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)”

Our misguided love affair with techno-politics


The Economist: “What might happen if technology, which smothers us with its bounty as consumers, made the same inroads into politics? Might data-driven recommendations suggest “policies we may like” just as Amazon recommends books? Would we swipe right to pick candidates in elections or answers in referendums? Could businesses expand into every cranny of political and social life, replete with ® and ™ at each turn? What would this mean for political discourse and individual freedom?

This dystopian yet all-too-imaginable world has been conjured up by Giuseppe Porcaro in his novel “Disco Sour”. The story takes place in the near future, after a terrible war and breakdown of nations, when the (fictional) illegitimate son of Roman Polanski creates an app called Plebiscitum that works like Tinder for politics.

Mr Porcaro—who comes armed with a doctorate in political geography—uses the plot to consider questions of politics in the networked age. The Economist’s Open Future initiative asked him to reply to five questions in around 100 words each. An excerpt from the book appears thereafter.

*     *     *

The Economist: In your novel, an entrepreneur attempts to replace elections with an app that asks people to vote on individual policies. Is that science fiction or prediction? And were you influenced by Italy’s Five Star Movement?

Giuseppe Porcaro: The idea of imagining a Tinder-style app replacing elections came up because I see connections between the evolution of dating habits and 21st-century politics. A new sort of “tinderpolitics” kicking in when instant gratification substitutes substantial participation. Think about tweet trolling, for example.

Italy’s Five Star Movement was certainly another inspiration as it is has been a pioneer in using an online platform to successfully create a sort of new political mass movement. Another one was an Australian political party called Flux. They aim to replace the world’s elected legislatures with a new system known as issue-based direct democracy.

The Economist: Is it too cynical to suggest that a more direct relationship between citizens and policymaking would lead to a more reactionary political landscape? Or does the ideal of liberal democracy depend on an ideal citizenry that simply doesn’t exist?  

Mr Porcaro: It would be cynical to put the blame on citizens for getting too close to influence decision-making. That would go against the very essence of the “liberal democracy ideal”. However, I am critical towards the pervasive idea that technology can provide quick fixes to bridge the gap between citizens and the government. By applying computational thinking to democracy, an extreme individualisation and instant participation, we forget democracy is not simply the result of an election or the mathematical sum of individual votes. Citizens risk entering a vicious circle where reactionary politics are easier to go through.

The Economist: Modern representative democracy was in some ways a response to the industrial revolution. If AI and automation radically alter the world we live in, will we have to update the way democracy works too—and if so, how? 

Mr Porcaro: Democracy has already morphed several times. 19th century’s liberal democracy was shaken by universal suffrage, and adapted to the Fordist mode of production with the mass party. May 1968 challenged that model. Today, the massive availability of data and the increasing power of decision-making algorithms will change both political institutions.

The policy “production” process might be utterly redesigned. Data collected by devices we use on a daily basis (such as vehicles, domestic appliances and wearable sensors) will provide evidence about the drivers of personal voting choices, or the accountability of government decisions. …(More)

This surprising, everyday tool might hold the key to changing human behavior


Annabelle Timsit at Quartz: “To be a person in the modern world is to worry about your relationship with your phone. According to critics, smartphones are making us ill-mannered and sore-necked, dragging parents’ attention away from their kids, and destroying an entire generation.

But phones don’t have to be bad. With 4.68 billion people forecast to become mobile phone users by 2019, nonprofits and social science researchers are exploring new ways to turn our love of screens into a force for good. One increasingly popular option: Using texting to help change human behavior.

Texting: A unique tool

The short message service (SMS) was invented in the late 1980s, and the first text message was sent in 1992. (Engineer Neil Papworth sent “merry Christmas” to then-Vodafone director Richard Jarvis.) In the decades since, texting has emerged as the preferred communication method for many, and in particular younger generations. While that kind of habit-forming can be problematic—47% of US smartphone users say they “couldn’t live without” the device—our attachment to our phones also makes text-based programs a good way to encourage people to make better choices.

“Texting, because it’s anchored in mobile phones, has the ability to be with you all the time, and that gives us an enormous flexibility on precision,” says Todd Rose, director of the Mind, Brain, & Education Program at the Harvard Graduate School of Education. “When people lead busy lives, they need timely, targeted, actionable information.”

And who is busier than a parent? Text-based programs can help current or would-be moms and dads with everything from medication pickup to childhood development. Text4Baby, for example, messages pregnant women and young moms with health information and reminders about upcoming doctor visits. Vroom, an app for building babies’ brains, sends parents research-based prompts to help them build positive relationships with their children (for example, by suggesting they ask toddlers to describe how they’re feeling based on the weather). Muse, an AI-powered app, uses machine learning and big data to try and help parents raise creative, motivated, emotionally intelligent kids. As Jenny Anderson writes in Quartz: “There is ample evidence that we can modify parents’ behavior through technological nudges.”

