Regulation of Big Data: Perspectives on Strategy, Policy, Law and Privacy


Paper by Pompeu CasanovasLouis de KokerDanuta Mendelson and David Watts: “…presents four complementary perspectives stemming from governance, law, ethics, and computer science. Big, Linked, and Open Data constitute complex phenomena whose economic and political dimensions require a plurality of instruments to enhance and protect citizens’ rights. Some conclusions are offered in the end to foster a more general discussion.

This article contends that the effective regulation of Big Data requires a combination of legal tools and other instruments of a semantic and algorithmic nature. It commences with a brief discussion of the concept of Big Data and views expressed by Australian and UK participants in a study of Big Data use in a law enforcement and national security perspective. The second part of the article highlights the UN’s Special Rapporteur on the Right to Privacy interest in the themes and the focus of their new program on Big Data. UK law reforms regarding authorisation of warrants for the exercise of bulk data powers is discussed in the third part. Reflecting on these developments, the paper closes with an exploration of the complex relationship between law and Big Data and the implications for regulation and governance of Big Data….(More)”.

Computational Propaganda Worldwide


Executive Summary: “The Computational Propaganda Research Project at the Oxford Internet Institute, University of Oxford, has researched the use of social media for public opinion manipulation. The team involved 12 researchers across nine countries who, altogether, interviewed 65 experts, analyzed tens of millions posts on seven different social media platforms during scores of elections, political crises, and national security incidents. Each case study analyzes qualitative, quantitative, and computational evidence collected between 2015 and 2017 from Brazil, Canada, China, Germany, Poland, Taiwan, Russia, Ukraine, and the United States.

Computational propaganda is the use of algorithms, automation, and human curation to purposefully distribute misleading information over social media networks. We find several distinct global trends in computational propaganda. •

  • Social media are significant platforms for political engagement and crucial channels for disseminating news content. Social media platforms are the primary media over which young people develop their political identities.
    • In some countries this is because some companies, such as Facebook, are effectively monopoly platforms for public life. o In several democracies the majority of voters use social media to share political news and information, especially during elections.
    • In countries where only small proportions of the public have regular access to social media, such platforms are still fundamental infrastructure for political conversation among the journalists, civil society leaders, and political elites.
  • Social media are actively used as a tool for public opinion manipulation, though in diverse ways and on different topics. o In authoritarian countries, social media platforms are a primary means of social control. This is especially true during political and security crises. o In democracies, social media are actively used for computational propaganda either through broad efforts at opinion manipulation or targeted experiments on particular segments of the public.
  • In every country we found civil society groups trying, but struggling, to protect themselves and respond to active misinformation campaigns….(More)”.

Open Data’s Effect on Food Security


Jeremy de Beer, Jeremiah Baarbé, and Sarah Thuswaldner at Open AIR: “Agricultural data is a vital resource in the effort to address food insecurity. This data is used across the food-production chain. For example, farmers rely on agricultural data to decide when to plant crops, scientists use data to conduct research on pests and design disease resistant plants, and governments make policy based on land use data. As the value of agricultural data is understood, there is a growing call for governments and firms to open their agricultural data.

Open data is data that anyone can access, use, or share. Open agricultural data has the potential to address food insecurity by making it easier for farmers and other stakeholders to access and use the data they need. Open data also builds trust and fosters collaboration among stakeholders that can lead to new discoveries to address the problems of feeding a growing population.

 

A network of partnerships is growing around agricultural data research. The Open African Innovation Research (Open AIR) network is researching open agricultural data in partnership with the Plant Phenotyping and Imaging Research Centre (P2IRC) and the Global Institute for Food Security (GIFS). This research builds on a partnership with the Global Open Data for Agriculture and Nutrition (GODAN) and they are exploring partnerships with Open Data for Development (OD4D) and other open data organizations.

