot 2016-05-25 at 6.51.50 AM

  • Plan/Design
  • Collect/Find/Acquire
  • Store
  • Transmit
  • Access
  • Share
  • Analyze/use
  • Retention
  • Disposal
  • Afterlife

Participants added additional stages in the data life cycle that they passed through in their work (coordinate, monitor the process, monitor compliance with data privacy and security policies). We placed the points of the data life cycle on the wall, and invited participants to:

  • Place a pink sticky note under the stage in the data life cycle that resonates or interests them most and think about why.
  • Place a green sticky note under the stage that is the most challenging or troublesome for them or their organizations and think about why.
  • Place a blue sticky note under the stage where they have the most experience, and to share a particular experience or tip that might help others to better manage their data life cycle in a private, secure and safe way.

Challenges, concerns and lessons

Design as well as policy are important!

  • Design drives everScreen Shot 2016-05-25 at 7.21.07 AMything else. We often start from the point of collection when really it’s at the design stage when we should think about the burden of data collection and define what’s the minimum we can ask of people? How we design – even how we get consent – can inform how the whole process happens.
  • When we get part-way through the data life cycle, we often wish we’d have thought of the whole cycle at the beginning, during the design phase.
  • In addition to good design, coordination of data collection needs to be thought about early in the process so that duplication can be reduced. This can also reduce fatigue for people who are asked over and over for their data.
  • Informed consent is such a critical issue that needs to be linked with the entire process of design for the whole data life cycle. How do you explain to people that you will be giving their data away, anonymizing, separating out, encrypting? There are often flow down clauses in some contracts that shifts responsibilities for data protection and security and it’s not always clear who is responsible for those data processes? How can you be sure that they are doing it properly and in a painstaking way?
  • Anonymization is also an issue. It’s hard to know to what level to anonymize things like call data records — to the individual? Township? District Level? And for how long will anonymization actually hold up?
  • The lack of good design and policy contributes to overlapping efforts and poor coordination of data collection efforts across agencies. We often collect too much data in poorly designed databases.
  • Policy is not enough – we need to do a much better job of monitoring compliance with policy.
  • Institutional Review Boards (IRBs) and compliance aspects need to be updated to the new digital data reality. At the same time, sometimes IRBs are not the right instrument for what we are aiming to achieve.

Data collection needs more attention.

  • Data collection is the easy part – where institutions struggle is with analyzing and doing something with the data we collect.
  • Organizations often don’t have a well-structured or systematic process for data collection.
  • We need to be clearer about what type of information we are collecting and why.
  • We need to update our data protection policy.

Reasons for data sharing are not always clear.

  • How can share data securely and efficiently without building duplicative systems? We should be thinking more during the design and collection phase about whether the data is going to be interoperable and who needs to access it.
  • How can we get the right balance in terms of data sharing? Some donors really push for information that can put people in real danger – like details of people who have participated in particular programs that would put them at risk with their home governments. Organizations really need to push back against this. It’s an education thing with donors. Middle management and intermediaries are often the ones that push for this type of data because they don’t really have a handle on the risk it represents. They are the weak points because of the demands they are putting on people. This is a challenge for open data policies – leaving it open to people leaves it to doing the laziest job possible of thinking about the potential risks for that data.
  • There are legal aspects of sharing too – such as the USAID open data policy where those collecting data have to share with the government. But we don’t have a clear understanding of what the international laws are about data sharing.
  • There are so many pressures to share data but they are not all fully thought through!

Data analysis and use of data are key weak spots for organizations.

  • We are just beginning to think through capturing lots of data.
  • Data is collected but not always used. Too often it’s extractive data collection. We don’t have the feedback loops in place, and when there are feedback loops we often don’t use the the feedback to make changes.
  • We forget often to go back to the people who have provided us with data to share back with them. It’s not often that we hold a consultation with the community to really involve them in how the data can be used.

Secure storage is a challenge.

  • We have hundreds of databases across the agency in various formats, hard drives and states of security, privacy and safety. Are we able to keep these secure?
  • We need to think more carefully about where we hold our data and who has access to it. Sometimes our data is held by external consultants. How should we be addressing that?

Disposing of data properly in a global context is hard!

