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This post was written with input from Maliha Khan, Independent Consultant; Emily Tomkys, Oxfam GB; Siobhan Green, Sonjara and Zara Rahman, The Engine Room.

A friend reminded me earlier this month at the MERL Tech Conference that a few years ago when we brought up the need for greater attention to privacy, security and ethics when using ICTs and digital data in humanitarian and development contexts, people pointed us to Tor, encryption and specialized apps. “No, no, that’s not what we mean!” we kept saying. “This is bigger. It needs to be holistic. It’s not just more tools and tech.”

So, even if as a sector we are still struggling to understand and address all the different elements of what’s now referred to as “Responsible Data” (thanks to the great work of the Engine Room and key partners), at least we’ve come a long way towards framing and defining the areas we need to tackle. We understand the increasing urgency of the issue that the volume of data in the world is increasing exponentially and the data in our sector is becoming more and more digitalized.

This year’s MERL Tech included several sessions on Responsible Data, including Responsible Data Policies, the Human Element of the Data Cycle, The Changing Nature of Informed Consent, Remote Monitoring in Fragile Environments and plenary talks that mentioned ethics, privacy and consent as integral pieces of any MERL Tech effort.

The session on Responsible Data Policies was a space to share with participants why, how, and what policies some organizations have put in place in an attempt to be more responsible. The presenters spoke about the different elements and processes their organizations have followed, and the reasoning behind the creation of these policies. They spoke about early results from the policies, though it is still early days when it comes to implementing them.

What do we mean by Responsible Data?

Responsible data is about more than just privacy or encryption. It’s a wider concept that includes attention to the data cycle at every step, and puts the rights of people reflected in the data first:

  • Clear planning and purposeful collection and use of data with the aim of improving humanitarian and development approaches and results for those we work with and for
  • Responsible treatment of the data and respectful and ethical engagement with people we collect data from, including privacy and security of data and careful attention to consent processes and/or duty of care
  • Clarity on data sharing – what data, from whom and with whom and under what circumstances and conditions
  • Attention to transparency and accountability efforts in all directions (upwards, downwards and horizontally)
  • Responsible maintenance, retention or destruction of data.

Existing documentation and areas to explore

There is a huge bucket of concepts, frameworks, laws and policies that already exist in various other sectors and that can be used, adapted and built on to develop responsible approaches to data in development and humanitarian work. Some of these are in conflict with one another, however, and those conflicts need to be worked out or at least recognized if we are to move forward as a sector and/or in our own organizations.

Some areas to explore when developing a Responsible Data policy include:

  • An organization’s existing policies and practices (IT and equipment; downloading; storing of official information; confidentiality; monitoring, evaluation and research; data collection and storage for program administration, finance and audit purposes; consent and storage for digital images and communications; social media policies).
  • Local and global laws that relate to collection, storage, use and destruction of data, such as: Freedom of information acts (FOIA); consumer protection laws; data storage and transfer regulations; laws related to data collection from minors; privacy regulations such as the latest from the EU.
  • Donor grant requirements related to data privacy and open data, such as USAID’s Chapter 579 or International Aid Transparency Initiative (IATI) stipulations.

Experiences with Responsible Data Policies

At the MERL Tech Responsible Data Policy session, organizers and participants shared their experiences. The first step for everyone developing a policy was establishing wide agreement and buy-in for why their organizations should care about Responsible Data. This was done by developing Values and Principles that form the foundation for policies and guidance.

Oxfam’s Responsible Data policy has a focus on rights, since Oxfam is a rights-based organization. The organization’s existing values made it clear that ethical use and treatment of data was something the organization must consider to hold true to its ethos. It took around six months to get all of the global affiliates to agree on the Responsible Program Data policy, a quick turnaround compared to other globally agreed documents because all the global executive directors recognized that this policy was critical. A core point for Oxfam was the belief that digital identities and access will become increasingly important for inclusion in the future, and so the organization did not want to stand in the way of people being counted and heard. However, it wanted to be sure that this was done in a way that balanced and took privacy and security into consideration.

The policy is a short document that is now in the process of operationalization in all the countries where Oxfam works. Because many of Oxfam’s affiliate headquarters reside in the European Union, it needs to consider the new EU regulations on data, which are extremely strict, for example, providing everyone with an option for withdrawing consent. This poses a challenge for development agencies who normally do not have the type of detailed databases on ‘beneficiaries’ as they do on private donors. Shifting thinking about ‘beneficiaries’ and treating them more as clients may be in order as one result of these new regulations. As Oxfam moves into implementation, challenges continue to arise. For example, data protection in Yemen is different than data protection in Haiti. Knowing all the national level laws and frameworks and mapping these out alongside donor requirements and internal policies is extremely complicated, and providing guidance to country staff is difficult given that each country has different laws.

