Maria Bottis and George Bouchagiar in the Open Journal of Philosophy: “Any firm today may, at little or no cost, build its own infrastructure to process personal data for commercial, economic, political, technological or any other purposes. Society has, therefore, turned into a privacy-unfriendly environment. The processing of personal data is essential for multiple economically and socially useful purposes, such as health care, education or terrorism prevention. But firms view personal data as a commodity, as a valuable asset, and heavily invest in processing for private gains. This article studies the potential to subject personal data to trade secret rules, so as to ensure the users’ control over their data without limiting the data’s free movement, and examines some positive scenarios of attributing commercial value to personal data….(More)”.
Against the Dehumanisation of Decision-Making – Algorithmic Decisions at the Crossroads of Intellectual Property, Data Protection, and Freedom of Information
Paper by Guido Noto La Diega: “Nowadays algorithms can decide if one can get a loan, is allowed to cross a border, or must go to prison. Artificial intelligence techniques (natural language processing and machine learning in the first place) enable private and public decision-makers to analyse big data in order to build profiles, which are used to make decisions in an automated way.
This work presents ten arguments against algorithmic decision-making. These revolve around the concepts of ubiquitous discretionary interpretation, holistic intuition, algorithmic bias, the three black boxes, psychology of conformity, power of sanctions, civilising force of hypocrisy, pluralism, empathy, and technocracy.
The lack of transparency of the algorithmic decision-making process does not stem merely from the characteristics of the relevant techniques used, which can make it impossible to access the rationale of the decision. It depends also on the abuse of and overlap between intellectual property rights (the “legal black box”). In the US, nearly half a million patented inventions concern algorithms; more than 67% of the algorithm-related patents were issued over the last ten years and the trend is increasing.
To counter the increased monopolisation of algorithms by means of intellectual property rights (with trade secrets leading the way), this paper presents three legal routes that enable citizens to ‘open’ the algorithms.
First, copyright and patent exceptions, as well as trade secrets are discussed.
Second, the GDPR is critically assessed. In principle, data controllers are not allowed to use algorithms to take decisions that have legal effects on the data subject’s life or similarly significantly affect them. However, when they are allowed to do so, the data subject still has the right to obtain human intervention, to express their point of view, as well as to contest the decision. Additionally, the data controller shall provide meaningful information about the logic involved in the algorithmic decision.
Third, this paper critically analyses the first known case of a court using the access right under the freedom of information regime to grant an injunction to release the source code of the computer program that implements an algorithm.
Only an integrated approach – which takes into account intellectual property, data protection, and freedom of information – may provide the citizen affected by an algorithmic decision of an effective remedy as required by the Charter of Fundamental Rights of the EU and the European Convention on Human Rights….(More)”.
Big Data and AI – A transformational shift for government: So, what next for research?
Irina Pencheva, Marc Esteve and Slava Jenkin Mikhaylov in Public Policy and Administration: “Big Data and artificial intelligence will have a profound transformational impact on governments around the world. Thus, it is important for scholars to provide a useful analysis on the topic to public managers and policymakers. This study offers an in-depth review of the Policy and Administration literature on the role of Big Data and advanced analytics in the public sector. It provides an overview of the key themes in the research field, namely the application and benefits of Big Data throughout the policy process, and challenges to its adoption and the resulting implications for the public sector. It is argued that research on the subject is still nascent and more should be done to ensure that the theory adds real value to practitioners. A critical assessment of the strengths and limitations of the existing literature is developed, and a future research agenda to address these gaps and enrich our understanding of the topic is proposed…(More)”.
Data Protection and e-Privacy: From Spam and Cookies to Big Data, Machine Learning and Profiling
Chapter by Lilian Edwards in L Edwards ed Law, Policy and the Internet (Hart , 2018): “In this chapter, I examine in detail how data subjects are tracked, profiled and targeted by their activities on line and, increasingly, in the “offline” world as well. Tracking is part of both commercial and state surveillance, but in this chapter I concentrate on the former. The European law relating to spam, cookies, online behavioural advertising (OBA), machine learning (ML) and the Internet of Things (IoT) is examined in detail, using both the GDPR and the forthcoming draft ePrivacy Regulation. The chapter concludes by examining both code and law solutions which might find a way forward to protect user privacy and still enable innovation, by looking to paradigms not based around consent, and less likely to rely on a “transparency fallacy”. Particular attention is drawn to the new work around Personal Data Containers (PDCs) and distributed ML analytics….(More)”.
Latin America is fighting corruption by opening up government data
Anoush Darabi in apolitical: “Hardly a country in Latin America has been untouched by corruption scandals; this was just one of the more bizarre episodes. In response, using a variety of open online platforms, both city and national governments are working to lift the lid on government activity, finding new ways to tackle corruption with technology….
In Buenos Aires, government is dealing with the problem by making the details of all its public works projects completely transparent. With BA Obras, an online platform, the city maps projects across the city, and lists detailed information on their cost, progress towards completion and the names of the contractors.
