JPMorgan Creates ‘Volfefe’ Index to Track Trump Tweet Impact

Curated on Posted on by Stefaan Verhulst

Tracy Alloway at Bloomberg: “Two of the largest Wall Street banks are trying to measure the market impact of Donald Trump’s tweets.

Analysts at JPMorgan Chase & Co. have created an index to quantify what they say are the growing effects on U.S. bond yields. Citigroup Inc.’s foreign exchange team, meanwhile, report that these micro-blogging missives are also becoming “increasingly relevant” to foreign-exchange moves.

JPMorgan’s “Volfefe Index,” named after Trump’s mysterious covfefe tweet from May 2017, suggests that the president’s electronic musings are having a statistically significant impact on Treasury yields. The number of market-moving Trump tweets has ballooned in the past month, with those including words such as “China,” “billion,” “products,” “Democrats” and “great” most likely to affect prices, the analysts found….

JPMorgan’s analysis looked at Treasury yields in the five minutes after a Trump tweet, and the index shows the rolling one-month probability that each missive is market-moving.

They found that the Volfefe Index can account for a “measurable fraction” of moves in implied volatility, seen in interest rate derivatives known as swaptions. That’s particularly apparent at the shorter end of the curve, with two- and five-year rates more impacted than 10-year securities.

Meanwhile, Citi’s work shows that the president’s tweets are generally followed by a stretch of higher volatility across global currency markets. And there’s little sign traders are growing numb to these messages….(More)”

The Why of the World

Curated on Posted on by Stefaan Verhulst

Book review by Tim Maudlin of The Book of Why: The New Science of Cause and Effect by Judea Pearl and Dana Mackenzie: “Correlation is not causation.” Though true and important, the warning has hardened into the familiarity of a cliché. Stock examples of so-called spurious correlations are now a dime a dozen. As one example goes, a Pacific island tribe believed flea infestations to be good for one’s health because they observed that healthy people had fleas while sick people did not. The correlation is real and robust, but fleas do not cause health, of course: they merely indicate it. Fleas on a fevered body abandon ship and seek a healthier host. One should not seek out and encourage fleas in the quest to ward off sickness.

The rub lies in another observation: that the evidence for causation seems to lie entirely in correlations. But for seeing correlations, we would have no clue about causation. The only reason we discovered that smoking causes lung cancer, for example, is that we observed correlations in that particular circumstance. And thus a puzzle arises: if causation cannot be reduced to correlation, how can correlation serve as evidence of causation?

The Book of Why, co-authored by the computer scientist Judea Pearl and the science writer Dana Mackenzie, sets out to give a new answer to this old question, which has been around—in some form or another, posed by scientists and philosophers alike—at least since the Enlightenment. In 2011 Pearl won the Turing Award, computer science’s highest honor, for “fundamental contributions to artificial intelligence through the development of a calculus of probabilistic and causal reasoning,” and this book sets out to explain what all that means for a general audience, updating his more technical book on the same subject, Causality, published nearly two decades ago. Written in the first person, the new volume mixes theory, history, and memoir, detailing both the technical tools of causal reasoning Pearl has developed as well as the tortuous path by which he arrived at them—all along bucking a scientific establishment that, in his telling, had long ago contented itself with data-crunching analysis of correlations at the expense of investigation of causes. There are nuggets of wisdom and cautionary tales in both these aspects of the book, the scientific as well as the sociological…(More)”.

Sharenthood: Why We Should Think before We Talk about Our Kids Online

Curated on Posted on by Stefaan Verhulst

Book by Leah Plunkett: “Our children’s first digital footprints are made before they can walk—even before they are born—as parents use fertility apps to aid conception, post ultrasound images, and share their baby’s hospital mug shot. Then, in rapid succession come terabytes of baby pictures stored in the cloud, digital baby monitors with built-in artificial intelligence, and real-time updates from daycare. When school starts, there are cafeteria cards that catalog food purchases, bus passes that track when kids are on and off the bus, electronic health records in the nurse’s office, and a school surveillance system that has eyes everywhere. Unwittingly, parents, teachers, and other trusted adults are compiling digital dossiers for children that could be available to everyone—friends, employers, law enforcement—forever. In this incisive book, Leah Plunkett examines the implications of “sharenthood”—adults’ excessive digital sharing of children’s data. She outlines the mistakes adults make with kids’ private information, the risks that result, and the legal system that enables “sharenting.”

Plunkett describes various modes of sharenting—including “commercial sharenting,” efforts by parents to use their families’ private experiences to make money—and unpacks the faulty assumptions made by our legal system about children, parents, and privacy. She proposes a “thought compass” to guide adults in their decision making about children’s digital data: play, forget, connect, and respect. Enshrining every false step and bad choice, Plunkett argues, can rob children of their chance to explore and learn lessons. The Internet needs to forget. We need to remember….(More)”.