Research suggests text-based programs may also be helpful in supporting young children’s academic and cognitive development. …Texts aren’t just being used to help out parents. Non-governmental organizations (NGOs) have also used them to encourage civic participation in kids and young adults. Open Progress, for example, has an all-volunteer community called “text troop” that messages young adults across the US, reminding them to register to vote and helping them find their polling location.

Text-based programs are also useful in the field of nutrition, where private companies and public-health organizations have embraced them as a way to give advice on healthy eating and weight loss. The National Cancer Institute runs a text-based program called SmokefreeTXT that sends US adults between three and five messages per day for up to eight weeks, to help them quit smoking.

Texting programs can be a good way to nudge people toward improving their mental health, too. Crisis Text Line, for example, was the first national 24/7 crisis-intervention hotline to conduct counseling conversations entirely over text…(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)”.

Doing good data science


Mike Loukides, Hilary Mason and DJ Patil at O’Reilly: “(This post is the first in a series on data ethics) The hard thing about being an ethical data scientist isn’t understanding ethics. It’s the junction between ethical ideas and practice. It’s doing good data science.

There has been a lot of healthy discussion about data ethics lately. We want to be clear: that discussion is good, and necessary. But it’s also not the biggest problem we face. We already have good standards for data ethics. The ACM’s code of ethics, which dates back to 1993, is clear, concise, and surprisingly forward-thinking; 25 years later, it’s a great start for anyone thinking about ethics. The American Statistical Association has a good set of ethical guidelines for working with data. So, we’re not working in a vacuum.

And, while there are always exceptions, we believe that most people want to be fair. Data scientists and software developers don’t want to harm the people using their products. There are exceptions, of course; we call them criminals and con artists. Defining “fairness” is difficult, and perhaps impossible, given the many crosscutting layers of “fairness” that we might be concerned with. But we don’t have to solve that problem in advance, and it’s not going to be solved in a simple statement of ethical principles, anyway.

The problem we face is different: how do we put ethical principles into practice? We’re not talking about an abstract commitment to being fair. Ethical principles are worse than useless if we don’t allow them to change our practice, if they don’t have any effect on what we do day-to-day. For data scientists, whether you’re doing classical data analysis or leading-edge AI, that’s a big challenge. We need to understand how to build the software systems that implement fairness. That’s what we mean by doing good data science.

Any code of data ethics will tell you that you shouldn’t collect data from experimental subjects without informed consent. But that code won’t tell you how to implement “informed consent.” Informed consent is easy when you’re interviewing a few dozen people in person for a psychology experiment. Informed consent means something different when someone clicks on an item in an online catalog (hello, Amazon), and ads for that item start following them around ad infinitum. Do you use a pop-up to ask for permission to use their choice in targeted advertising? How many customers would you lose? Informed consent means something yet again when you’re asking someone to fill out a profile for a social site, and you might (or might not) use that data for any number of experimental purposes. Do you pop up a consent form in impenetrable legalese that basically says “we will use your data, but we don’t know for what”? Do you phrase this agreement as an opt-out, and hide it somewhere on the site where nobody will find it?…

To put ethical principles into practice, we need space to be ethical. We need the ability to have conversations about what ethics means, what it will cost, and what solutions to implement. As technologists, we frequently share best practices at conferences, write blog posts, and develop open source technologies—but we rarely discuss problems such as how to obtain informed consent.

There are several facets to this space that we need to think about.

First, we need corporate cultures in which discussions about fairness, about the proper use of data, and about the harm that can be done by inappropriate use of data can be considered. In turn, this means that we can’t rush products out the door without thinking about how they’re used. We can’t allow “internet time” to mean ignoring the consequences. Indeed, computer security has shown us the consequences of ignoring the consequences: many companies that have never taken the time to implement good security practices and safeguards are now paying with damage to their reputations and their finances. We need to do the same when thinking about issues like fairness, accountability, and unintended consequences….(More)”.

Making a 21st Century Constitution: Playing Fair in Modern Democracies


Making a 21st Century Constitution

Book by Frank Vibert: “Democratic constitutions are increasingly unfit for purpose with governments facing increased pressures from populists and distrust from citizens. The only way to truly solve these problems is through reform. Within this important book, Frank Vibert sets out the key challenges to reform, the ways in which constitutions should be revitalised and provides the standards against which reform should be measured…

Democratic governments are increasingly under pressure from populists, and distrust of governmental authority is on the rise. Economic causes are often blamed. Making a 21st Century Constitution proposes instead that constitutions no longer provide the kind of support that democracies need in today’s conditions, and outlines ways in which reformers can rectify this.

