Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions


HBR Working Paper by Andrea Blasco et al: “Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant performance gains over established algorithms. These include algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research….(More)”.

Data Can Help Students Maximize Return on Their College Investment


Blog by Jennifer Latson for Arnold Ventures: “When you buy a car, you want to know it will get you where you’re going. Before you invest in a certain model, you check its record. How does it do in crash tests? Does it have a history of breaking down? Are other owners glad they bought it?

Students choosing between college programs can’t do the same kind of homework. Much of the detailed data we demand when we buy a car isn’t available for postsecondary education — data such as how many students find jobs in the fields they studied, what they earn, how much debt they accumulate, and how quickly they repay it — yet choosing a college is a much more important financial decision.

The most promising solution to filling in the gaps, according to data advocates, is the College Transparency Act, which would create a secure, comprehensive national data network with information on college costs, graduation rates, and student career paths — and make this data publicly available. The bill, which will be discussed in Congress this year, has broad support from both Republicans and Democrats in the House and the Senate in part because it includes precautions to protect privacy and secure student data….

The data needed to answer questions about student success already exists but is scattered among various agencies and institutions: the Department of Educationfor data on student loan repayment; the Treasury Department for earnings information; and schools themselves for graduation rates.

“We can’t connect the dots to find out how these programs are serving certain students, and that’s because the Department of Education isn’t allowed to connect all the information these places have already collected,” says Amy Laitinen, director for higher education at New America, a think tank collaborating with IHEP to promote educational transparency.
And until recently, publicly available federal postsecondary data only included full-time students who’d never enrolled in a college program before, ignoring the more than half of the higher ed population made up of students who attend school part time or who transfer from one institution to another….(More)”.

Trustworthy Privacy Indicators: Grades, Labels, Certifications and Dashboards


Paper by Joel R. Reidenberg et al: “Despite numerous groups’ efforts to score, grade, label, and rate the privacy of websites, apps, and network-connected devices, these attempts at privacy indicators have, thus far, not been widely adopted. Privacy policies, however, remain long, complex, and impractical for consumers. Communicating in some short-hand form, synthesized privacy content is now crucial to empower internet users and provide them more meaningful notice, as well as nudge consumers and data processors toward more meaningful privacy. Indeed, on the basis of these needs, the National Institute of Standards and Technology and the Federal Trade Commission in the United States, as well as lawmakers and policymakers in the European Union, have advocated for the development of privacy indicator systems.

Efforts to develop privacy grades, scores, labels, icons, certifications, seals, and dashboards have wrestled with various deficiencies and obstacles for the wide-scale deployment as meaningful and trustworthy privacy indicators. This paper seeks to identify and explain these deficiencies and obstacles that have hampered past and current attempts. With these lessons, the article then offers criteria that will need to be established in law and policy for trustworthy indicators to be successfully deployed and adopted through technological tools. The lack of standardization prevents user-recognizability and dependability in the online marketplace, diminishes the ability to create automated tools for privacy, and reduces incentives for consumers and industry to invest in a privacy indicators. Flawed methods in selection and weighting of privacy evaluation criteria and issues interpreting language that is often ambiguous and vague jeopardize success and reliability when baked into an indicator of privacy protectiveness or invasiveness. Likewise, indicators fall short when those organizations rating or certifying the privacy practices are not objective, trustworthy, and sustainable.

Nonetheless, trustworthy privacy rating systems that are meaningful, accurate, and adoptable can be developed to assure effective and enduring empowerment of consumers. This paper proposes a framework using examples from prior and current attempts to create privacy indicator systems in order to provide a valuable resource for present-day, real world policymaking….(More)”.

Nudging the dead: How behavioural psychology inspired Nova Scotia’s organ donation scheme


Joseph Brean at National Post: “Nova Scotia’s decision to presume people’s consent to donating their organs after death is not just a North American first. It is also the latest example of how deeply behavioural psychology has changed policy debates.