Is Privacy and Personal Data Set to Become the New Intellectual Property?

Curated on Posted on by Stefaan Verhulst

Paper by Leon Trakman, Robert Walters, and Bruno Zeller: “A pressing concern today is whether the rationale underlying the protection of personal data is itself a meaningful foundation for according intellectual property (IP) rights in personal data to data subjects. In particular, are there particular technological attributes about the collection, use and processing of personal data on the Internet, and global access to that data, that provide a strong justification to extend IP rights to data subjects? A central issue in so determining is whether data subjects need the protection of such rights in a technological revolution in which they are increasingly exposed to the use and abuse of their personal data. A further question is how IP law can provide them with the requisite protection of their private space, or whether other means of protecting personal data, such as through general contract rights, render IP protections redundant, or at least, less necessary. This paper maintains that lawmakers often fail to distinguish between general property and IP protection of personal data; that IP protection encompasses important attributes of both property and contract law; and that laws that implement IP protection in light of its sui generis attributes are more fitting means of protecting personal data than the alternatives. The paper demonstrates that one of the benefits of providing IP rights in personal data goes some way to strengthening data subjects’ control and protection over their personal data and strengthening data protection law more generally. It also argues for greater harmonization of IP law across jurisdictions to ensure that the protection of personal data becomes more coherent and internationally sustainable….(More)”.

Computational Communication Science

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue of the International Journal of Communication:”Over the past two decades, processes of digitalization and mediatization have shaped the communication landscape and have had a strong impact on various facets of communication. The digitalization of communication results in completely new forms of digital traces that make communication processes observable in new and unprecedented ways. Although many scholars in the social sciences acknowledge the chances and requirements of the digital revolution in communication, they are also facing fundamental challenges in implementing successful research programs, strategies, and designs that are based on computational methods and “big data.” This Special Section aims at bringing together seminal perspectives on challenges and chances of computational communication science (CCS). In this introduction, we highlight the impulses provided by the research presented in the Special Section, discuss the most pressing challenges in the context of CCS, and sketch a potential roadmap for future research in this field….(More)”.

How to Build Artificial Intelligence We Can Trust

Curated on Posted on by Stefaan Verhulst

Gary Marcus and Ernest Davis at the New York Times: “Artificial intelligence has a trust problem. We are relying on A.I. more and more, but it hasn’t yet earned our confidence.

Tesla cars driving in Autopilot mode, for example, have a troubling history of crashing into stopped vehicles. Amazon’s facial recognition system works great much of the time, but when asked to compare the faces of all 535 members of Congress with 25,000 public arrest photos, it found 28 matches, when in reality there were none. A computer program designed to vet job applicants for Amazon was discovered to systematically discriminate against women. Every month new weaknesses in A.I. are uncovered.

The problem is not that today’s A.I. needs to get better at what it does. The problem is that today’s A.I. needs to try to do something completely different.

In particular, we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets — often using an approach known as deep learning — and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space and causality….

We face a choice. We can stick with today’s approach to A.I. and greatly restrict what the machines are allowed to do (lest we end up with autonomous-vehicle crashes and machines that perpetuate bias rather than reduce it). Or we can shift our approach to A.I. in the hope of developing machines that have a rich enough conceptual understanding of the world that we need not fear their operation. Anything else would be too risky….(More)”.

Next100

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PressRelease: “Next100, a new “startup” think tank built for and by the next generation of policy leaders, officially launched today with the announcement of its inaugural class of eight “Policy Entrepreneurs,” selected from a highly competitive pool of more than 740 applicants. These eight rising leaders will spend the next two years researching and developing policy solutions to the issues that matter most to the next generation, focusing in particular on: education, immigration, criminal justice, climate change, economic opportunity, and the intersections between such issues.

Next100 was announced as an independent think tank earlier this year by The Century Foundation (TCF), in celebration of TCF’s 100th anniversary. It is built as a different type of “think and do” tank — both in terms of the people, perspectives, and policy areas represented, as well as its approach to advancing policy change. The organization’s mission is to change the face and future of progressive policy, through making the policymaking space more inclusive of diverse, next generation voices, and by helping emerging leaders translate their creative policy ideas into tangible policy change.

“The next generation is too often and too easily excluded from the policymaking table, despite having the most at stake in the decisions made at that table,” said Emma Vadehra, executive director of Next100. “As a result, we end up with the same people, with the same ideas, trying to solve the same problems, in the same ways. Next100 is trying to change that, and reimagine what a think tank can and should be. We’re giving diverse leaders of the next generation a chance to cut through the inertia and bring their unmatched creativity, knowledge, skills, and experiences to bear on the policymaking process. Policy by those with the most at stake, for those with the most at stake.”…(More)”.