Frank Vibert addresses key sources of constitutional obsolescence, identifies the main challenges for constitutional updating and sets out the ways in which constitutions may be made suitable for the the 21st century. The book highlights the need for reformers to address the deep diversity of values in today’s urbanized societies, the blind spots and content-lite nature of democratic politics, and the dispersion of authority among new chains of intermediaries.

This book will be invaluable for students of political science, public administration and policy, law and constitutional economics. Its analysis of how constitutions can be made fit for purpose again will appeal to all concerned with governance, practitioners and reformers alike…(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)”.

Open Science by Design: Realizing a Vision for 21st Century Research


Report by the National Academies of Sciences: “Openness and sharing of information are fundamental to the progress of science and to the effective functioning of the research enterprise. The advent of scientific journals in the 17th century helped power the Scientific Revolution by allowing researchers to communicate across time and space, using the technologies of that era to generate reliable knowledge more quickly and efficiently. Harnessing today’s stunning, ongoing advances in information technologies, the global research enterprise and its stakeholders are moving toward a new open science ecosystem. Open science aims to ensure the free availability and usability of scholarly publications, the data that result from scholarly research, and the methodologies, including code or algorithms, that were used to generate those data.

Open Science by Design is aimed at overcoming barriers and moving toward open science as the default approach across the research enterprise. This report explores specific examples of open science and discusses a range of challenges, focusing on stakeholder perspectives. It is meant to provide guidance to the research enterprise and its stakeholders as they build strategies for achieving open science and take the next steps….(More)”.

Forty years of wicked problems literature: forging closer links to policy studies


Brian W. Head at Policy and Society: “Rittel and Webber boldly challenged the conventional assumption that ‘scientific’ approaches to social policy and planning provide the most reliable guidance for practitioners and researchers who are addressing complex, and contested, social problems.

This provocative claim, that scientific-technical approaches would not ‘work’ for complex social issues, has engaged policy analysts, academic researchers and planning practitioners since the 1970s. Grappling with the implications of complexity and uncertainty in policy debates, the first generation of ‘wicked problem’ scholars generally agreed that wicked issues require correspondingly complex and iterative approaches. This tended to quarantine complex ‘wicked’ problems as a special category that required special collaborative processes.

Most often they recommended the inclusion of multiple stakeholders in exploring the relevant issues, interests, value differences and policy responses. More than four decades later, however, there are strong arguments for developing a second-generation approach which would ‘mainstream’ the analysis of wicked problems in public policy. While continuing to recognize the centrality of complexity and uncertainty, and the need for creative thinking, a broader approach would make better use of recent public policy literatures on such topics as problem framing, policy design, policy capacity and the contexts of policy implementation….(More)”.

‘Data is a fingerprint’: why you aren’t as anonymous as you think online


Olivia Solon at The Guardian: “In August 2016, the Australian government released an “anonymised” data set comprising the medical billing records, including every prescription and surgery, of 2.9 million people.

Names and other identifying features were removed from the records in an effort to protect individuals’ privacy, but a research team from the University of Melbourne soon discovered that it was simple to re-identify people, and learn about their entire medical history without their consent, by comparing the dataset to other publicly available information, such as reports of celebrities having babies or athletes having surgeries.

The government pulled the data from its website, but not before it had been downloaded 1,500 times.

This privacy nightmare is one of many examples of seemingly innocuous, “de-identified” pieces of information being reverse-engineered to expose people’s identities. And it’s only getting worse as people spend more of their lives online, sprinkling digital breadcrumbs that can be traced back to them to violate their privacy in ways they never expected.

Nameless New York taxi logs were compared with paparazzi shots at locations around the city to reveal that Bradley Cooper and Jessica Alba were bad tippers. In 2017 German researchers were able to identify people based on their “anonymous” web browsing patterns. This week University College London researchers showed how they could identify an individual Twitter user based on the metadata associated with their tweets, while the fitness tracking app Polar revealed the homes and in some cases names of soldiers and spies.

“It’s convenient to pretend it’s hard to re-identify people, but it’s easy. The kinds of things we did are the kinds of things that any first-year data science student could do,” said Vanessa Teague, one of the University of Melbourne researchers to reveal the flaws in the open health data.

One of the earliest examples of this type of privacy violation occurred in 1996 when the Massachusetts Group Insurance Commission released “anonymised” data showing the hospital visits of state employees. As with the Australian data, the state removed obvious identifiers like name, address and social security number. Then the governor, William Weld, assured the public that patients’ privacy was protected….(More)”.