Paper by Sam Grabus and Jane Greenberg: “Over the last twenty years, a wide variety of resources have been developed to address the rights and licensing problems inherent with contemporary data sharing practices. The landscape of developments is this area is increasingly confusing and difficult to navigate, due to the complexity of intellectual property and ethics issues associated with sharing sensitive data. This paper seeks to address this challenge, examining the landscape and presenting a Version 1.0 directory of resources. A multi-method study was pursued, with an environmental scan examining 20 resources, resulting in three high-level categories: standards, tools, and community initiatives; and a content analysis revealing the subcategories of rights, licensing, metadata & ontologies. A timeline confirms a shift in licensing standardization priorities from open data to more nuanced and technologically robust solutions, over time, to accommodate for more sensitive data types. This paper reports on the research undertaking, and comments on the potential for using license-specific metadata supplements and developing data-centric rights and licensing ontologies….(More)”.
The Lives and After Lives of Data
Paper by Christine L. Borgman: “The most elusive term in data science is ‘data.’ While often treated as objects to be computed upon, data is a theory-laden concept with a long history. Data exist within knowledge infrastructures that govern how they are created, managed, and interpreted. By comparing models of data life cycles, implicit assumptions about data become apparent. In linear models, data pass through stages from beginning to end of life, which suggest that data can be recreated as needed. Cyclical models, in which data flow in a virtuous circle of uses and reuses, are better suited for irreplaceable observational data that may retain value indefinitely. In astronomy, for example, observations from one generation of telescopes may become calibration and modeling data for the next generation, whether digital sky surveys or glass plates. The value and reusability of data can be enhanced through investments in knowledge infrastructures, especially digital curation and preservation. Determining what data to keep, why, how, and for how long, is the challenge of our day…(More)”.
Urbanism Under Google: Lessons from Sidewalk Toronto
Paper by Ellen P. Goodman and Julia Powles: “Cities around the world are rapidly adopting digital technologies, data analytics, and the trappings of “smart” infrastructure. No company is more ambitious about exploring data flows and seeking to dominate networks of information than Google. In October 2017, Google affiliate Sidewalk Labs embarked on its first prototype smart city in Toronto, Canada, planning a new kind of data-driven urban environment: “the world’s first neighborhood built from the internet up.” Although the vision is for an urban district foregrounding progressive ideals of inclusivity, for the crucial first 18 months of the venture, many of the most consequential features of the project were hidden from view and unavailable for serious scrutiny. The players defied public accountability on questions about data collection and surveillance, governance, privacy, competition, and procurement. Even more basic questions about the use of public space went unanswered: privatized services, land ownership, infrastructure deployment and, in all cases, the question of who is in control. What was hidden in this first stage, and what was revealed, suggest that the imagined smart city may be incompatible with democratic processes, sustained public governance, and the public interest.
This article analyzes the Sidewalk project in Toronto as it took shape in its first phase, prior to the release of the Master Innovation and Development Plan, exploring three major governance challenges posed by the imagined “city of the future”: privatization, platformization, and domination. The significance of this case study applies well beyond Toronto. Google and related companies are modeling future business growth embedded in cities and using projects like the one in Toronto as test beds. What happens in Toronto is designed to be replicated. We conclude with some lessons, highlighting the precarity of civic stewardship and public accountability when cities are confronted with tantalizing visions of privatized urban innovation…(More)”.
AI & the sustainable development goals: The state of play
Report by 2030Vision: “…While the world is making progress in some areas, we are falling behind in delivering the SDGs overall. We need all actors – businesses, governments, academia, multilateral institutions, NGOs, and others – to accelerate and scale their efforts to deliver the SDGs, using every tool at their disposal, including artificial intelligence (AI).
In December 2017, 2030Vision published its first report, Uniting to Deliver Technology for the Global Goals, which addressed the role of digital technology – big data, robotics, internet of things, AI, and other technologies – in achieving the SDGs.