Girl Effect’s policy has a focus on privacy, security and safety of adolescent girls, who are the core constituency of the organization. The policy became clearly necessary because although the organization had a strong girl safeguarding policy and practice, the effect of digital data had not previously been considered, and the number of programs that involve digital tools and data is increasing. The Girl Effect policy currently has four core chapters: privacy and security during design of a tool, service or platform; content considerations; partner vetting; and MEAL considerations. Girl Effect looks at not only the privacy and security elements, but also aims to spur thinking about potential risks and unintended consequences for girls who access and use digital tools, platforms and content. One core goal is to stimulate implementers to think through a series of questions that help them to identify risks. Another is to establish accountability for decisions around digital data.

The policy has been in process of implementation with one team for a year and will be updated and adapted as the organization learns. It has proven to have good uptake so far from team members and partners, and has become core to how the teams and the wider organization think about digital programming. Cost and time for implementation increase with the incorporation of stricter policies, however, and it is challenging to find a good balance between privacy and security, the ability to safely collect and use data to adapt and improve tools and platforms, and user friendliness/ease of use.

Catholic Relief Services has an existing set of eight organizational principles: Sacredness and Dignity of the human person; Rights and responsibilities; Social Nature of Humanity; The Common Good; Subsidiarity; Solidarity; Option for the Poor; Stewardship. It was a natural fit to see how these values that are already embedded in the organization could extend to the idea of Responsible Data. Data is an extension of the human person, therefore it should be afforded the same respect as the individual. The principle of ‘common good’ easily extends to responsible data sharing. The notion of subsidiarity says that decision-making should happen as close as possible to the place where the impact of the decision will be the strongest, and this is nicely linked with the idea of sharing data back with communities where CRS works and engaging them in decision-making. The option for the poor urges CRS to place a preferential value on privacy, security and safety of the data of the poor over the data demands of other entities.

The organization is at the initial phase of creating its Responsible Data Policy. The process includes the development of the values and principles, two country learning visits to understand the practices of country programs and their concerns about data, development of the policy, and a set of guidelines to support staff in following the policy.

USAID recently embarked on its process of developing practical Responsible Data guidance to pair with its efforts in the area of open data. (See ADS 579). More information will be available soon on this initiative.

Where are we now?

Though several organizations are moving towards the development of policies and guidelines, it was clear from the session that uncertainties are the order of the day, as Responsible Data is an ethical question, often relying on tradeoffs and decisions that are not hard and fast. Policies and guidelines generally aim to help implementers ask the right questions, sort through a range of possibilities and weigh potential risks and benefits.

Another critical aspect that was raised at the MERL Tech session was the financial and staff resources that can be required to be responsible about data. On the other hand, for those organizations receiving funds from the European Union or residing in the EU or the UK (where despite Brexit, organizations will likely need to comply with EU Privacy Regulations), the new regulations mean that NOT being responsible about data may result in hefty fines and potential legal action.

Going from policy to implementation is a challenge that involves both capacity strengthening in this new area as well as behavior change and a better understanding of emerging concepts and multiple legal frameworks. The nuances by country, organization and donor make the process difficult to get a handle on.

Because staff and management are already overburdened, the trick to developing and implementing Responsible Data Policies and Practice will be finding ways to strengthen staff capacity and to provide guidance in ways that do not feel overwhelmingly complex. Though each situation will be different, finding ongoing ways to share resources and experiences so that we can advance as a sector will be one key step for moving forward.

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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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This is a guest post from Anna Crowe, Research Officer on the Privacy in the Developing World Project, and  Carly Nyst, Head of International Advocacy at Privacy International, a London-based NGO working on issues related to technology and human rights, with a focus on privacy and data protection. Privacy International’s new report, Aiding Surveillance, which covers this topic in greater depth was released this week.

by Anna Crowe and Carly Nyst

NOV 21 CANON 040

New technologies hold great potential for the developing world, and countless development scholars and practitioners have sung the praises of technology in accelerating development, reducing poverty, spurring innovation and improving accountability and transparency.

Worryingly, however, privacy is presented as a luxury that creates barriers to development, rather than a key aspect to sustainable development. This perspective needs to change.