  • Screen Shot 2016-05-25 at 7.17.58 AMIt’s difficult to dispose of data when there are multiple versions of it and a data footprint.
  • Disposal is an issue. We’re doing a lot of server upgrades and many of these are remote locations. How do we ensure that the right disposal process is going on globally, short of physically seeing that hard drives are smashed up!
  • We need to do a better job of disposal on personal laptops. I’ve done a lot of data collection on my personal laptop – no one has ever followed up to see if I’ve deleted it. How are we handling data handover? How do you really dispose of data?
  • Our organization hasn’t even thought about this yet!

Tips and recommendations from participants

  • Organizations should be using different tools. They should be using Pretty Good Privacy techniques rather than relying on free or commercial tools like Google or Skype.
  • People can be your weakest link if they are not aware or they don’t care about privacy and security. We send an email out to all staff on a weekly basis that talks about taking adequate measures. We share tips and stories. That helps to keep privacy and security front and center.
  • Even if you have a policy the hard part is enforcement, accountability, and policy reform. If our organizations are not doing direct policy around the formation of best practices in this area, then it’s on us to be sure we understand what is best practice, and to advocate for that. Let’s do what we can before the policy catches up.
  • The Responsible Data Forum and Tactical Tech have a great set of resources.
  • Oxfam has a Responsible Data Policy and Girl Effect have developed a Girls’ Digital Privacy, Security and Safety Toolkit that can also offer some guidance.

In conclusion, participants agreed that development agencies and NGOs need to take privacy, security and safety seriously. They can no longer afford to implement security at a lower level than corporations. “Times are changing and hackers are no longer just interested in financial information. People’s data is very valuable. We need to change and take security as seriously as corporates do!” as one person said.

 

 

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At our April 5th Salon in Washington, DC we had the opportunity to take a closer look at open data and privacy and discuss the intersection of the two in the framework of ‘responsible data’. Our lead discussants were Amy O’Donnell, Oxfam GB; Rob Baker, World Bank; Sean McDonald, FrontlineSMS. I had the pleasure of guest moderating.

What is Responsible Data?

We started out by defining ‘responsible data‘ and some of the challenges when thinking about open data in a framework of responsible data.

The Engine Room defines ‘responsible data’ as

the duty to ensure people’s rights to consent, privacy, security and ownership around the information processes of collection, analysis, storage, presentation and reuse of data, while respecting the values of transparency and openness.

Responsible Data can be like walking a tightrope, noted our first discussant, and you need to find the right balance between opening data and sharing it, all the while being ethical and responsible. “Data is inherently related to power – it can create power, redistribute it, make the powerful more powerful or further marginalize the marginalized. Getting the right balance involves asking some key questions throughout the data lifecycle from design of the data gathering all the way through to disposal of the data.

How can organizations be more responsible?

If an organization wants to be responsible about data throughout the data life cycle, some questions to ask include:

  • In whose interest is it to collect the data? Is it extractive or empowering? Is there informed consent?
  • What and how much do you really need to know? Is the burden of collecting and the liability of storing the data worth it when balanced with the data’s ability to represent people and allow them to be counted and served? Do we know what we’ll actually be doing with the data?
  • How will the data be collected and treated? What are the new opportunities and risks of collecting and storing and using it?
  • Why are you collecting it in the first place? What will it be used for? Will it be shared or opened? Is there a data sharing MOU and has the right kind of consent been secured? Who are we opening the data for and who will be able to access and use it?
  • What is the sensitivity of the data and what needs to be stripped out in order to protect those who provided the data?

Oxfam has developed a data deposit framework to help assess the above questions and make decisions about when and whether data can be open or shared.

(The Engine Room’s Responsible Development Data handbook offers additional guidelines and things to consider)

(See: https://wiki.responsibledata.io/Data_in_the_project_lifecycle for more about the data lifecycle)

Is ‘responsible open data’ an oxymoron?

Responsible Data policies and practices don’t work against open data, our discussant noted. Responsible Data is about developing a framework so that data can be opened and used safely. It’s about respecting the time and privacy of those who have provided us with data and reducing the risk of that data being hacked. As more data is collected digitally and donors are beginning to require organizations to hand over data that has been collected with their funding, it’s critical to have practical resources and help staff to be more responsible about data.

Some disagreed that consent could be truly informed and that open data could ever be responsible since once data is open, all control over the data is lost. “If you can’t control the way the data is used, you can’t have informed people. It’s like saying ‘you gave us permission to open your data, so if something bad happens to you, oh well….” Informed consent is also difficult nowadays because data sets are being used together and in ways that were not possible when informed consent was initially obtained.

