Proposal for an International Taxonomy on the Various Forms of the ‘Right to Be Forgotten’: A Study on the Convergence of Norms


Paper by W. Gregory Voss and Céline Castets-Renard: “The term “right to be forgotten” is used today to represent a multitude of rights, and this fact causes difficulties in interpretation, analysis, and comprehension of such rights. These rights have become of utmost importance due to the increased risks to the privacy of individuals on the Internet, where social media, blogs, fora, and other outlets have entered into common use as part of human expression. Search engines, as Internet intermediaries, have been enrolled to assist in the attempt to regulate the Internet, and the rights falling under the moniker of the “right to be forgotten,” without truly knowing the extent of the related rights. In part to alleviate such problems, and focusing on digital technology and media, this paper proposes a taxonomy to identify various rights from different countries, which today are often regrouped under the banner “right to be forgotten,” and to do so in an understandable and coherent way. As an integral part of this exercise, this study aims to measure the extent to which there is a convergence of legal rules internationally in order to regulate private life on the Internet and to elucidate the impact that the important Google Spain “right to be forgotten” ruling of the Court of Justice of the European Union has had on law in other jurisdictions on this matter.

This paper will first introduce the definition and context of the “right to be forgotten.” Second, it will trace some of the sources of the rights discussed around the world to survey various forms of the “right to be forgotten” internationally and propose a taxonomy. This work will allow for a determination on whether there is a convergence of norms regarding the “right to be forgotten” and, more generally, with respect to privacy and personal data protection laws. Finally, this paper will provide certain criteria for the relevant rights and organize them into a proposed analytical grid to establish more precisely the proposed taxonomy of the “right to be forgotten” for the use of scholars, practitioners, policymakers, and students alike….(More)”.

How an AI Utopia Would Work


Sami Mahroum at Project Syndicate: “…It is more than 500 years since Sir Thomas More found inspiration for the “Kingdom of Utopia” while strolling the streets of Antwerp. So, when I traveled there from Dubai in May to speak about artificial intelligence (AI), I couldn’t help but draw parallels to Raphael Hythloday, the character in Utopia who regales sixteenth-century Englanders with tales of a better world.

As home to the world’s first Minister of AI, as well as museumsacademies, and foundations dedicated to studying the future, Dubai is on its own Hythloday-esque voyage. Whereas Europe, in general, has grown increasingly anxious about technological threats to employment, the United Arab Emirates has enthusiastically embraced the labor-saving potential of AI and automation.

There are practical reasons for this. The ratio of indigenous-to-foreign labor in the Gulf states is highly imbalanced, ranging from a high of 67% in Saudi Arabia to a low of 11% in the UAE. And because the region’s desert environment cannot support further population growth, the prospect of replacing people with machines has become increasingly attractive.

But there is also a deeper cultural difference between the two regions. Unlike Western Europe, the birthplace of both the Industrial Revolution and the “Protestant work ethic,” Arab societies generally do not “live to work,” but rather “work to live,” placing a greater value on leisure time. Such attitudes are not particularly compatible with economic systems that require squeezing ever more productivity out of labor, but they are well suited for an age of AI and automation….

Fortunately, AI and data-driven innovation could offer a way forward. In what could be perceived as a kind of AI utopia, the paradox of a bigger state with a smaller budget could be reconciled, because the government would have the tools to expand public goods and services at a very small cost.

The biggest hurdle would be cultural: As early as 1948, the German philosopher Joseph Pieper warned against the “proletarianization” of people and called for leisure to be the basis for culture. Westerners would have to abandon their obsession with the work ethic, as well as their deep-seated resentment toward “free riders.” They would have to start differentiating between work that is necessary for a dignified existence, and work that is geared toward amassing wealth and achieving status. The former could potentially be all but eliminated.

With the right mindset, all societies could start to forge a new AI-driven social contract, wherein the state would capture a larger share of the return on assets, and distribute the surplus generated by AI and automation to residents. Publicly-owned machines would produce a wide range of goods and services, from generic drugs, food, clothes, and housing, to basic research, security, and transportation….(More)”.