…published two works on open agricultural data. Published in partnership with GODAN, “Ownership of Open Data” describes how intellectual property law defines ownership rights in data. Firms that collect data own the rights to data, which is a major factor in the power dynamics of open data. In July, Jeremiah Baarbé and Jeremy de Beer will be presenting “A Data Commons for Food Security” …The paper proposes a licensing model that allows farmers to benefit from the datasets to which they contribute. The license supports SME data collectors, who need sophisticated legal tools; contributors, who need engagement, privacy, control, and benefit sharing; and consumers who need open access….(More)“.

Teaching machines to understand – and summarize – text


 and  in The Conversation: “We humans are swamped with text. It’s not just news and other timely information: Regular people are drowning in legal documents. The problem is so bad we mostly ignore it. Every time a person uses a store’s loyalty rewards card or connects to an online service, his or her activities are governed by the equivalent of hundreds of pages of legalese. Most people pay no attention to these massive documents, often labeled “terms of service,” “user agreement” or “privacy policy.”

These are just part of a much wider societal problem of information overload. There is so much data stored – exabytes of it, as much stored as has ever been spoken by people in all of human history – that it’s humanly impossible to read and interpret everything. Often, we narrow down our pool of information by choosing particular topics or issues to pay attention to. But it’s important to actually know the meaning and contents of the legal documents that govern how our data is stored and who can see it.

As computer science researchers, we are working on ways artificial intelligence algorithms could digest these massive texts and extract their meaning, presenting it in terms regular people can understand….

Examining privacy policies

A modern internet-enabled life today more or less requires trusting for-profit companies with private information (like physical and email addresses, credit card numbers and bank account details) and personal data (photos and videos, email messages and location information).

These companies’ cloud-based systems typically keep multiple copies of users’ data as part of backup plans to prevent service outages. That means there are more potential targets – each data center must be securely protected both physically and electronically. Of course, internet companies recognize customers’ concerns and employ security teams to protect users’ data. But the specific and detailed legal obligations they undertake to do that are found in their impenetrable privacy policies. No regular human – and perhaps even no single attorney – can truly understand them.

In our study, we ask computers to summarize the terms and conditions regular users say they agree to when they click “Accept” or “Agree” buttons for online services. We downloaded the publicly available privacy policies of various internet companies, including Amazon AWS, Facebook, Google, HP, Oracle, PayPal, Salesforce, Snapchat, Twitter and WhatsApp….

Our software examines the text and uses information extraction techniques to identify key information specifying the legal rights, obligations and prohibitions identified in the document. It also uses linguistic analysis to identify whether each rule applies to the service provider, the user or a third-party entity, such as advertisers and marketing companies. Then it presents that information in clear, direct, human-readable statements….(More)”

Artificial intelligence can predict which congressional bills will pass


Other algorithms have predicted whether a bill will survive a congressional committee, or whether the Senate or House of Representatives will vote to approve it—all with varying degrees of success. But John Nay, a computer scientist and co-founder of Skopos Labs, a Nashville-based AI company focused on studying policymaking, wanted to take things one step further. He wanted to predict whether an introduced bill would make it all the way through both chambers—and precisely what its chances were.

Nay started with data on the 103rd Congress (1993–1995) through the 113th Congress (2013–2015), downloaded from a legislation-tracking website call GovTrack. This included the full text of the bills, plus a set of variables, including the number of co-sponsors, the month the bill was introduced, and whether the sponsor was in the majority party of their chamber. Using data on Congresses 103 through 106, he trained machine-learning algorithms—programs that find patterns on their own—to associate bills’ text and contextual variables with their outcomes. He then predicted how each bill would do in the 107th Congress. Then, he trained his algorithms on Congresses 103 through 107 to predict the 108th Congress, and so on.

