05
Oct 17

Biased #data

Diana, October 5.

bias data

To continue my previous post, I’ll talk more about the biased data in this one.

Like I mentioned before, the Big Data is, unfortunately, not objective, but a human creation: Taylor and Schroeder accentuate that if we know the whole information on the matter, it can lead to the difficulty in understanding it and to the unwillingness to share it. Also, if we are not critical enough towards data we are receiving, we can buy false information as it is, without the evidence.

Big Data is everywhere. Big companies or “development professionals” such as the United Nations (UN) or Organisation for Economic Co-operation and Development (OECD) are using these types of data for research and exploration. Companies meet a lot of technical concerns on the way, like risks and issues of bias have tended to dominate the discussion so far.

Taylor and Schroeder point out the role of biased data in development politics. One example is how data is politicised, namely, that even correct data may not be accepted: all information has to be agreed upon in order to be useful to country authorities as support for policy decisions. Many undeveloped countries have that problem, where real information is hard to acquire. Officials censors all information that comes from sectors of the population who feel underrepresented.

bias data

Kate Crawford — a Principal Researcher at Microsoft Research New York City, a Visiting Professor at MIT’s Center for Civic Media and a Senior Fellow at NYU’s Information Law Institute, her research addresses the social impacts of big data and she’s currently writing a new book on data and power with Yale University Press — published an article in Harward Business Review: “The Hidden Biases in Big Data”.

Hidden biases in both the collection and analysis stages present considerable risks and are as important to the big-data equation as the numbers themselves. — Kate Crawford.

Kate takes up an example to explain the hidden bias in data. There was a lot of tweets about Hurricane Sandy, more than 20 million, between October 27 and November 1. A study shows that these data don’t represent the whole picture. The highest number of tweets about Sandy came from Manhattan: the city has a high level of smartphone ownership and Twitter use. On the other hand, it forms the illusion that Manhattan was the hub of the disaster. Not so many messages originated from affected locations, such as Breezy Point, Coney Island, Rockaway and even fewer tweets came from the worst-hit areas.

Here we can ask ourselves: how do the people outside of affected areas know about what is really happening there?

We rely more and more on Big Data’s numbers to speak for themselves, but we risk in misunderstanding the results and in turn misdirecting important public resources are as big as data itself. “Development professionals” do that mistake also, they rely on information without questioning it. All that misinformation can cause a wrong type of help to a wrong place or be an obstacle in aid relief.

Taylor and Schroeder take a similar example of biased data: the Big Data being used by “development professionals” in mobiles for tracking population movement in disaster relief. The problem with collecting this data is that it is not totally complete: not everyone uses mobile phones, with users particularly low amongst vulnerable and ‘hidden’ populations such as children, the elderly, the poorest and women.

As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already existing inequities will be further entrenched. Thus, with every big data set, we need to ask which people are excluded. Which places are less visible? What happens if you live in the shadow of big data sets? — Kate Crawford.

 


04
Oct 17

Citizen-Generated #Data. A Game-Changer for Human Rights?

Louise, October 4.

I will, as promised, dedicate this post to some positive examples of when data has enhanced human rights and global development.

One example, which is commonly mentioned in discussions like these, is big data in relation to the right to health. The right to health is rather broad and, as stated in the International Covenant on Economic, Social and Cultural Rights, includes medical access, equal care, the right to prevention, treatment and control of diseases, and broader development areas such as the right to water and food.

An explicit positive example of how big data enhances the right to health is, as pointed out by Spratt & Baker (2015:13), the so-called remote patient monitoring (RPM). In developing countries, where the lack of access to doctors is often a fact, data can enable RPM as it allows medical staff to monitor and help those in need without actually being close-by. Instead, they can provide adequate health care through smart devices.

In addition, from a development perspective, there are according to Spratt & Baker (2015:22) strong indicators that the collection and analysis of big data from different sources could, in powerful systems, be used to warn people of issues such as natural or humanitarian disasters, famine, outbreaks of diseases, and other issues related to human security.