How I Learned to Stop Worrying and Love the GDPR


Ariane Adam at DataStewards.net: “The General Data Protection Regulation (GDPR) was approved by the EU Parliament on 14 April 2016 and came into force on 25 May 2018….

The coming into force of this important regulation has created confusion and concern about penalties, particularly in the private sector….There is also apprehension about how the GDPR will affect the opening and sharing of valuable databases. At a time when open data is increasingly shaping the choices we make, from finding the fastest route home to choosing the best medical or education provider, misinformation about data protection principles leads to concerns that ‘privacy’ will be used as a smokescreen to not publish important information. Allaying the concerns of private organisations and businesses in this area is particularly important as often the datasets that most matter, and that could have the most impact if they were open, do not belong to governments.

Looking at the regulation and its effects about one year on, this paper advances a positive case for the GDPR and aims to demonstrate that a proper understanding of its underlying principles can not only assist in promoting consumer confidence and therefore business growth, but also enable organisations to safely open and share important and valuable datasets….(More)”.

Crosscope


Crosscope is revolutionizing the way practitioners and researchers are leveraging digital pathology to share and solve medical cases.

Since the 1900s cancer diagnosis has been limited to the subjective interpretation of what the pathologist could see under a microscope. To transform the way we perform pathology and cancer research, we are developing new tools to leverage powerful AI & perspectives of medical experts at the same time.

At Crosscope, we are building a place for the convergence of collective intelligence of our massive online medical community and AI. We are commited to developing cutting edge AI tools for better decision support in cancer care. We aim to be the largest database for tagged histopathology images which will contain a lot more information than genomics alone and will be crucial in early diagnosis of cancer….(More)”.

AI Ethics — Too Principled to Fail?


Paper by Brent Mittelstadt: “AI Ethics is now a global topic of discussion in academic and policy circles. At least 63 public-private initiatives have produced statements describing high-level principles, values, and other tenets to guide the ethical development, deployment, and governance of AI. According to recent meta-analyses, AI Ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics.

Despite the initial credibility granted to a principled approach to AI Ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach in the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement….(More)”.

Trusted data and the future of information sharing


 MIT Technology Review: “Data in some form underpins almost every action or process in today’s modern world. Consider that even farming, the world’s oldest industry, is on the verge of a digital revolution, with AI, drones, sensors, and blockchain technology promising to boost efficiencies. The market value of an apple will increasingly reflect not only traditional farming inputs but also some value of modern data, such as weather patterns, soil acidity levels and agri-supply-chain information. By 2022 more than 60% of global GDP will be digitized, according to IDC.

Governments seeking to foster growth in their digital economies need to be more active in encouraging safe data sharing between organizations. Tolerating the sharing of data and stepping in only where security breaches occur is no longer enough. Sharing data across different organizations enables the whole ecosystem to grow and can be a unique source of competitive advantage. But businesses need guidelines and support in how to do this effectively.   

This is how Singapore’s data-sharing worldview has evolved, according to Janil Puthucheary, senior minister of state for communications and information and transport, upon launching the city-state’s new Trusted Data Sharing Framework in June 2019.

The Framework, a product of consultations between Singapore’s Infocomm Media Development Authority (IMDA), its Personal Data Protection Commission (PDPC), and industry players, is intended to create a common data-sharing language for relevant stakeholders. Specifically, it addresses four common categories of concerns with data sharing: how to formulate an overall data-sharing strategy, legal and regulatory considerations, technical and organizational considerations, and the actual operationalizing of data sharing.

For instance, companies often have trouble assessing the value of their own data, a necessary first step before sharing should even be considered. The framework describes the three general approaches used: market-, cost-, and income-based. The legal and regulatory section details when businesses can, among other things, seek exemptions from Singapore’s Personal Data Protection Act.

The technical and organizational chapter includes details on governance, infrastructure security, and risk management. Finally, the section on operational aspects of data sharing includes guidelines for when it is appropriate to use shared data for a secondary purpose or not….(More)”.

Digital tools for Citizens’ Assemblies


Report by Alex Parsons: “… result of mySociety’s research into how digital tools can be used as part of the process of a Citizens’ Assembly.