Nay’s most complex machine-learning algorithm combined several parts. The first part analyzed the language in the bill. It interpreted the meaning of words by how they were embedded in surrounding words. For example, it might see the phrase “obtain a loan for education” and assume “loan” has something to do with “obtain” and “education.” A word’s meaning was then represented as a string of numbers describing its relation to other words. The algorithm combined these numbers to assign each sentence a meaning. Then, it found links between the meanings of sentences and the success of bills that contained them. Three other algorithms found connections between contextual data and bill success. Finally, an umbrella algorithm used the results from those four algorithms to predict what would happen…. his program scored about 65% better than simply guessing that a bill wouldn’t pass, Nay reported last month in PLOS ONE…(More).

Why blockchain could be your next form of ID as a world citizen


 at TechRepublic: “Blockchain is moving from banking to the refugee crisis, as Microsoft and Accenture on Monday announced a partnership to use the technology to provide a legal form of identification for 1.1 billion people worldwide as part of the global public-private partnership ID2020.

The two tech giants developed a prototype that taps Accenture’s blockchain capabilities and runs on Microsoft Azure. The tech tool uses a person’s biometric data, such as a fingerprint or iris scan, to unlock the record-keeping blockchain technology and create a legal ID. This will allow refugees to have a personal identity record they can access from an app on a smartphone to receive assistance at border crossings, or to access basic services such as healthcare, according to a press release.

The prototype is designed so that personally identifiable information (PII) always exists “off chain,” and is not stored in a centralized system. Citizens use their biometric data to access their information, and chose when to share it—preventing the system from being accessed by tyrannical governments that refugees are fleeing from, as ZDNet noted.

Accenture’s platform is currently used in the Biometric Identity Management System operated by the United Nations High Commissioner for Refugees, which has enrolled more than 1.3 million refugees in 29 nations across Asia, Africa, and the Caribbean. The system is predicted to support more than 7 million refugees from 75 countries by 2020, the press release noted.

“People without a documented identity suffer by being excluded from modern society,” said David Treat, a managing director in Accenture’s global blockchain business, in the press release. “Our prototype is personal, private and portable, empowering individuals to access and share appropriate information when convenient and without the worry of using or losing paper documentation.”

ID is key for accessing education, healthcare, voting, banking, housing, and other family benefits, the press release noted. ID2020’s goal is to create a secure, established digital ID system for all citizens worldwide….

Blockchain will likely play an increasing role in both identification and security moving forward, especially as it relates to the Internet of Things (IoT). For example, Telstra, an Australian telecommunications company, is currently experimenting with a combination of blockchain and biometric security for its smart home products, ZDNet reported….(More)”.

AI software created for drones monitors wild animals and poachers


Springwise: “Artificial intelligence software installed into drones is to be used by US tech company Neurala to help protect endangered species from poachers. Working with the region’s Lingbergh Foundation, Neurala is currently helping operations in South Africa, Malawi and Zimbabwe and have had requests from Botswana, Mozambique and Zambia for assistance with combatting poaching.

The software is designed to monitor video as it is streamed back to researchers from unmanned drones that can fly for up to five hours, identifying animals, vehicles and poachers in real time without any human input. It can then alert rangers via the mobile command center if anything out of the ordinary is detected. The software can analyze regular or infrared footage, and therefore works with video taken day or night.

The Lindbergh Foundation will be deploying the technology as part of operation Air Shepherd, which is aimed at protecting elephants and rhinos in Southern Africa from poachers. According to the Foundation, elephants and rhinos are at risk of being extinct in just 10 years if current poaching rates continue, and has logged 5,000 hours of drone flight time over the course of 4,000 missions to date.

The use of drones within business models is proving popular, with recent innovations including a drone painting systemthat created crowdfunded murals and two Swiss hospitals that used a drone to deliver lab samples between them….(More)”.

LSE launches crowdsourcing project inspiring millennials to shape Brexit


LSE Press Release: “A crowdsourcing project inspiring millennials in Britain and the EU to help shape the upcoming Brexit negotiations is being launched by the London School of Economics and Political Science (LSE) this week.

The social media-based project, which hopes to engage 3000 millennials aged 35 and under, kicks off on 23 June, the first anniversary of the life-changing vote to take Britain out of the EU.