In my work, which relates a lot closer to the International Covenant on Civil and Political Rights, I have perceived big data usage as more tied to repression than to justice. But when looking closer at the positive examples of how big data can be used, I must admit that I am a bit amazed.

I recently came in contact with the term citizen-generated data – data in the hands of the people. According to the network CIVICUS, this is data that civil society actors collect or produce in order to “monitor, demand or drive change on issues that affect them”. An initiative which has been started by the network is called DataShift, which monitors the sustainable development goals and increases government accountability so that the voices of the people can influence national and global policy in order for the most marginalised people to be heard by the most powerful.

When data ends up in the hands of the people who want to bring about change, I can truly see how also civil and political rights can gain from it. Let us return to the example of the Kenyan organisation Ushahidi, which I mentioned in my last post. To me, this is one of the most impressive examples of how ICT and data can prevent human rights abuses such as election violence and potential mass atrocities. The organisation is one of the most vocal groups in the East African region when it comes to applying ICT in relation to human rights, development and human security. According to the organisation, the goal is to “create the simplest way of aggregating information from the public for use in crisis response”.

Using the concept of crowdsourcing for social activism and public accountability, the organisation has created a model that has later been used for mapping not only election violence but also enhance humanitarian response in the crisis such as the Haiti earthquake and tracking malaria, Ebola and other diseases. The model has been coined as Activist Mapping, which is described as a combination of social activism, citizen journalism and geospatial information. What is great with Ushahidi is that it is, as also pointed out by Read, Taithe and Mac Ginty (2016:10), a typical example of when the information sharing is conducted on a horizontal level, meaning that citizens themselves have been able to use ICT and new media to inform and warn each other about urgent and often violent situations.

Citizen-Generated #Data

Photo: rsambrook

HarassMap is another example that is tied to the organisation Ushahidi. It is a volunteer-based initiative which aims to combat sexual harassment in Egypt. By collecting data that make up an online map, the hope is that the information can serve as a point of reference for “occurrences of incidents, positive interventions and available services” such as for example legal assistance.

It is clear that there is not only one but several examples of how data and ICT can be used to enhance or improve the respect for human rights. What I find interesting and relevant in all above-mentioned examples is the large focus on sharing. According to Spratt & Baker (2015:7), this phenomenon, in combination with the emergence of the internet, is one of the several improvements that enable data to be effective and have a real impact on human rights.

To finish off, I would like to return to a key point that I made in my last post. The effectiveness and “goodness” of big data depends to a large extent in whose hands it is placed. In my next post, I will discuss what happens when data slip through the hands of the people and instead ends up in the control of repressive actors.

Until then, do feel free to comment and share your thoughts.

 


29
Sep 17

Is a BIG DATA always a GOOD DATA or is it sometimes a MESS?

Goda, September 29.

dataAs it was discussed in the previous chapters, the big data has a potential to do many things and add value to major areas of our lives. So almost everyone is heavily involved in the big data. Moreover, one of the important aspects, reshaping the world today, is the worldwide accessibility to the Internet which has become incredibly broad. Internet live stats shows that approx. 40% of the entire population has an internet connection today. In 1995, it was less than 1%. The number of internet users has amazingly increased from 1999 to 2013.  The first billion was reached in 2005, the second billion in 2010, the third one in 2014 (Internetlivestats.com, 2017). While big data is concerned with all kinds of sources, it is estimated that the majority of it comes from unstructured sources and social media constitutes perhaps the biggest source of unstructured sources for big data including blogs, forums, social networking platforms, gaming and many other networks (The Statistics Portal, 2017).

Social media has become a key element in every society and culture, encouraging individuals to gather together on common interests and share opinions through the Internet. This has prompted the development of new big data approaches to capture, process and analyse large and complex data. New statistical methods and tools can process and examine such big data effectively at such a scale and speed that would have been unimaginable just a few years ago (Spratt & Baker, 2016).

