Negotiating with the future: incorporating imaginary future generations into negotiations

Curated on Posted on by Stefaan Verhulst

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

Curated on Posted on by Stefaan Verhulst

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)”.

Using massive online choice experiments to measure changes in well-being

Curated on Posted on by Stefaan Verhulst

Paper by Erik Brynjolfsson, Avinash Collis, and Felix Eggers: “Gross domestic product (GDP) and derived metrics such as productivity have been central to our understanding of economic progress and well-being. In principle, changes in consumer surplus provide a superior, and more direct, measure of changes in well-being, especially for digital goods. In practice, these alternatives have been difficult to quantify. We explore the potential of massive online choice experiments to measure consumer surplus. We illustrate this technique via several empirical examples which quantify the valuations of popular digital goods and categories. Our examples include incentive-compatible discrete-choice experiments where online and laboratory participants receive monetary compensation if and only if they forgo goods for predefined periods.

For example, the median user needed a compensation of about $48 to forgo Facebook for 1 mo. Our overall analyses reveal that digital goods have created large gains in well-being that are not reflected in conventional measures of GDP and productivity. By periodically querying a large, representative sample of goods and services, including those which are not priced in existing markets, changes in consumer surplus and other new measures of well-being derived from these online choice experiments have the potential for providing cost-effective supplements to the existing national income and product accounts….(More)”.

Beyond opinion classification: Extracting facts, opinions and experiences from health forums

Curated on Posted on by Stefaan Verhulst

Paper by Jorge Carrillo-de-Albornoz et al in PLOS-ONE: “Surveys indicate that patients, particularly those suffering from chronic conditions, strongly benefit from the information found in social networks and online forums. One challenge in accessing online health information is to differentiate between factual and more subjective information. In this work, we evaluate the feasibility of exploiting lexical, syntactic, semantic, network-based and emotional properties of texts to automatically classify patient-generated contents into three types: “experiences”, “facts” and “opinions”, using machine learning algorithms. In this context, our goal is to develop automatic methods that will make online health information more easily accessible and useful for patients, professionals and researchers….

We work with a set of 3000 posts to online health forums in breast cancer, morbus crohn and different allergies. Each sentence in a post is manually labeled as “experience”, “fact” or “opinion”. Using this data, we train a support vector machine algorithm to perform classification. The results are evaluated in a 10-fold cross validation procedure.

Overall, we find that it is possible to predict the type of information contained in a forum post with a very high accuracy (over 80 percent) using simple text representations such as word embeddings and bags of words. We also analyze more complex features such as those based on the network properties, the polarity of words and the verbal tense of the sentences and show that, when combined with the previous ones, they can boost the results….(More)”.

Comparative Accuracy of Diagnosis by Collective Intelligence of Multiple Physicians vs Individual Physicians

Curated on Posted on by Stefaan Verhulst

Study by Michael L. Barnett et al in JAMA: “Is a collective intelligence approach of pooling multiple clinician and medical student diagnoses associated with improvement in diagnostic accuracy in online, structured clinical cases?

Findings  This cross-sectional study analyzing data from the Human Diagnosis Project found that, across a broad range of medical cases and common presenting symptoms, independent differential diagnoses of multiple physicians combined into a weighted list significantly outperformed diagnoses of individual physicians with groups as small as 2, and accuracy increased with larger groups up to 9 physicians. Groups of nonspecialists also significantly outperformed individual specialists solving cases matched to the individual specialist’s specialty….

Main Outcomes and Measures  The primary outcome was diagnostic accuracy, assessed as a correct diagnosis in the top 3 ranked diagnoses for an individual; for groups, the top 3 diagnoses were a collective differential generated using a weighted combination of user diagnoses with a variety of approaches. A version of the McNemar test was used to account for clustering across repeated solvers to compare diagnostic accuracy.

Conclusions and Relevance  A collective intelligence approach was associated with higher diagnostic accuracy compared with individuals, including individual specialists whose expertise matched the case diagnosis, across a range of medical cases. Given the few proven strategies to address misdiagnosis, this technique merits further study in clinical settings….(More)”.

Crowdsourcing Change: A Novel Vantage Point for Investigating Online Petitioning Platforms

Curated on Posted on by Stefaan Verhulst

Presentation by Shipi Dhanorkar and Mary Beth Rosson: “The internet connects people who are spatially and temporally separated. One result is new modes of reaching out to, organizing and mobilizing people, including online activism. Internet platforms can be used to mobilize people around specific concerns, short-circuiting structures such as organizational hierarchies or elected officials. These online processes allow consumers and concerned citizens to voice their opinions, often to businesses, other times to civic groups or other authorities. Not surprisingly, this opportunity has encouraged a steady rise in specialized platforms dedicated to online petitioning; eg., Change.org, Care2 Petitions, MoveOn.org, etc.

These platforms are open to everyone; any individual or group who is affected by a problem or disappointed with the status quo, can raise awareness for or against corporate or government policies. Such platforms can empower ordinary citizens to bring about social change, by leveraging support from the masses. In this sense, the platforms allow citizens to “crowdsource change”. In this paper, we offer a comparative analysis of the affordances of four online petitioning platforms, and use this analysis to propose ideas for design enhancements to online petitioning platforms….(More)”.