One of the Generation Brexit project leaders, Dr Jennifer Jackson-Preece from LSE’s European Institute, said the online platform would give a voice to British and European millennials on the future of Europe in the Brexit negotiations and beyond.

She said: “We’re going to invite millennials from across the UK and Europe to debate, decide and draft policy proposals that will be sent to parliaments in Westminster and Strasbourg during the negotiations.”

Another project leader, Dr Roch Dunin-Wąsowicz, said the pan-European project would seek views from a whole cross section of millennials, including Leavers, Remainers, left and right-wingers, European federalists and nationalists.

“We want to come up with millennial proposals for a mutually beneficial relationship, reflecting the diverse political, cultural, religious and economic backgrounds in the UK and EU.

“We are especially keen to engage the forgotten, the apolitical and the apathetic – for whom Brexit has become a moment of political awakening,” he said.

Generation Brexit follows on the heels of LSE’s Constitution UK crowdsourcing project in 2015, which broke new ground in galvanising people around the country to help shape Britain’s first constitution. The 10-week internet project signed up 1500 people from all corners of the UK to debate how the country should be governed.

Dr Manmit Bhambra, also working on the project, said the success of the Constitution UK platform had laid the foundation for Generation Brexit, with LSE hoping to double the numbers and sign up 3000 participants, split equally between Britain and Europe.

The project can be accessed at www.generationbrexit.org and all updates will be available on Twitter @genbrexit & @lsebrexitvote with the hashtag #GenBrexit, and on facebook.com/GenBrexit… (More)”.

Remix, Slang and Memes: A New Collection Documents Web Culture


 at the Library of Congress: “…just announced the release of the Web Cultures Web Archive Collection, a representative sampling of websites documenting the creation and sharing of emergent cultural traditions on the web.

Why is this important? Increasingly, people take to their smart phones, tablets and laptops to enact much of their lives through creative communication, making the web a predominant place to share folklore. It is where a significant portion of the historical record is now being written.

Archived from the web starting in 2014, the new—and growing—collection of collaborative cultural creation includes reaction GIFs (animated images, often bodies in motion, used online as responses or reactions to previous posts in a communication thread); image macros (photographic images on which a funny caption is superimposed); and memes (in this context, internet phenomena).

Because the collection aims to document online communities that have established, shaped and disseminated communication tropes and themes, it also includes sites that capture icon-based communications, such as emoji, and those that establish or define vernacular language. Examples of these include “Leet” and “Lolspeak,” two examples of written English language that derive from internet usages. Leet emerged from 1980s software piracy communities, referring to “elite” code wranglers. Lolspeak primarily features in memes and carries collective meaning as the form of English that cats might use.

Some sites represent the DIY (do-it-yourself) movements of crafting and making—for example, Instructables. Still others focus on the distribution and discussion of digital “urban legends” and lore, such as Creepypasta, or vernacular creative forms, such as fan fiction.

The project is a contemporary manifestation of the AFC’s mission to document traditional cultural forms and practices, and results from the collaborative work between the AFC and those steeped in digital culture, both scholars and enthusiasts….(More)”.

Does democracy cause innovation? An empirical test of the popper hypothesis


Yanyan GaoLeizhen ZangAntoine Roth, and Puqu Wang in Research Policy: “Democratic countries produce higher levels of innovation than autocratic ones, but does democratization itself lead to innovation growth either in the short or in the long run? The existing literature has extensively examined the relationship between democracy and growth but seldom explored the effect of democracy on innovation, which might be an important channel through which democracy contributes to economic growth. This article aims to fill this gap and contribute to the long-standing debate on the relationship between democracy and innovation by offering empirical evidence based on a data set covering 156 countries between 1964 and 2010. The results from the difference-in-differences method show that democracy itself has no direct positive effect on innovation measured with patent counts, patent citations and patent originality….(More)”.