However, to have lots of data doesn’t mean to have a good data. Surprisingly, the biggest long-term challenge of implementing and integrating big data isn’t technology – it is data governance and management or proper data collection and analysis (Read, Taithe & Mac Ginty, 2016).

When talking about data governance and management many articles concentrate on businesses to gain insights through analysis, to understand consumers’ behaviors by targeting products and services more effectively. Nevertheless, it has the same impact in politics too in terms of improving government decision-making and informing about their activities.

WHY? Because the DATA is the main element, not a technology, and implementation of the data into the whole picture is very important. Therefore, if the big data quality is POOR and INCORRECTLY analysed, proper integration of a big data can become one of the major problems.

EXAMPLE:

Nowadays, almost anyone can easily access public information from social media platforms such as Facebook or Twitter. Access to large amounts of data on millions of peoples’ activities and behaviors is an exceptionally good resource for every organisation by describing potential customer’s profile from the way how individuals naturally communicate online.

Therefore, recently there has been a lot of complaints due to the subjectivity in data because it was being used as a manipulation strategy by governments. Governments have faster, simpler methods to access the data. A large amount of articles talks about the company Cambridge Analytica which helped to manipulate both the US election and the EU referendum by using social networking platforms data in terms of how people show their opinions and preferences in social media and in terms of creating fake online profiles to give an impression that many  individuals support their certain political position (www.parliament.uk, 2017).

The  REASON of these problems is that governments can access data more accurately and quickly and by adjusting their power relations (Read, Taithe & Mac Ginty, 2016). Moreover, there are some discussions that social media data may not include vulnerable groups such as the elderly or groups with lower salaries. Therefore, there are big gaps in the data and there are no procedures yet for controlling these gaps.

Taking everything into consideration, you don’t necessarily need to examine a lot of data to get an accurate result, you just need to be sure you are analysing the RIGHT DATA. You should seek out new and diverse sources that can give you a well-rounded overview of the subject. Therefore, before making important decisions it is important to consider thoroughly all the information we have available, to reach a fair and just judgement.


26
Sep 17

Think About It – Is Bigger Better?

Diana, September 26.

Information and communication technology (ICT) haven’t even existed for some years ago. Now, it helps us to interact in the digital world. ICT gave way to Big Data revolution, namely, to all voluminous amount of structured and unstructured data which meant to be quarried with information. The amount of data that’s being created and stored on a global level is almost inconceivable, and it just keeps growing.

I challenge you to think about it one more time – is bigger really better? Let’s try to answer this question.

[youtube]https://www.youtube.com/watch?v=-Gj93L2Qa6c[/youtube]

SAS Software

Taylor and Schroeder talk about that the development of data and technologies, as well as usage of those by people, have the potential to give the public a rich mine of information about health interventions, human mobility, conflict and violence, technology adoption, communication dynamics and economic behaviour.

The bigger data, the better: it allows us to perceive the environment in new ways. By having more information, we can do things that you couldn’t do before. We can collect information, share it, analyse it, learn from it and store it for years to come. Also, big data is a good tool to solve some of the world’s problems, like global food insecurity, medical care, energy and climate change.

Additionally, data and technologies bring together heterogeneous “development professionals“, such as donors, non-governmental organisations’ activists, government policy officers, consultants, academics, intended beneficiaries and so forth, who are active in various development aid organisations distributed all over the world.

In the data-driven world, the usage of data is also necessary. “Development professionals” are using data not only to promote and endorse development discourse but, as well, to save time. Big data accessibility and availability to useful information allows organizations to better understand the changing aspects of local field environments and, in turn, simplifies a better decision-making. Big data is a game changer if it is good, clean, accurate and transparent.

Nevertheless, what about the risks of losing data in the sea of all that informational overflow?