So Many Nudges, So Little Time: Can Cost-effectiveness Tell Us When It Is Worthwhile to Try to Change Provider Behavior?

Curated on Posted on by Stefaan Verhulst

Paper by David Atkins: “Interest in behavioral economics has grown steadily within health care. Policy makers, payers, and providers now recognize that the decisions of patients and of their doctors frequently deviate from the strictly “rational” choices that classical economic theory would predict. For example, patients rarely adhere to the medication regimens or health behaviors that would optimize their health outcomes, and clinicians often make decisions that conflict with evidence-based recommendations or even the practices they profess to endorse. The groundbreaking work of psychologist Daniel Kahneman and his collaborator Amos Tversky raised attention to this field, which was accelerated by Kahneman’s 2002 Nobel Prize in economics and his popular 2011 book “Thinking Fast and Slow” which reached a much broader audience.

Behavioral economics examines cognitive, psychological, and cultural factors that may influence how we make decisions, resulting in behavior that another Nobel laureate, economist Richard Thaler, has termed “predictably irrational.” Principles from behavioral economics have been adopted to health care, including the role of heuristics (rules of thumb), the importance of framing, and the effects of specific cognitive biases (for example, overconfidence and status quo bias).

These principles have been incorporated into interventions that seek to use these insights to change health-related behaviors—these include nudges, where systems are redesigned to make the preferred choice the default choice (for example, making generic versions the default in electronic prescribing); incentive programs that reward patients for taking their medications on schedule or getting preventive interventions like immunizations; and specific interventions aimed at how clinicians respond to information or make decisions….(More)”.

How Effective Is Nudging? A Quantitative Review on the Effect Sizes and Limits of Empirical Nudging Studies

Curated on Posted on by Stefaan Verhulst

Paper by Dennis Hummel and Alexander Maedche: “Changes in the choice architecture, so-called nudges, have been employed in a variety of contexts to alter people’s behavior. Although nudging has gained a widespread popularity, the effect sizes of its influences vary considerably across studies. In addition, nudges have proven to be ineffective or even backfire in selected studies which raises the question whether, and under which conditions, nudges are effective. Therefore, we conduct a quantitative review on nudging with 100 primary publications including 317 effect sizes from different research areas. We derive four key results. (1) A morphological box on nudging based on eight dimensions, (2) an assessment of the effectiveness of different nudging interventions, (3) a categorization of the relative importance of the application context and the nudge category, and (4) a comparison of nudging and digital nudging. Thereby, we shed light on the (in)effectiveness of nudging and we show how the findings of the past can be used for future research. Practitioners, especially government officials, can use the results to review and adjust their policy making….(More)”.

Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation

Curated on Posted on by Stefaan Verhulst

Paper by Serge Abiteboul and Julia Stoyanovich: “The data revolution continues to transform every sector of science, industry and government. Due to the incredible impact of data-driven technology on society, we are becoming increasingly aware of the imperative to use data and algorithms responsibly — in accordance with laws and ethical norms. In this article we discuss three recent regulatory frameworks: the European Union’s General Data Protection Regulation (GDPR), the New York City Automated Decisions Systems (ADS) Law, and the Net Neutrality principle, that aim to protect the rights of individuals who are impacted by data collection and analysis. These frameworks are prominent examples of a global trend: Governments are starting to recognize the need to regulate data-driven algorithmic technology. 


Our goal in this paper is to bring these regulatory frameworks to the attention of the data management community, and to underscore the technical challenges they raise and which we, as a community, are well-equipped to address. The main .take-away of this article is that legal and ethical norms cannot be incorporated into data-driven systems as an afterthought. Rather, we must think in terms of responsibility by design, viewing it as a systems requirement….(More)”

Digital Pro Bono: Leveraging Technology to Provide Access to Justice

Curated on Posted on by Stefaan Verhulst

Paper by Kathleen Elliott Vinson and Samantha A. Moppett: “…While individuals have the constitutional right to legal assistance in criminal cases, the same does not hold true for civil matters. Low-income Americans are unable to gain access to meaningful help for basic legal needs. Although legal aid organizations exist to help low-income Americans who cannot afford legal representation, the resources available are insufficient to meet current civil legal needs. Studies show more than 80 percent of the legal needs of low-income Americans go unaddressed every year. 

This article examines how law students, law schools, the legal profession, legal services’ agencies, and low-income individuals who need assistance, all have a shared interest—access to justice—and can work together to reach the elusive goal in the Pledge of Allegiance of “justice for all.” It illustrates how their collaborative leveraging of technology in innovative ways like digital pro bono services, is one way to provide access to justice. It discusses ABA Free Legal Answers Online, the program that the ABA pioneered to help confront the justice gap in the United States. The program provides a “virtual legal advice clinic” where attorneys answer civil legal questions that low-income residents post on free, secure, and confidential state-specific websites. The article provides a helpful resource of how law schools can leverage this technology to increase access to justice for low-income communities while providing pro bono opportunities for attorneys and students in their state…(More)”.