That is a rare achievement for science. Governments used to appeal to people’s sense of reason, religion, civic duty, or fear of consequences. Today, when they want to change how their citizens behave, they use psychological tricks to hack their minds.

Nudge politics, as it came to be known, has been an intellectual hit among wonks and technocrats ever since Daniel Kahneman won the Nobel Prize in 2002 for destroying the belief people make decisions based on good information and reasonable expectations. Not so, he showed. Not even close. Human decision-making is an organic process, all but immune to reason, but strangely susceptible to simple environmental cues, just waiting to be exploited by a clever policymaker….

Organ donation is a natural fit. Nova Scotia’s experiment aims to solve a policy problem by getting people to do what they always tend to do about government requests — nothing.

The cleverness is evident in the N.S. government’s own words, which play on the meaning of “opportunity”: “Every Nova Scotian will have the opportunity to be an organ and tissue donor unless they opt out.” The policy applies to kidneys, pancreas, heart, liver, lungs, small bowel, cornea, sclera, skin, bones, tendons and heart valves.

It is so clever it aims to make progress as people ignore it. The default position is a positive for the policy. It assumes poor pickup. You can opt out of organ donation if you want. Nova Scotia is simply taking the informed gamble that you probably won’t. That is the goal, and it will make for a revealing case study.

Organ donation is an important question, and chronically low donation rates can reasonably be called a crisis. But most people make their personal choice “thoughtlessly,” as Kahneman wrote in the 2011 book Thinking, Fast and Slow.

He referred to European statistics which showed vast differences in organ donation rights between neighbouring and culturally similar countries, such as Sweden and Denmark, or Germany and Austria. The key difference, he noted, was what he called “framing effects,” or how the question was asked….(More)”.

What if You Could Vote for President Like You Rate Uber Drivers?


Essay by Guru Madhavan and Charles Phelps: “…Some experimental studies have begun to offer insights into the benefits of making voting methods—and the very goals of voting—more expressive. In the 2007 French presidential election, for instance, people were offered the chance to participate in an experimental ballot that allowed them to use letter grades to evaluate the candidates just as professors evaluate students. This approach, called the “majority judgment,” provides a clear method to combine those grades into rankings or a final winner. But instead of merely selecting a winner, majority judgment conveys—with a greater degree of expressivity—the voters’ evaluations of their choices. In this experiment, people completed their ballots in about a minute, thus allaying potential concerns that a letter grading system was too complicated to use. What’s more, they seemed more enthusiastic about this method. Scholars Michel Balinski and Rida Laraki, who led this study, point out: “Indeed, one of the most effective arguments for persuading reluctant voters to participate was that the majority judgment allows fuller expression of opinion.”

Additional experiments with more expressive ballots have now been repeated across different countries and elections. According to a 2018 summary of these experiments by social choice theorist Annick Laruelle,  “While ranking all candidates appears to be difficult … participants enjoy the possibility of choosing a grade for each candidate … [and] ballots with three grades are preferred to those … with two grades.” Some participant comments are revealing, stating, “With this ballot we can at last vote with the heart,” or, “Voting with this ballot is a relief.” Voters, according to Laruelle, “Enjoyed the option of voting in favor of several candidates and were especially satisfied of being offered the opportunity to vote against candidates.”…

These opportunities for expression might increase public interest in (and engagement with) democratic decision making, encouraging more thoughtful candidate debates, more substantive election campaigns and advertisements, and richer use of opinion polling to help candidates shape their position statements (once they are aware that the public’s selection process has changed). One could even envision that the basis for funding election campaigns might evolve if funders focused on policy ideas rather than political allegiances and specific candidates. Changes such as these would ideally put the power back in the hands of the people, where it actually belongs in a democracy. These conjectures need to be tested and retested across contexts, ideally through field experiments that leverage research and expertise in engineering, social choice, and political and behavioral sciences.