Others noted that standard informed consent practices are unhelpful, as people don’t understand what might be done with their data, especially when they have low data literacy. Involving local communities and individuals in defining what data they would like to have and use could make the process more manageable and useful for those whose data we are collecting, using and storing, they suggested.

One person said that if consent to open data was not secured initially; the data cannot be opened, say, 10 years later. Another felt that it was one thing to open data for a purpose and something entirely different to say “we’re going to open your data so people can do fun things with it, to play around with it.”

But just what data are we talking about?

USAID was questioned for requiring grantees to share data sets and for leaning towards de-identification rather than raising the standard to data anonymity. One person noted that at one point the agency had proposed a 22-step process for releasing data and even that was insufficient for protecting program participants in a risky geography because “it’s very easy to figure out who in a small community recently received 8 camels.” For this reason, exclusions are an important part of open data processes, he said.

It’s not black or white, said another. Responsible open data is possible, but openness happens along a spectrum. You have financial data on the one end, which should be very open as the public has a right to know how its tax dollars are being spent. Human subjects research is on the other end, and it should not be totally open. (Author’s note: The Open Knowledge Foundation definition of open data says: “A key point is that when opening up data, the focus is on non-personal data, that is, data which does not contain information about specific individuals.” The distinction between personal data, such as that in household level surveys, and financial data on agency or government activities seems to be blurred or blurring in current debates around open data and privacy.) “Open data will blow up in your face if it’s not done responsibly,” he noted. “But some of the open data published via IATI (the International Aid Transparency Initiative) has led to change.”

A participant followed this comment up by sharing information from a research project conducted on stakeholders’ use of IATI data in 3 countries. When people knew that the open data sets existed they were very excited, she said. “These are countries where there is no Freedom of Information Act (FOIA), and where people cannot access data because no one will give it to them. They trusted the US Government’s data more than their own government data, and there was a huge demand for IATI data. People were very interested in who was getting what funding. They wanted information for planning, coordination, line ministries and other logistical purposes. So let’s not underestimate open data. If having open data sets means that governments, health agencies or humanitarian organizations can do a better job of serving people, that may make for a different kind of analysis or decision.”

‘Open by default’ or ‘open by demand’?

Though there are plenty of good intentions and rationales for open data, said one discussant, ‘open by default’ is a mistake. We may have quick wins with a reduction in duplicity of data collection, but our experiences thus far do not merit ‘open by default’. We have not earned it. Instead, he felt that ‘open by demand’ is a better idea. “We can put out a public list of the data that’s available and see what demand for data comes in. If we are proactive on what is available and what can be made available, and we monitor requests, we can avoid putting out information that no one is interested in. This would lower the overhead on what we are releasing. It would also allow us to have a conversation about who needs this data and for what.”

One participant agreed, positing that often the only reason that we collect data is to provide proof and evidence that we’re doing our job, spending the money given to us, and tracking back. “We tend to think that the only way to provide this evidence is to collect data: do a survey, talk to people, look at website usage. But is anyone actually using this data, this evidence to make decisions?”

Is the open data honeymoon over?

“We need to do a better job of understanding the impact at a wider level,” said another participant, “and I think it’s pretty light. Talking about open data is too general. We need to be more service oriented and problem driven. The conversation is very different when you are using data to solve a particular problem and you can focus on something tangible like service delivery or efficiency. Open data is expensive and not sustainable in the current setup. We need to figure this out.”

Another person shared results from an informal study on the use of open data portals around the world. He found around 2,500 open data portals, and only 3.8% of them use https (the secure version of http). Most have very few visitors, possibly due to poor Internet access in the countries whose open data they are serving up, he said. Several exist in countries with a poor Freedom House ranking and/or in countries at the bottom end of the World Bank’s Digital Dividends report. “In other words, the portals have been built for people who can’t even use them. How responsible is this?” he asked, “And what is the purpose of putting all that data out there if people don’t have the means to access it and we continue to launch more and more portals? Where’s all this going?”

Are we conflating legal terms?

Legal frameworks around data ownership were debated. Some said that the data belonged to the person or agency that collected it or paid for the cost of collecting in terms of copyright and IP. Others said that the data belonged to the individual who provided it. (Author’s note: Participants may have been referring to different categories of data, eg., financial data from government vs human subjects data.) The question was raised of whether informed consent for open data in the humanitarian space is basically a ‘contract of adhesion’ (a term for a legally binding agreement between two parties wherein one side has all the bargaining power and uses it to its advantage). Asking a person to hand over data in an emergency situation in order to enroll in a humanitarian aid program is akin to holding a gun to a person’s head in order to get them to sign a contract, said one person.