“We allocate an enormous amount of money,” said Alvaro Herrero, Under Secretary for Strategic Management and Institutional Quality for the government of Buenos Aires, who helped to build the tool. “We need to be accountable to citizens in terms of what are we doing with that money.”
The portal is designed to be accessible to the average user. Citizens can filter the map to focus on their neighbourhood, revealing information on existing projects with the click of a mouse.
“A journalist called our communications team a couple of weeks ago,” said Herrero. “He said: ‘I want all the information on all the infrastructure projects that the government has, and I want the documentation.’ Our guy’s answer was, ‘OK, I will send you all the information in ten seconds.’ All he had to do was send a link to the platform.”
Since launching in October 2017 with 80 public works projects, the platform now features over 850. It has had 75,000 unique views, the majority coming in the month after launching.
Making people aware and encouraging them to use it is key. “The main challenge is not the platform itself, but getting residents to use it,” said Herrero. “We’re still in that process.”
Brazil’s public spending checkers
Brazil is using big data analysis to scrutinise its spending via its Public Expenditure Observatory (ODP).
The ODP was founded in 2008 to help monitor spending across government departments systematically. In such a large country, spending data is difficult to pull together, and its volume makes it difficult to analyse. The ODP pulls together disparate information from government databases across the country into a central location, puts it into a consistent format and analyses it for inconsistency. Alongside analysis, the ODP also makes the data public.
For example, in 2010 the ODP analysed expenses made on credit cards by federal government officers. They discovered that 11% of all transactions that year were suspicious, requiring further investigation. After the data was published, credit card expenditure dropped by 25%….(More)”.
Using Satellite Imagery to Revolutionize Creation of Tax Maps and Local Revenue Collection
World Bank Policy Research Paper by Daniel Ayalew Ali, Klaus Deininger and Michael Wild: “The technical complexity of ensuring that tax rolls are complete and valuations current is often perceived as a major barrier to bringing in more property tax revenues in developing countries.
This paper shows how high-resolution satellite imagery makes it possible to assess the completeness of existing tax maps by estimating built-up areas based on building heights and footprints. Together with information on sales prices from the land registry, targeted surveys, and routine statistical data, this makes it possible to use mass valuation procedures to generate tax maps. The example of Kigali illustrates the reliability of the method and the potentially far-reaching revenue impacts. Estimates show that heightened compliance and a move to a 1 percent ad valorem tax would yield a tenfold increase in revenue from public land….(More)”.
Data for Good: Unlocking Privately-Held Data to the Benefit of the Many
Alberto Alemanno in the European Journal of Risk Regulation: “It is almost a truism to argue that data holds a great promise of transformative resources for social good, by helping to address a complex range of societal issues, ranging from saving lives in the aftermath of a natural disaster to predicting teen suicides. Yet it is not public authorities who hold this real-time data, but private entities, such as mobile network operators and business card companies, and – with even greater detail – tech firms such as Google through its globally-dominant search engine, and, in particular, social media platforms, such as Facebook and Twitter. Besides a few isolated and self-proclaimed ‘data philanthropy’ initiatives and other corporate data-sharing collaborations, data-rich companies have historically shown resistance to not only share this data for the public good, but also to identify its inherent social, non-commercial benefit. How to explain to citizens across the world that their own data – which has been aggressively harvested over time – can’t be used, and not even in emergency situations? Responding to this unsettling question entails a fascinating research journey for anyone interested in how the promises of big data could deliver for society as a whole. In the absence of a plausible solution, the number of societal problems that won’t be solved unless firms like Facebook, Google and Apple start coughing up more data-based evidence will increase exponentially, as well as societal rejection of their underlying business models.
This article identifies the major challenges of unlocking private-held data to the benefit of society and sketches a research agenda for scholars interested in collaborative and regulatory solutions aimed at unlocking privately-held data for good….(More)”.
Big Data against Child Obesity
European Commission: “Childhood and adolescent obesity is a major global and European public health problem. Currently, public actions are detached from local needs, mostly including indiscriminate blanket policies and single-element strategies, limiting their efficacy and effectiveness. The need for community-targeted actions has long been obvious, but the lack of monitoring and evaluation framework and the methodological inability to objectively quantify the local community characteristics, in a reasonable timeframe, has hindered that.
Big Data based Platform
Technological achievements in mobile and wearable electronics and Big Data infrastructures allow the engagement of European citizens in the data collection process, allowing us to reshape policies at a regional, national and European level. In BigO, that will be facilitated through the development of a platform, allowing the quantification of behavioural community patterns through Big Data provided by wearables and eHealth- devices.
Estimate child obesity through community data
BigO has set detailed scientific, technological, validation and business objectives in order to be able to build a system that collects Big Data on children’s behaviour and helps planning health policies against obesity. In addition, during the project, BigO will reach out to more than 25.000 school and age-matched obese children and adolescents as sources for community data. Comprehensive models of the obesity prevalence dependence matrix will be created, allowing the data-driven effectiveness predictions about specific policies on a community and the real-time monitoring of the population response, supported by powerful real-time data visualisations….(More)
Data Governance in the Digital Age
Centre for International Governance Innovation: “Data is being hailed as “the new oil.” The analogy seems appropriate given the growing amount of data being collected, and the advances made in its gathering, storage, manipulation and use for commercial, social and political purposes.