Taylor and Schroeder stress that bigger is not better, namely, there is an absence of good data. They lift up few drawbacks with “Bigger” Data. Data is not always simple and stable, namely, we need knowledge of how to use it. Most of the time, it is enough with some basic knowledge. It depends, of course, on what is the purpose of usage: a post on Facebook or managing a website.

Further, data can be bias. If we know the whole information on the matter, it can lead to the difficulty in understanding it and to the unwillingness to share it. The other risk here can be that we are not critical enough towards data we are receiving, namely, we buy it as it is, without the evidence.

Moreover, risks with an absence of the clear ethical framework, as well as rules for handling and sharing. The data revolution is so far mainly a technical one: the power of data to sort, categorise and intervene has not yet been clearly linked to a moral basis. In fact, while data-driven unfairness is evolving at exactly the same pace as data processing technologies, awareness and tools for fighting it are not.

Furthermore, anonymization techniques are unreliable. Data anonymization is the system intended to make it impossible to identify a particular individual from stored data related to him/her. Unfortunately, it doesn’t always work. One aspect of anonymization that worries individuals who value their privacy is that the process can be reversed.

The only way to stop big data from becoming big brother is to introduce privacy laws that protect the basic human rights online.”
― Arzak Khan

 


22
Sep 17

Thinking about #data (for development)?

Eraptis, September 22.

Thinking about data (for development) has really got me thinking. What is data, and what makes it “big”? How can it be used in the context of development, and which data really matters – is all data created equal? Blogging to reflect on these and other questions, sharing our thoughts with the (social media) world, might help in putting these things into perspective. It may even change how we view things. But then again, to who are we talking – who reads our blogs, and which blogs do we read ourselves?

Tobias Denskus and Andrea S. Papan have taken a closer look into the practices of blogging by development practitioners. In their paper, they interviewed a set of international development bloggers’ on their motivations for maintaining a blog. Although the motivations might be many, their research primarily points towards some individual reasons for maintaining a blog. Among the reasons stated were venting and reflecting on everyday occurrences in the professional life of the bloggers, putting them “out there” for others to engage with. The “Others” mainly comprising other development professionals sharing and consuming information as a way to stay in tune with the “hot topics” of the development sphere, and as a way to show one’s own expertise on the issues of the day. The networking aspect of it all, thus, seems to be an important motivation for blogging – leading to both virtual and real meetings. From an organizational perspective, these things certainly have the potential to create innovative ideas, and lead to improved processes – but there seems to be something missing. As the authors also point out, for blogging to be truly impactful, it needs to turn away from this inward tendency to also engage with local communities.

Why is this important? In my view, it potentially reflects a common practice of development discourse to view the means to an end as the end itself. ICT and data seem to be no different. In the opening chapter of his recent book, Tim Unwin argues exactly this point when writing:

All too often, ICT4D research and practice has been technologically driven, and has therefore tended to replicate existing social and economic structures, thereby failing sufficiently to explore, interpret, or change the very conditions that have given rise to them.” – Tim Unwin 

So – how to challenge this? Perhaps a good starting point is to look at the very definition of “data”, defined by the Oxford dictionaries as “facts and statistics collected together for reference or analysis”. Data, thus, is by its very nature positivistic. It can, at best, tell us what ”is”. But can data be normative? Can data tell us what ”should be”? As Spratt and Baker writes, the answer is not straight forward. While some would argue that if the data sets were just big enough theory as we know it would cease to exist, others point to such statements as hubris – dangerously overestimating the potential of technology to advance development.

Although I would tend to join ranks with the latter, I simultaneously share Unwin’s optimistic mindset that done right ICTs can indeed be a powerful medium for advancing development. But before that can happen we all need to engage in self-reflection and be critical about the appropriate use of ICT4D in order to consider all aspects of an implementation of data-driven development initiatives. At the heart of all this, Unwin argues, lies adopting a critical theory mindset. Among many things, this means doing away with the rather naïve and problematic notion that ICT, in and by itself, is good. And instead see it for what it is, one of many potential means to an end where the central aspect must be to understand the needs of those people for whom these kinds of interventions are intended. In the context of big data, this means working with and empowering those peoples to both generate and analyze this kind of information for themselves.