There’s a world of difference between ‘published data’ and ‘openly licensed data,’ commented our third discussant. “An open license is a complete lack of control, and you can’t be responsible with something you can’t control. There are ways to be responsible about the way you open something, but once it’s open, your responsibility has left the port.” ‘Use-based licensing’ is something else, and most IP is governed by how it’s used. For example, educational institutions get free access to data because they are educational institutions. Others pay and this subsidized their use of this data, he explained.

One person suggested that we could move from the idea of ‘open data’ to sub-categories related to how accessible the data would be and to whom and for what purposes. “We could think about categories like: completely open, licensed, for a fee, free, closed except for specific uses, etc.; and we could also specify for whom, whose data and for what purposes. If we use the term ‘accessible’ rather than ‘open’ perhaps we can attach some restrictions to it,” she said.

Is data an asset or a liability?

Our current framing is wrong, said one discussant. We should think of data as a toxic asset since as soon as it’s in our books and systems, it creates proactive costs and proactive risks. Threat modeling is a good approach, he noted. Data can cause a lot of harm to an organization – it’s a liability, and if it’s not used or stored according to local laws, an agency could be sued. “We’re far under the bar. We are not compliant with ‘safe harbor’ or ECOWAS regulations. There are libel questions and property laws that our sector is ignorant of. Our good intentions mislead us in terms of how we are doing things. There is plenty of room to build good practice here, he noted, for example through Civic Trusts. Another participant noted that insurance underwriters are already moving into this field, meaning that they see growing liability in this space.

How can we better engage communities and the grassroots?

Some participants shared examples of how they and their organizations have worked closely at the grassroots level to engage people and communities in protecting their own privacy and using open data for their own purposes. Threat modeling is an approach that helps improve data privacy and security, said one. “When we do threat modeling, we treat the data that we plan to collect as a potential asset. At each step of collection, storage, sharing process – we ask, ‘how will we protect those assets? What happens if we don’t share that data? If we don’t collect it? If we don’t delete it?’”

In one case, she worked with very vulnerable women working on human rights issues and together the group put together an action plan to protect its data from adversaries. The threats that they had predicted actually happened and the plan was put into action. Threat modeling also helps to “weed the garden once you plant it,” she said, meaning that it helps organizations and individuals keep an eye on their data, think about when to delete data, pay attention to what happens after data’s opened and dedicate some time for maintenance rather than putting all their attention on releasing and opening data.

More funding needs to be made available for data literacy for those whose data has been collected and/or opened. We need to help people think about what data is of use to them also. One person recalled hearing people involved in the creation of the Kenya Open Government Data portal say that the entire process was a waste of time because of low levels of use of any of the data. There are examples, however, of people using open data and verifying it at community level. For example, high school students in one instance found the data on all the so-called grocery stores in their community and went one-by-one checking into them, and identifying that some of these were actually liquor stores selling potato chips, not actual grocery stores. Having this information and engaging with it can be powerful for local communities’ advocacy work.

Are we the failure here? What are we going to do about it?

One discussant felt that ‘data’ and ‘information’ are often and easily conflated. “Data alone is not power. Information is data that is contextualized into something that is useful.” This brings into question the value of having so many data portals, and so much risk, when so little is being done to turn data into information that is useful to the people our sector says it wants to support and empower.

He gave the example of the Weather Channel, a business built around open data sets that are packaged and broadcast, which just got purchased for $2 billion. Channels like radio that would have provided information to the poor were not purchased, only the web assets, meaning that those who benefit are not the disenfranchised. “Our organizations are actually just like the Weather Channel – we are intermediaries who are interested in taking and using open data for public good.”

As intermediaries, we can add value in the dissemination of this open data, he said. If we have the skills, the intention and the knowledge to use it responsibly, we have a huge opportunity here. “However our enlightened intent has not yet turned this data into information and knowledge that communities can use to improve their lives, so are we the failure here? And if so, what are we doing about it? We could immediately begin engaging communities and seeing what is useful to them.” (See this article for more discussion on how ‘open’ may disenfranchise the poor.)