Standard left-to-right political scales and the way we currently vote do not capture the true complexity of our evolving political identities and preferences. If voting is indeed the true instrument of democracy and much more than a repeated political ritual, it must allow for richer expression. Current methods seem to discourage public participation, the very nucleus of civic life. The essence of civility and democracy is not merely about providing issues and options to vote on but in enabling people to fully express their preferences. For a country founded on choice as its tenet, is it too much to ask for a little bit more choice in how we select our leaders? …(More)”.

Understanding algorithmic decision-making: Opportunities and challenges


Study by Claude Castelluccia and Daniel Le Métayer for the European Parliament: “While algorithms are hardly a recent invention, they are nevertheless increasingly involved in systems used to support decision-making. These systems, known as ‘ADS’ (algorithmic decision systems), often rely on the analysis of large amounts of personal data to infer correlations or, more generally, to derive information deemed useful to make decisions. Human intervention in the decision-making may vary, and may even be completely out of the loop in entirely automated systems. In many situations, the impact of the decision on people can be significant, such as access to credit, employment, medical treatment, or judicial sentences, among other things.

Entrusting ADS to make or to influence such decisions raises a variety of ethical, political, legal, or technical issues, where great care must be taken to analyse and address them correctly. If they are neglected, the expected benefits of these systems may be negated by a variety of different risks for individuals (discrimination, unfair practices, loss of autonomy, etc.), the economy (unfair practices, limited access to markets, etc.), and society as a whole (manipulation, threat to democracy, etc.).

This study reviews the opportunities and risks related to the use of ADS. It presents policy options to reduce the risks and explain their limitations. We sketch some options to overcome these limitations to be able to benefit from the tremendous possibilities of ADS while limiting the risks related to their use. Beyond providing an up-to date and systematic review of the situation, the study gives a precise definition of a number of key terms and an analysis of their differences to help clarify the debate. The main focus of the study is the technical aspects of ADS. However, to broaden the discussion, other legal, ethical and social dimensions are considered….(More)”.

Privacy-Preserved Data Sharing for Evidence-Based Policy Decisions: A Demonstration Project Using Human Services Administrative Records for Evidence-Building Activities


Paper by the Bipartisan Policy Center: “Emerging privacy-preserving technologies and approaches hold considerable promise for improving data privacy and confidentiality in the 21st century. At the same time, more information is becoming accessible to support evidence-based policymaking.

In 2017, the U.S. Commission on Evidence-Based Policymaking unanimously recommended that further attention be given to the deployment of privacy-preserving data-sharing applications. If these types of applications can be tested and scaled in the near-term, they could vastly improve insights about important policy problems by using disparate datasets. At the same time, the approaches could promote substantial gains in privacy for the American public.

There are numerous ways to engage in privacy-preserving data sharing. This paper primarily focuses on secure computation, which allows information to be accessed securely, guarantees privacy, and permits analysis without making private information available. Three key issues motivated the launch of a domestic secure computation demonstration project using real government-collected data:

  • Using new privacy-preserving approaches addresses pressing needs in society. Current widely accepted approaches to managing privacy risks—like preventing the identification of individuals or organizations in public datasets—will become less effective over time. While there are many practices currently in use to keep government-collected data confidential, they do not often incorporate modern developments in computer science, mathematics, and statistics in a timely way. New approaches can enable researchers to combine datasets to improve the capability for insights, without being impeded by traditional concerns about bringing large, identifiable datasets together. In fact, if successful, traditional approaches to combining data for analysis may not be as necessary.
  • There are emerging technical applications to deploy certain privacy-preserving approaches in targeted settings. These emerging procedures are increasingly enabling larger-scale testing of privacy-preserving approaches across a variety of policy domains, governmental jurisdictions, and agency settings to demonstrate the privacy guarantees that accompany data access and use.
  • Widespread adoption and use by public administrators will only follow meaningful and successful demonstration projects. For example, secure computation approaches are complex and can be difficult to understand for those unfamiliar with their potential. Implementing new privacy-preserving approaches will require thoughtful attention to public policy implications, public opinions, legal restrictions, and other administrative limitations that vary by agency and governmental entity.