In this paper, we focus on AI for the SDGs. AI extends and amplifies the capacity of human beings to understand and solve complex, dynamic, and interconnected systems challenges like the SDGs. Our main objective was to survey the landscape of research and initiatives on AI and the SDGs to identify key themes and questions in need of further exploration. We also reviewed the state of AI and the SDGs in two sectors – food and agriculture and healthcare – to understand if and how AI is being deployed to address the SDGs and the challenges and opportunities in doing so….(More)”.
Why data ownership is the wrong approach to protecting privacy
Article by John B. Morris Jr. and Cameron F. Kerry: “It’s my data.” It’s an idea often expressed about information privacy.
Indeed, in congressional hearings last year, Mark Zuckerberg said multiple times that “people own all of their own content” on Facebook. A survey by Insights Network earlier this year found that 79% of consumers said they want compensation when their data is shared. Musician and tech entrepreneur will.i.am took to the website of The Economist to argue that payment for data is a way to “redress the balance” between individuals and “data monarchs.”
Some policymakers are taking such thinking to heart. Senator John Kennedy (R-LA) introduced a three-page bill, the “Own Your Own Data Act of 2019,” which declares that “each individual owns and has an exclusive property right in the data that individual generates on the internet” and requires that social media companies obtain licenses to use this data. Senators Mark Warner (D-VA) and Josh Hawley (R-MO) are filing legislation to require Facebook, Google, and other large collectors of data to disclose the value of personal data they collect, although the bill would not require payments. In California, Governor Gavin Newsome wants to pursue a “data dividend” designed to “share in the wealth that is created from [people’s] data.”
Treating our data as our property has understandable appeal. It touches what the foundational privacy thinker Alan Westin identified as an essential aspect of privacy, a right “to control, edit, manage, and delete information about [individuals] and decide when, how, and to what extent information is communicated to others.” It expresses the unfairness people feel about an asymmetrical marketplace in which we know little about the data we share but the companies that receive the data can profit by extracting marketable information.
The trouble is, it’s not your data; it’s not their data either. Treating data like it is property fails to recognize either the value that varieties of personal information serve or the abiding interest that individuals have in their personal information even if they choose to “sell” it. Data is not a commodity. It is information. Any system of information rights—whether patents, copyrights, and other intellectual property, or privacy rights—presents some tension with strong interest in the free flow of information that is reflected by the First Amendment. Our personal information is in demand precisely because it has value to others and to society across a myriad of uses.
Treating personal information as property to be licensed or sold may induce people to trade away their privacy rights for very little value while injecting enormous friction into free flow of information. The better way to strengthen privacy is to ensure that individual privacy interests are respected as personal information flows to desirable uses, not to reduce personal data to a commodity….(More)”.
A guide to using artificial intelligence in the public sector
Guidance: “The Government Digital Service (GDS) and the Office for Artificial Intelligence (OAI) have published joint guidance on how to build and use artificial intelligence (AI) in the public sector.
This guidance covers how:
- to assess if using AI will help you meet user needs
- the public sector can best use AI
- to implement AI ethically, fairly and safely…(More)”
How Much Is Data Privacy Worth? A Preliminary Investigation
Paper by Angela G. Winegar and Cass R. Sunstein: “Do consumers value data privacy? How much? In a survey of 2,416 Americans, we find that the median consumer is willing to pay just $5 per month to maintain data privacy (along specified dimensions), but would demand $80 to allow access to personal data. This is a “superendowment effect,” much higher than the 1:2 ratio often found between willingness to pay and willingness to accept. In addition, people demand significantly more money to allow access to personal data when primed that such data includes health-related data than when primed that such data includes demographic data. We analyze reasons for these disparities and offer some notations on their implications for theory and practice.
A general theme is that because of a lack of information and behavioral biases, both willingness to pay and willingness to accept measures are highly unreliable guides to the welfare effects of retaining or giving up data privacy. Gertrude Stein’s comment about Oakland, California may hold for consumer valuations of data privacy: “There is no there there.” For guidance, policymakers should give little or no attention to either of those conventional measures of economic value, at least when steps are not taken to overcome deficits in information and behavioral biases….(More)”.