How Should Scientists’ Access To Health Databanks Be Managed?

Curated on Posted on by Stefaan Verhulst

Richard Harris at NPR: “More than a million Americans have donated genetic information and medical data for research projects. But how that information gets used varies a lot, depending on the philosophy of the organizations that have gathered the data.

Some hold the data close, while others are working to make the data as widely available to as many researchers as possible — figuring science will progress faster that way. But scientific openness can be constrained b y both practical and commercial considerations.

Three major projects in the United States illustrate these differing philosophies.

VA scientists spearhead research on veterans database

The first project involves three-quarters of a million veterans, mostly men over age 60. Every day, 400 to 500 blood samples show up in a modern lab in the basement of the Veterans Affairs hospital in Boston. Luis Selva, the center’s associate director, explains that robots extract DNA from the samples and then the genetic material is sent out for analysis….

Intermountain Healthcare teams with deCODE genetics

Our second example involves what is largely an extended family: descendants of settlers in Utah, primarily from the Church of Jesus Christ of Latter-day Saints. This year, Intermountain Healthcare in Utah announced that it was going to sequence the complete DNA of half a million of its patients, resulting in what the health system says will be the world’s largest collection of complete genomes….

NIH’s All of Us aims to diversify and democratize research

Our third and final example is an effort by the National Institutes of Health to recruit a million Americans for a long-term study of health, behavior and genetics. Its philosophy sharply contrasts with that of Intermountain Health.

“We do have a very strong goal around diversity, in making sure that the participants in the All of Us research program reflect the vast diversity of the United States,” says Stephanie Devaney, the program’s deputy director….(More)”.

Raw data won’t solve our problems — asking the right questions will

Curated on Posted on by Stefaan Verhulst

Stefaan G. Verhulst in apolitical: “If I had only one hour to save the world, I would spend fifty-five minutes defining the questions, and only five minutes finding the answers,” is a famous aphorism attributed to Albert Einstein.

Behind this quote is an important insight about human nature: Too often, we leap to answers without first pausing to examine our questions. We tout solutions without considering whether we are addressing real or relevant challenges or priorities. We advocate fixes for problems, or for aspects of society, that may not be broken at all.

This misordering of priorities is especially acute — and represents a missed opportunity — in our era of big data. Today’s data has enormous potential to solve important public challenges.

However, policymakers often fail to invest in defining the questions that matter, focusing mainly on the supply side of the data equation (“What data do we have or must have access to?”) rather than the demand side (“What is the core question and what data do we really need to answer it?” or “What data can or should we actually use to solve those problems that matter?”).

As such, data initiatives often provide marginal insights while at the same time generating unnecessary privacy risks by accessing and exploring data that may not in fact be needed at all in order to address the root of our most important societal problems.

A new science of questions

So what are the truly vexing questions that deserve attention and investment today? Toward what end should we strategically seek to leverage data and AI?

The truth is that policymakers and other stakeholders currently don’t have a good way of defining questions or identifying priorities, nor a clear framework to help us leverage the potential of data and data science toward the public good.

This is a situation we seek to remedy at The GovLab, an action research center based at New York University.

Our most recent project, the 100 Questions Initiative, seeks to begin developing a new science and practice of questions — one that identifies the most urgent questions in a participatory manner. Launched last month, the goal of this project is to develop a process that takes advantage of distributed and diverse expertise on a range of given topics or domains so as to identify and prioritize those questions that are high impact, novel and feasible.

Because we live in an age of data and much of our work focuses on the promises and perils of data, we seek to identify the 100 most pressing problems confronting the world that could be addressed by greater use of existing, often inaccessible, datasets through data collaboratives – new forms of cross-disciplinary collaboration beyond public-private partnerships focused on leveraging data for good….(More)”.

How Tulsa is Preserving Privacy and Sharing Data for Social Good

Curated on Posted on by Stefaan Verhulst

Data across Sectors for Health: “Data sharing between organizations addressing social risk factors has the potential to amplify impact by increasing direct service capacity and efficiency. Unfortunately, the risks of and restrictions on sharing personal data often limit this potential, and adherence to regulations such as HIPAA and FERPA can make data sharing a significant challenge.

DASH CIC-START awardee Restore Hope Ministries worked with Asemio to utilize technology that allows for the analysis of personally identifiable information while preserving clients’ privacy. The collaboration shared their findings in a new white paper that describes the process of using multi-party computation technology to answer questions that can aid service providers in exploring the barriers that underserved populations may be facing. The first question they asked: what is the overlap of populations served by two distinct organizations? The results of the overlap analysis confirmed that a significant opportunity exists to increase access to services for a subset of individuals through better outreach…(More)”