Technology is threatening our democracy. How do we save it?


MIT Technology Review: “Our newest issue is live today, in which we dive into the many ways that technology is changing politics.

A major shift: In 2013 we emblazoned our cover with the words, “Big Data Will Save Politics.” When we chose that headline, Barack Obama had just won reelection with the help of a crack team of data scientists. The Arab Spring had already cooled into an Arab Winter, but the social-media platforms that had powered the uprisings were still basking in the afterglow. As our editor in chief Gideon Lichfield writes, today, with Cambridge Analytica, fake news, election hacking, and the shrill cacophony that dominates social media, technology feels as likely to destroy politics as to save it.

The political impact: From striking data visualizations that take a close look at the famed “filter bubble” effect that’s blamed for political polarization to an examination of how big data is disrupting the cozy world of political lobbying, we’re analyzing how emerging technologies are shaping the political landscape, eroding trust, and, possibly, becoming a part of the solution….(More)”.

Data-Driven Law: Data Analytics and the New Legal Services


Book by Edward J. Walters: “For increasingly data-savvy clients, lawyers can no longer give “it depends” answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions.

Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as:

  • Mining legal data
  • Computational law
  • Uncovering bias through the use of Big Data
  • Quantifying the quality of legal services
  • Data mining and decision-making
  • Contract analytics and contract standards

In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable….(More)”.

A roadmap for restoring trust in Big Data


Mark Lawler et al in the Lancet: “The fallout from the Cambridge Analytica–Facebook scandal marks a significant inflection point in the public’s trust concerning Big Data. The health-science community must use this crisis-in-confidence to redouble its commitment to talk openly and transparently about benefits and risks and to act decisively to deliver robust effective governance frameworks, under which personal health data can be responsibly used. Activities such as the Innovative Medicines Initiative’s Big Data for Better Outcomes emphasise how a more granular data-driven understanding of human diseases including cancer could underpin innovative therapeutic intervention.
 Health Data Research UK is developing national research expertise and infrastructure to maximise the value of health data science for the National Health Service and ultimately British citizens.
Comprehensive data analytics are crucial to national programmes such as the US Cancer Moonshot, the UK’s 100 000 Genomes project, and other national genomics programmes. Cancer Core Europe, a research partnership between seven leading European oncology centres, has personal data sharing at its core. The Global Alliance for Genomics and Health recently highlighted the need for a global cancer knowledge network to drive evidence-based solutions for a disease that kills more than 8·7 million citizens annually worldwide. These activities risk being fatally undermined by the recent data-harvesting controversy.
We need to restore the public’s trust in data science and emphasise its positive contribution in addressing global health and societal challenges. An opportunity to affirm the value of data science in Europe was afforded by Digital Day 2018, which took place on April 10, 2018, in Brussels, and where European Health Ministers signed a declaration of support to link existing or future genomic databanks across the EU, through the Million European Genomes Alliance.
So how do we address evolving challenges in analysis, sharing, and storage of information, ensure transparency and confidentiality, and restore public trust? We must articulate a clear Social Contract, where citizens (as data donors) are at the heart of decision-making. We need to demonstrate integrity, honesty, and transparency as to what happens to data and what level of control people can, or cannot, expect. We must embed ethical rigour in all our data-driven processes. The Framework for Responsible Sharing of Genomic and Health Related Data represents a practical global approach, promoting effective and ethical sharing and use of research or patient data, while safeguarding individual privacy through secure and accountable data transfer…(More)”.

Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject


Nick Couldry and Ulises Mejias in Television & New Media (TVNM): “...Data colonialism combines the predatory extractive practices of historical colonialism with the abstract quantification methods of computing. Understanding Big Data from the Global South means understanding capitalism’s current dependence on this new type of appropriation that works at every point in space where people or things are attached to today’s infrastructures of connection. The scale of this transformation means that it is premature to map the forms of capitalism that will emerge from it on a global scale. Just as historical colonialism over the long-run provided the essential preconditions for the emergence of industrial capitalism, so over time, we can expect that data colonialism will provide the preconditions for a new stage of capitalism that as yet we can barely imagine, but for which the appropriation of human life through data will be central.

Right now, the priority is not to speculate about that eventual stage of capitalism, but to resist the data colonialism that is under way. This is how we understand Big Data from the South. Through what we call ‘data relations’ (new types of human relations which enable the extraction of data for commodification), social life all over the globe becomes an ‘open’ resource for extraction that is somehow ‘just there’ for capital. These global flows of data are as expansive as historic colonialism’s appropriation of land, resources, and bodies, although the epicentre has somewhat shifted. Data colonialism involves not one pole of colonial power (‘the West’), but at least two: the USA and China. This complicates our notion of the geography of the Global South, a concept which until now helped situate resistance and disidentification along geographic divisions between former colonizers and colonized. Instead, the new data colonialism works both externally — on a global scale — and internally on its own home populations. The elites of data colonialism (think of Facebook) benefit from colonization in both dimensions, and North-South, East-West divisions no longer matter in the same way.