This project used real-world government data to illustrate the applicability of secure computation compared to the classic data infrastructure available to some local governments. The project took place in a domestic, non-intelligence setting to increase the salience of potential lessons for public agencies….(More)”.

Fearful of fake news blitz, U.S. Census enlists help of tech giants


Nick Brown at Reuters: “The U.S. Census Bureau has asked tech giants Google, Facebook and Twitter to help it fend off “fake news” campaigns it fears could disrupt the upcoming 2020 count, according to Census officials and multiple sources briefed on the matter.

The push, the details of which have not been previously reported, follows warnings from data and cybersecurity experts dating back to 2016 that right-wing groups and foreign actors may borrow the “fake news” playbook from the last presidential election to dissuade immigrants from participating in the decennial count, the officials and sources told Reuters.

The sources, who asked not to be named, said evidence included increasing chatter on platforms like “4chan” by domestic and foreign networks keen to undermine the survey. The census, they said, is a powerful target because it shapes U.S. election districts and the allocation of more than $800 billion a year in federal spending.

Ron Jarmin, the Deputy Director of the Census Bureau, confirmed the bureau was anticipating disinformation campaigns, and was enlisting the help of big tech companies to fend off the threat.

“We expect that (the census) will be a target for those sorts of efforts in 2020,” he said.

Census Bureau officials have held multiple meetings with tech companies since 2017 to discuss ways they could help, including as recently as last week, Jarmin said.

So far, the bureau has gotten initial commitments from Alphabet Inc’s Google, Twitter Inc and Facebook Inc to help quash disinformation campaigns online, according to documents summarizing some of those meetings reviewed by Reuters.

But neither Census nor the companies have said how advanced any of the efforts are….(More)”.

Negotiating with the future: incorporating imaginary future generations into negotiations


Paper by Yoshio Kamijo et al: “People to be born in the future have no direct
influence on current affairs. Given the disconnect between people who are currently living and those who will inherit the planet left for them, individuals who are currently alive tend to be more oriented toward the present, posing a fundamental problem related to sustainability.

In this study, we propose a new framework for reconciling the disconnect between the present and the future whereby some individuals in the current generation serve as an imaginary future generation that negotiates with individuals in the real-world present. Through a laboratory-controlled intergenerational sustainability dilemma game (ISDG), we show how the presence of negotiators for a future generation increases the benefits of future generations. More specifically, we found that when faced with members of an imaginary future generation, 60% of participants selected
an option that promoted sustainability. In contrast, when the imaginary future generation was not salient, only 28% of participants chose the sustainable option…(More)”.

Big Data in the U.S. Consumer Price Index: Experiences & Plans


Paper by Crystal G. Konny, Brendan K. Williams, and David M. Friedman: “The Bureau of Labor Statistics (BLS) has generally relied on its own sample surveys to collect the price and expenditure information necessary to produce the Consumer Price Index (CPI). The burgeoning availability of big data has created a proliferation of information that could lead to methodological improvements and cost savings in the CPI. The BLS has undertaken several pilot projects in an attempt to supplement and/or replace its traditional field collection of price data with alternative sources. In addition to cost reductions, these projects have demonstrated the potential to expand sample size, reduce respondent burden, obtain transaction prices more consistently, and improve price index estimation by incorporating real-time expenditure information—a foundational component of price index theory that has not been practical until now. In CPI, we use the term alternative data to refer to any data not collected through traditional field collection procedures by CPI staff, including third party datasets, corporate data, and data collected through web scraping or retailer API’s. We review how the CPI program is adapting to work with alternative data, followed by discussion of the three main sources of alternative data under consideration by the CPI with a description of research and other steps taken to date for each source. We conclude with some words about future plans… (More)”.