Privacy is not a luxury, but a fundamental human right

New technologies are being incorporated into development initiatives and programmes relating to everything from education to health and elections, and in humanitarian initiatives, including crisis response, food delivery and refugee management. But many of the same technologies being deployed in the developing world with lofty claims and high price tags have been extremely controversial in the developed world. Expansive registration systems, identity schemes and databases that collect biometric information including fingerprints, facial scans, iris information and even DNA, have been proposed, resisted, and sometimes rejected in various countries.

The deployment of surveillance technologies by development actors, foreign aid donors and humanitarian organisations, however, is often conducted in the complete absence of the type of public debate or deliberation that has occurred in developed countries. Development actors rarely consider target populations’ opinions when approving aid programmes. Important strategy documents such as the UN Office for Humanitarian Affairs’ Humanitarianism in a Networked Age and the UN High-Level Panel on the Post-2015 Development Agenda’s A New Global Partnership: Eradicate Poverty and Transfer Economies through Sustainable Development give little space to the possible impact adopting new technologies or data analysis techniques could have on individuals’ privacy.

Some of this trend can be attributed to development actors’ systematic failure to recognise the risks to privacy that development initiatives present. However, it also reflects an often unspoken view that the right to privacy must necessarily be sacrificed at the altar of development – that privacy and development are conflicting, mutually exclusive goals.

The assumptions underpinning this view are as follows:

  • that privacy is not important to people in developing countries;
  • that the privacy implications of new technologies are not significant enough to warrant special attention;
  • and that respecting privacy comes at a high cost, endangering the success of development initiatives and creating unnecessary work for development actors.

These assumptions are deeply flawed. While it should go without saying, privacy is a universal right, enshrined in numerous international human rights treaties, and matters to all individuals, including those living in the developing world. The vast majority of developing countries have explicit constitutional requirements to ensure that their policies and practices do not unnecessarily interfere with privacy. The right to privacy guarantees individuals a personal sphere, free from state interference, and the ability to determine who has information about them and how it is used. Privacy is also an “essential requirement for the realization of the right to freedom of expression”. It is not an “optional” right that only those living in the developed world deserve to see protected. To presume otherwise ignores the humanity of individuals living in various parts of the world.

Technologies undoubtedly have the potential to dramatically improve the provision of development and humanitarian aid and to empower populations. However, the privacy implications of many new technologies are significant and are not well understood by many development actors. The expectations that are placed on technologies to solve problems need to be significantly circumscribed, and the potential negative implications of technologies must be assessed before their deployment. Biometric identification systems, for example, may assist in aid disbursement, but if they also wrongly exclude whole categories of people, then the objectives of the original development intervention have not been achieved. Similarly, border surveillance and communications surveillance systems may help a government improve national security, but may also enable the surveillance of human rights defenders, political activists, immigrants and other groups.

Asking for humanitarian actors to protect and respect privacy rights must not be distorted as requiring inflexible and impossibly high standards that would derail development initiatives if put into practice. Privacy is not an absolute right and may be limited, but only where limitation is necessary, proportionate and in accordance with law. The crucial aspect is to actually undertake an analysis of the technology and its privacy implications and to do so in a thoughtful and considered manner. For example, if an intervention requires collecting personal data from those receiving aid, the first step should be to ask what information is necessary to collect, rather than just applying a standard approach to each programme. In some cases, this may mean additional work. But this work should be considered in light of the contribution upholding human rights and the rule of law make to development and to producing sustainable outcomes. And in some cases, respecting privacy can also mean saving lives, as information falling into the wrong hands could spell tragedy.

A new framing

While there is an increasing recognition among development actors that more attention needs to be paid to privacy, it is not enough to merely ensure that a programme or initiative does not actively harm the right to privacy; instead, development actors should aim to promote rights, including the right to privacy, as an integral part of achieving sustainable development outcomes. Development is not just, or even mostly, about accelerating economic growth. The core of development is building capacity and infrastructure, advancing equality, and supporting democratic societies that protect, respect and fulfill human rights.

The benefits of development and humanitarian assistance can be delivered without unnecessary and disproportionate limitations on the right to privacy. The challenge is to improve access to and understanding of technologies, ensure that policymakers and the laws they adopt respond to the challenges and possibilities of technology, and generate greater public debate to ensure that rights and freedoms are negotiated at a societal level.

Technologies can be built to satisfy both development and privacy.

Download the Aiding Surveillance report.

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