It is important to acknowledge both the apparent similarities and the significant differences between our argument and the many preceding critical arguments about Big Data…(More)”

From Code to Cure


David J. Craig at Columbia Magazine: “Armed with enormous amounts of clinical data, teams of computer scientists, statisticians, and physicians are rewriting the rules of medical research….

The deluge is upon us.

We are living in the age of big data, and with every link we click, every message we send, and every movement we make, we generate torrents of information.

In the past two years, the world has produced more than 90 percent of all the digital data that has ever been created. New technologies churn out an estimated 2.5 quintillion bytes per day. Data pours in from social media and cell phones, weather satellites and space telescopes, digital cameras and video feeds, medical records and library collections. Technologies monitor the number of steps we walk each day, the structural integrity of dams and bridges, and the barely perceptible tremors that indicate a person is developing Parkinson’s disease. These are the building blocks of our knowledge economy.

This tsunami of information is also providing opportunities to study the world in entirely new ways. Nowhere is this more evident than in medicine. Today, breakthroughs are being made not just in labs but on laptops, as biomedical researchers trained in mathematics, computer science, and statistics use powerful new analytic tools to glean insights from enormous data sets and help doctors prevent, treat, and cure disease.

“The medical field is going through a major period of transformation, and many of the changes are driven by information technology,” says George Hripcsak ’85PS,’00PH, a physician who chairs the Department of Biomedical Informatics at Columbia University Irving Medical Center (CUIMC). “Diagnostic techniques like genomic screening and high-resolution imaging are generating more raw data than we’ve ever handled before. At the same time, researchers are increasingly looking outside the confines of their own laboratories and clinics for data, because they recognize that by analyzing the huge streams of digital information now available online they can make discoveries that were never possible before.” …

Consider, for example, what the young computer scientist has been able to accomplish in recent years by mining an FDA database of prescription-drug side effects. The archive, which contains millions of reports of adverse drug reactions that physicians have observed in their patients, is continuously monitored by government scientists whose job it is to spot problems and pull drugs off the market if necessary. And yet by drilling down into the database with his own analytic tools, Tatonetti has found evidence that dozens of commonly prescribed drugs may interact in dangerous ways that have previously gone unnoticed. Among his most alarming findings: the antibiotic ceftriaxone, when taken with the heartburn medication lansoprazole, can trigger a type of heart arrhythmia called QT prolongation, which is known to cause otherwise healthy people to suddenly drop dead…(More)”

Big Data Is Getting Bigger. So Are the Privacy and Ethical Questions.


Goldie Blumenstyk at The Chronicle of Higher Education: “…The next step in using “big data” for student success is upon us. It’s a little cool. And also kind of creepy.

This new approach goes beyond the tactics now used by hundreds of colleges, which depend on data collected from sources like classroom teaching platforms and student-information systems. It not only makes a technological leap; it also raises issues around ethics and privacy.

Here’s how it works: Whenever you log on to a wireless network with your cellphone or computer, you leave a digital footprint. Move from one building to another while staying on the same network, and that network knows how long you stayed and where you went. That data is collected continuously and automatically from the network’s various nodes.

Now, with the help of a company called Degree Analytics, a few colleges are beginning to use location data collected from students’ cellphones and laptops as they move around campus. Some colleges are using it to improve the kind of advice they might send to students, like a text-message reminder to go to class if they’ve been absent.

Others see it as a tool for making decisions on how to use their facilities. St. Edward’s University, in Austin, Tex., used the data to better understand how students were using its computer-equipped spaces. It found that a renovated lounge, with relatively few computers but with Wi-Fi access and several comfy couches, was one of the most popular such sites on campus. Now the university knows it may not need to buy as many computers as it once thought.

As Gary Garofalo, a co-founder and chief revenue officer of Degree Analytics, told me, “the network data has very intriguing advantages” over the forms of data that colleges now collect.

Some of those advantages are obvious: If you’ve got automatic information on every person walking around with a cellphone, your dataset is more complete than if you need to extract it from a learning-management system or from the swipe-card readers some colleges use to track students’ activities. Many colleges now collect such data to determine students’ engagement with their coursework and campus activities.

Of course, the 24-7 reporting of the data is also what makes this approach seem kind of creepy….

I’m not the first to ask questions like this. A couple of years ago, a group of educators organized by Martin Kurzweil of Ithaka S+R and Mitchell Stevens of Stanford University issued a series of guidelines for colleges and companies to consider as they began to embrace data analytics. Among other principles, the guidelines highlighted the importance of being transparent about how the information is used, and ensuring that institutions’ leaders really understand what companies are doing with the data they collect. Experts at New America weighed in too.

I asked Kurzweil what he makes of the use of Wi-Fi information. Location tracking tends toward the “dicey” side of the spectrum, he says, though perhaps not as far out as using students’ social-media habits, health information, or what they check out from the library. The fundamental question, he says, is “how are they managing it?”… So is this the future? Benz, at least, certainly hopes so. Inspired by the Wi-Fi-based StudentLife research project at Dartmouth College and the experiences Purdue University is having with students’ use of its Forecast app, he’s in talks now with a research university about a project that would generate other insights that might be gleaned from students’ Wi-Fi-usage patterns….(More)

Big Data: the End of the Scientific Method?