We reviewed how Citizens’ Assemblies to date have approached technology, and explored where lessons can be learned from other deliberative or consultative activities.

While there is no unified Citizens’ Assembly digital service, there are a number of different tools that can be used to enhance the process – and that most of these are generic and well-tested products and services. We also tried to identify where innovative tools could be put to new uses, while always bearing in mind the core importance of the in-person deliberative nature of assemblies….(More)”.

Foundations of Information Ethics


Book by John T. F. Burgess and Emily J. M. Knox: “As discussions about the roles played by information in economic, political, and social arenas continue to evolve, the need for an intellectual primer on information ethics that also functions as a solid working casebook for LIS students and professionals has never been more urgent. This text, written by a stellar group of ethics scholars and contributors from around the globe, expertly fills that need. Organized into twelve chapters, making it ideal for use by instructors, this volume from editors Burgess and Knox

  • thoroughly covers principles and concepts in information ethics, as well as the history of ethics in the information professions;
  • examines human rights, information access, privacy, discourse, intellectual property, censorship, data and cybersecurity ethics, intercultural information ethics, and global digital citizenship and responsibility;
  • synthesizes the philosophical underpinnings of these key subjects with abundant primary source material to provide historical context along with timely and relevant case studies;
  • features contributions from John M. Budd, Paul T. Jaeger, Rachel Fischer, Margaret Zimmerman, Kathrine A. Henderson, Peter Darch, Michael Zimmer, and Masooda Bashir, among others; and
  • offers a special concluding chapter by Amelia Gibson that explores emerging issues in information ethics, including discussions ranging from the ethics of social media and social movements to AI decision making…(More)”.

How credit unions could help people make the most of personal data


Dylan Walsh at MIT Sloan: “In May of 2018, the EU adopted the General Data Protection Regulation, referred to by The New York Timesas “the world’s toughest rules to protect people’s online data.” Among its many safeguards, the GDPR gave individuals ownership of their personal data and thereby restricted its collection and use by businesses.

“That’s a good first start,” said Alex Pentland, a co-creator of the MIT Media Lab who played a foundational role in the development of the GDPR. “But ownership isn’t enough. Simply having the rights to your data doesn’t allow you to do much with it.” In response to this shortcoming, Pentland and his team have proposed the establishment of data cooperatives.

The idea is conceptually straightforward: Individuals would pool their personal data in a single institution — just as they pool money in banks — and that institution would both protect the data and put it to use. Pentland and his team suggest credit unions as one type of organization that could fill this role. And while companies would need to request permission to use consumer data, consumers themselves could request analytic insights from the cooperative. Lyft drivers, for instance, might compare their respective incomes across routes, and ride-share passengers could compare how much they pay relative to other cooperative members….

Several states have now asked credit unions to look into the idea of data cooperatives, but the model has yet to gain a foothold. “Credit unions are conservative,” Pentland said. But assuming the idea gains traction, the infrastructure won’t be difficult to build. Technology exists to automatically record and organize all the data that we give to companies; and credit unions, which have 100 million members nationwide, possess charters readymade to take on data management….(More)”.

Mobile phone data’s potential for informing infrastructure planning in developing countries


Paper by Hadrien Salat, Zbigniew Smoreda, and Markus Schläpfer: “High quality census data are not always available in developing countries. Instead, mobile phone data are becoming a go to proxy to evaluate population density, activity and social characteristics. They offer additional advantages for infrastructure planning such as being updated in real-time, including mobility information and recording temporary visitors’ activity. We combine various data sets from Senegal to evaluate mobile phone data’s potential to replace insufficient census data for infrastructure planning in developing countries. As an applied case, we test their ability at predicting accurately domestic electricity consumption. We show that, contrary to common belief, average mobile phone activity is not well correlated with population density. However, it can provide better electricity consumption estimates than basic census data. More importantly, we successfully use curve and network clustering techniques to enhance the accuracy of the predictions, to recover good population mapping potential and to reduce the collection of informative data for planning to substantially smaller samples….(More)”.