Before ending this post I would like to leave you with a thought related to one of my initial questions – is all data created equal? Well, Spratt and Baker note that big data analysis, particularly in the context of social media, is heavily biased towards information in the English language. If data is “facts and statistics collected together for reference or analysis”, and most data analyzed is in English, then who’s voices are we really listening to?

Featured image: Eventfinda

 


18
Sep 17

What is BIG DATA and why it can be dangerous?

Goda, September 18.

big dataOver the last few decades, information communication technologies (ICT) have developed gradually and brought many changes to global and international development.  The rise of the social media and evolution of big data are one of them. In order to talk about big data in the context of social media, we have to understand what big data means.

So let’s imagine the time when there were no computers yet and all the information was stored in written sources – books, letters and etc. Let’s imagine that we have so many of these sources that we have to open a huge library that would help anyone to find any small text or photo they need. This means that library must have a clear system and the ways to find any information quickly.

The same thing happened with the digital data. However, the amount of it is more than enormous comparing to written sources. Some time ago this process of handling and storing information was covered by simple databases, but when practically everything that goes on in our society moved into a virtual space, all the impressive amount of information needed to have impressive programs. This is where the term “Big Data” came from.

Many authors compare big data with the fuel that drives the next industrial revolution into every aspect of economic and social life (Tufekci, 2017). Soon, particularly in developing countries, big data will be able to help to improve even areas such as government decision-making, implementation of social welfare programs or scientific research.

There are lot’s great benefits associated with big data. However, big risks are also widely discussed. The three main big risks can be the following:

  • Quantity and the quality do not match. Having a large amount of data does not necessarily mean having a high-quality data. For example, many of the developments in digital humanitarianism are based on what is possible rather than what is needed. More and more money is being invested in developing these technologies but their use is often limited.
  • Moreover, everything can be tracked – how, why and by whom information is collected, stored and processed. Social media, music or videos have all been stored as a data that has become available for analysis. For example, Facebook always can show where you are or when was the last time when you were online.
  • Furthermore, it can cause big privacy problems. Data protection online is a significant and increasingly urgent challenge especially in the previously mentioned networking platforms and many others, such as Facebook, Twitter, WhatsApp, Uber or AirBnB which have shown how huge amount of data can be achieved in the short period of time and, for example, how sharing one post on Facebook can make a difference.

Taking everything into consideration, it seems that big data will become inevitable everywhere. Nevertheless, despite its benefits, the three examples of the main risks of big data mentioned above are currently seen as very important challenges in the international development field which will be discussed in more detail later.

Thus, even if a huge amount of money is being invested in developing and improving digital technologies, their use is still quite limited. Also, these are the early days of the data revolution and many uses of it still remain unforeseen. Moreover, human impact how information is gathered and used needs to be considered too.

Therefore, thinking about the potential of big data, it requires more consideration about information gathering and processing especially in the light of accuracy, risk evaluation and assessment (Meier, 2015).

 


10
Sep 17

Hello there!

@Data4ComDev, September 10.

Blog

Welcome to our newly started blog. We are happy that you have found your way here already. You may wonder: who are you and what is this blog all about?

We are five students enrolled in a Master’s Programme in Communication for Development at Malmö University. We are currently in the process of exploring the possibilities and challenges of starting up this joint blog. No doubt it will be a little bit hard, very rewarding, extremely educating and, for sure, heaps of fun.

The theme we will be exploring is called Social Media, Data and Development. We will hence be looking into data in the context of development communication. That is what we have decided for now, and we are looking forward to figuring out the rest.

While you wait for us to finalise our plans, please take some time to have a look at our brief bios in the “about us” section in the top right corner. And make sure to come back soon, we are all up for some intense weeks of blogging.