Paper by S. Succi and P.V. Coveney at arXiv: “We argue that the boldest claims of Big Data are in need of revision and toning-down, in view of a few basic lessons learned from the science of complex systems. We point out that, once the most extravagant claims of Big Data are properly discarded, a synergistic merging of BD with big theory offers considerable potential to spawn a new scientific paradigm capable of overcoming some of the major barriers confronted by the modern scientific method originating with Galileo. These obstacles are due to the presence of nonlinearity, nonlocality and hyperdimensions which one encounters frequently in multiscale modelling….(More)”.

What top technologies should the next generation know how to use?


Lottie Waters at Devex: “Technology provides some great opportunities for global development, and a promising future. But for the next generation of professionals to succeed, it’s vital they stay up to date with the latest tech, innovations, and tools.

In a recent report produced by Devex in collaboration with the United States Agency for International Development and DAI, some 86 percent of survey respondents believe the technology, skills, and approaches development professionals will be using in 10 years’ time will be significantly different to today’s.

In fact, “technology for development” is regarded as the sector that will see the most development progress, but is also cited as the one that will see the biggest changes in skills required, according to the survey.

“As different technologies develop, new possibilities will open up that we may not even be aware of yet. These opportunities will bring new people into the development sector and require those in it to be more agile in adapting technologies to meet development challenges,” said one survey respondent.

While “blockchain,” “artificial intelligence,” and “drones” may be the current buzzwords surrounding tech in global development, geographical information systems, or GIS, and big data are actually the top technologies respondents believe the next generation of development professionals should learn how to utilize.

So, how are these technologies currently being used in development, how might this change in the near future, and what will their impact be in the next 10 years? Devex spoke with experts in the field who are already integrating these technologies into their work to find out….(More)”

Algorithms are taking over – and woe betide anyone they class as a ‘deadbeat’


Zoe Williams at The Guardian: “The radical geographer and equality evangelist Danny Dorling tried to explain to me once why an algorithm could be bad for social justice.

Imagine if email inboxes became intelligent: your messages would be prioritised on arrival, so if the recipient knew you and often replied to you, you’d go to the top; I said that was fine. That’s how it works already. If they knew you and never replied, you’d go to the bottom, he continued. I said that was fair – it would teach me to stop annoying that person.

If you were a stranger, but typically other people replied to you very quickly – let’s say you were Barack Obama – you’d sail right to the top. That seemed reasonable. And if you were a stranger who others usually ignored, you’d fall off the face of the earth.

“Well, maybe they should get an allotment and stop emailing people,” I said.

“Imagine how angry those people would be,” Dorling said. “They already feel invisible and they [would] become invisible by design.”…

All our debates about the use of big data have centred on privacy, and all seem a bit distant: I care, in principle, whether or not Ocado knows what I bought on Amazon. But in my truest heart, I don’t really care whether or not my Frube vendor knows that I also like dystopian fiction of the 1970s.

I do, however, care that a program exists that will determine my eligibility for a loan by how often I call my mother. I care if landlords are using tools to rank their tenants by compliant behaviour, to create a giant, shared platform of desirable tenants, who never complain about black mould and greet each rent increase with a basket of muffins. I care if the police in Durham are using Experian credit scores to influence their custodial decisions, an example – as you may have guessed by its specificity – that is already real. I care that the same credit-rating company has devised a Mosaic score, which splits households into comically bigoted stereotypes: if your name is Liam and you are an “avid texter”, that puts you in “disconnected youth”, while if you’re Asha you’re in “crowded kaleidoscope”. It’s not a privacy issue so much as a profiling one, although, as anyone who has ever been the repeated victim of police stop-and-search could have told me years ago, these are frequently the same thing.

Privacy isn’t the right to keep secrets: it’s the right to be an individual, not a type; the right to make a choice that’s entirely your own; the right to be private….(More)”.

Ethics as Methods: Doing Ethics in the Era of Big Data Research—Introduction


Introduction to the Special issue of Social Media + Society on “Ethics as Methods: Doing Ethics in the Era of Big Data Research”: Building on a variety of theoretical paradigms (i.e., critical theory, [new] materialism, feminist ethics, theory of cultural techniques) and frameworks (i.e., contextual integrity, deflationary perspective, ethics of care), the Special Issue contributes specific cases and fine-grained conceptual distinctions to ongoing discussions about the ethics in data-driven research.

In the second decade of the 21st century, a grand narrative is emerging that posits knowledge derived from data analytics as true, because of the objective qualities of data, their means of collection and analysis, and the sheer size of the data set. The by-product of this grand narrative is that the qualitative aspects of behavior and experience that form the data are diminished, and the human is removed from the process of analysis.

This situates data science as a process of analysis performed by the tool, which obscures human decisions in the process. The scholars involved in this Special Issue problematize the assumptions and trends in big data research and point out the crisis in accountability that emerges from using such data to make societal interventions.

Our collaborators offer a range of answers to the question of how to configure ethics through a methodological framework in the context of the prevalence of big data, neural networks, and automated, algorithmic governance of much of human socia(bi)lity…(More)”.