Clinical Trial Data Transparency and GDPR Compliance: Implications for Data Sharing and Open Innovation
Paper by Timo Minssen, Rajam N. and Marcel Bogers: “Recent EU initiatives and legislations have considerably increased public access to clinical trials data (CTD). These developments are generally much welcomed for the enhancement of science, trust, and open innovation. However, they also raise many questions and concerns, not least at the interface between CTD transparency and other areas of evolving EU law on the protection of trade secrets, intellectual property rights and privacy.
This paper focuses on privacy issues and on the interrelation between developments in transparency and the EU’s new General Data Protection Regulation 2016/679 (GDPR). More specifically, this paper examines: (1) the genesis of EU transparency regulations, including the incidents, developments and policy concerns that have shaped them; (2) the features and implications of the GDPR which are relevant in the context of clinical trials; and (3) the risk for tensions between the GDPR and the policy goals of CTD transparency, including their implications for data sharing and open innovation. Ultimately, we stress that these and other related factors must be carefully considered and addressed to reap the full benefits of CTD transparency….(More)”.
The “Tokenization” of the eParticipation in Public Governance: An Opportunity to Hack Democracy
Chapter by Francisco Luis Benítez Martínez, María Visitación Hurtado Torres and Esteban Romero Frías: “Currently Distributed Ledger Technologies-DLTs, and especially the Blockchain technology, are an excellent opportunity for public institutions to transform the channels of citizen participation and reinvigorate democratic processes. These technologies permit the simplification of processes and make it possible to safely and securely manage the data stored in its records. This guarantees the transmission and public transparency of information, and thus leads to the development of a new citizen governance model by using technology such as a BaaS (Blockchain as a Service) platform. G-Cloud solutions would facilitate a faster deployment in the cities and provide scalability to foster the creation of Smart Citizens within the philosophy of Open Government. The development of an eParticipation model that can configure a tokenizable system of the actions and processes that citizens currently exercise in democratic environments is an opportunity to guarantee greater participation and thus manage more effective local democratic spaces. Therefore, a Blockchain solution in eDemocracy platforms is an exciting new opportunity to claim a new pattern of management amongst the agents that participate in the public sphere….(More)”.
Soon, satellites will be able to watch you everywhere all the time
Christopher Beam at MIT Technology Review: “In 2013, police in Grants Pass, Oregon, got a tip that a man named Curtis W. Croft had been illegally growing marijuana in his backyard. So they checked Google Earth. Indeed, the four-month-old satellite image showed neat rows of plants growing on Croft’s property. The cops raided his place and seized 94 plants.
In 2018, Brazilian police in the state of Amapá used real-time satellite imagery to detect a spot where trees had been ripped out of the ground. When they showed up, they discovered that the site was being used to illegally produce charcoal, and arrested eight people in connection with the scheme.
Chinese government officials have denied or downplayed the existence of Uighur reeducation camps in Xinjiang province, portraying them as “vocational schools.” But human rights activists have used satellite imagery to show that many of the “schools” are surrounded by watchtowers and razor wire.
Every year, commercially available satellite images are becoming sharper and taken more frequently. In 2008, there were 150 Earth observation satellites in orbit; by now there are 768. Satellite companies don’t offer 24-hour real-time surveillance, but if the hype is to be believed, they’re getting close. Privacy advocates warn that innovation in satellite imagery is outpacing the US government’s (to say nothing of the rest of the world’s) ability to regulate the technology. Unless we impose stricter limits now, they say, one day everyone from ad companies to suspicious spouses to terrorist organizations will have access to tools previously reserved for government spy agencies. Which would mean that at any given moment, anyone could be watching anyone else.
The images keep getting clearer
Commercial satellite imagery is currently in a sweet spot: powerful enough to see a car, but not enough to tell the make and model; collected frequently enough for a farmer to keep tabs on crops’ health, but not so often that people could track the comings and goings of a neighbor. This anonymity is deliberate. US federal regulations limit images taken by commercial satellites to a resolution of 25 centimeters, or about the length of a man’s shoe….(More)”.