Big data and its application in artificial intelligence, for example, promises to transform the way we live and work — and will generate considerable wealth in the process. But data’s transformative nature also raises important questions around how the benefits are shared, privacy, public security, openness and democracy, and the institutions that will govern the data revolution.
The delicate interplay between these considerations means that they have to be treated jointly, and at every level of the governance process, from local communities to the international arena. This series of essays by leading scholars and practitioners, which is also published as a special report, will explore topics including the rationale for a data strategy, the role of a data strategy for Canadian industries, and policy considerations for domestic and international data governance…
RATIONALE OF A DATA STRATEGY
- Considerations for Canada’s National Data Strategy
- The Economics of Data: Implications for the Data-driven Economy
- The Government’s Role in Constructing the Data-driven Economy
- Canadian Network Sovereignty: A Strategy for Twenty-First-Century National Infrastructure Building
- VIDEO: Considerations for Canada’s National Data Strategy
- VIDEO: Canada Needs a National Data Strategy
- VIDEO: The Economics of Data: Implications for the Data-driven Economy
THE ROLE OF A DATA STRATEGY FOR CANADIAN INDUSTRIES
- Treasure of the Commons: Global Leadership through Health Data
- Monetizing Smart Cities: Framing the Debate
- Big Data: The Canadian Opportunity
- VIDEO: Treasure of the Commons: Global Leadership Through Health Data
- VIDEO: Big Data: The Canadian Opportunity
BALANCING PRIVACY AND COMMERCIAL VALUES
- Preventing Big Data Discrimination in Canada: Addressing Design, Consent and Sovereignty Challenges
- Data and the Future of Growth: The Need for Strategic Data Policy
- Crypto Agility Is a Must-Have for Data Encryption Standards
DOMESTIC POLICY FOR DATA GOVERNANCE
- Ungoverned Space: How Surveillance Capitalism and AI Undermine Democracy
- Governance Vacuums and How Code Is Becoming Law
- Measuring the Economy in an Increasingly Digitalized World: Are Statistics Up to the Task?
- VIDEO: Governance Vacuums and How Code Is Becoming Law
- VIDEO: How Surveillance Capitalism Undermines Democracy
INTERNATIONAL POLICY CONSIDERATIONS
- Data Libera? Canada’s Data Strategy and the Law of the Sea
- Data Rules in Modern Trade Agreements: Toward Reconciling an Open Internet with Privacy and Security Safeguards
- Data Minefield? How AI Is Prodding Governments to Rethink Trade in Data
- VIDEO: Data Rules in Modern Trade Agreements
- Screen Time, the Brain, Privacy and Mental Health
EPILOGUE
How the Math Men Overthrew the Mad Men
Ken Auletta in the New Yorker: “Once, Mad Men ruled advertising. They’ve now been eclipsed by Math Men—the engineers and data scientists whose province is machines, algorithms, pureed data, and artificial intelligence. Yet Math Men are beleaguered, as Mark Zuckerberg demonstrated when he humbled himself before Congress, in April. Math Men’s adoration of data—coupled with their truculence and an arrogant conviction that their “science” is nearly flawless—has aroused government anger, much as Microsoft did two decades ago.
The power of Math Men is awesome. Google and Facebook each has a market value exceeding the combined value of the six largest advertising and marketing holding companies. Together, they claim six out of every ten dollars spent on digital advertising, and nine out of ten new digital ad dollars. They have become more dominant in what is estimated to be an up to two-trillion-dollar annual global advertising and marketing business. Facebook alone generates more ad dollars than all of America’s newspapers, and Google has twice the ad revenues of Facebook.
In the advertising world, Big Data is the Holy Grail, because it enables marketers to target messages to individuals rather than general groups, creating what’s called addressable advertising. And only the digital giants possess state-of-the-art Big Data. “The game is no longer about sending you a mail order catalogue or even about targeting online advertising,” Shoshana Zuboff, a professor of business administration at the Harvard Business School, wrote on faz.net, in 2016. “The game is selling access to the real-time flow of your daily life—your reality—in order to directly influence and modify your behavior for profit.” Success at this “game” flows to those with the “ability to predict the future—specifically the future of behavior,” Zuboff writes. She dubs this “surveillance capitalism.”
However, to thrash just Facebook and Google is to miss the larger truth: everyone in advertising strives to eliminate risk by perfecting targeting data. Protecting privacy is not foremost among the concerns of marketers; protecting and expanding their business is. The business model adopted by ad agencies and their clients parallels Facebook and Google’s. Each aims to massage data to better identify potential customers. Each aims to influence consumer behavior. To appreciate how alike their aims are, sit in an agency or client marketing meeting and you will hear wails about Facebook and Google’s “walled garden,” their unwillingness to share data on their users. When Facebook or Google counter that they must protect “the privacy” of their users, advertisers cry foul: You’re using the data to target ads we paid for—why won’t you share it, so that we can use it in other ad campaigns?…(More)”