Where to from here?

Some points raised that merit further discussion and attention include:

  • There is little demand or use of open data (such as government data and finances) and preparing and maintaining data sets is costly – ‘open by demand’ may be a more appropriate approach than ‘open by default.’
  • There is a good deal of disagreement about whether data can be opened responsibly. Some of this disagreement may stem from a lack of clarity about what kind of data we are talking about when we talk about open data.
  • Personal data and human subjects data that was never foreseen to be part of “open data” is potentially being opened, bringing with it risks for those who share it as well as for those who store it.
  • Informed consent for personal/human subject data is a tricky concept and it’s not clear whether it is even possible in the current scenario of personal data being ‘opened’ and the lack of control over how it may be used now or in the future, and the increasing ease of data re-identification.
  • We may want to look at data as a toxic asset rather than a beneficial one, because of the liabilities it brings.
  • Rather than a blanket “open” categorization, sub-categorizations that restrict data sets in different ways might be a possibility.
  • The sector needs to improve its understanding of the legal frameworks around data and data collection, storage and use or it may start to see lawsuits in the near future.
  • Work on data literacy and community involvement in defining what data is of interest and is collected, as well as threat modeling together with community groups is a way to reduce risk and improve data quality, demand and use; but it’s a high-touch activity that may not be possible for every kind of organization.
  • As data intermediaries, we need to do a much better job as a sector to see what we are doing with open data and how we are using it to provide services and contextualized information to the poor and disenfranchised. This is a huge opportunity and we have not done nearly enough here.

The Technology Salon is conducted under Chatham House Rule so attribution has not been made in this post. If you’d like to attend future Salons, sign up here

 

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Screen Shot 2014-05-08 at 9.36.00 AMDebate and thinking around data, ethics, ICT have been growing and expanding a lot lately, which makes me very happy!

Coming up on May 22 in NYC, the engine room, Hivos, the Berkman Center for Internet and Society, and Kurante (my newish gig) are organizing the latest in a series of events as part of the Responsible Data Forum.

The event will be hosted at ThoughtWorks and it is in-person only. Space is limited, so if you’d like to join us, let us know soon by filling in this form. 

What’s it all about?

This particular Responsible Data Forum event is an effort to map the ethical, legal, privacy and security challenges surrounding the increased use and sharing of data in development programming. The Forum will aim to explore the ways in which these challenges are experienced in project design and implementation, as well as when project data is shared or published in an effort to strengthen accountability. The event will be a collaborative effort to begin developing concrete tools and strategies to address these challenges, which can be further tested and refined with end users at events in Amsterdam and Budapest.

We will explore the responsible data challenges faced by development practitioners in program design and implementation.

Some of the use cases we’ll consider include:

  • projects collecting data from marginalized populations, aspiring to respect a do no harm principle, but also to identify opportunities for informational empowerment
  • project design staff seeking to understand and manage the lifespan of project data from collection, through maintenance, utilization, and sharing or destruction.
  • project staff that are considering data sharing or joint data collection with government agencies or corporate actors
  • project staff who want to better understand how ICT4D will impact communities
  • projects exploring the potential of popular ICT-related mechanisms, such as hackathons, incubation labs or innovation hubs
  • projects wishing to use development data for research purposes, and crafting responsible ways to use personally identifiable data for academic purposes
  • projects working with children under the age of 18, struggling to balance the need for data to improve programming approaches, and demand higher levels of protection for children

By gathering a significant number of development practitioners grappling with these issues, the Forum aims to pose practical and critical questions to the use of data and ICTs in development programming. Through collaborative sessions and group work, the Forum will identify common pressing issues for which there might be practical and feasible solutions. The Forum will focus on prototyping specific tools and strategies to respond to these challenges.

What will be accomplished?

Some outputs from the event may include:

  • Tools and checklists for managing responsible data challenges for specific project modalities, such as sms surveys, constructing national databases, or social media scraping and engagement.
  • Best practices and ethical controls for data sharing agreements with governments, corporate actors, academia or civil society
  • Strategies for responsible program development
  • Guidelines for data-driven projects dealing with communities with limited representation or access to information
  • Heuristics and frameworks for understanding anonymity and re-identification of large development data sets
  • Potential policy interventions to create greater awareness and possibly consider minimum standards

Hope to see some of you on the 22nd! Sign up here if you’re interested in attending, and read more about the Responsible Data Forum here.

 

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