Algorithmic Bayesian Persuasion

Persuasion, defined as the act of exploiting an informational advantage in order to effect the decisions of others, is ubiquitous. Indeed, persuasive communication has been estimated to account for almost a third of all economic activity in the US. This paper examines persuasion through a computational lens, focusing on what is perhaps the most basic and fundamental model in this space: the celebrated Bayesian persuasion model of Kamenica and Gentzkow. Here there are two players, a sender and a receiver. The receiver must take one of a number of actions with a-priori unknown payoff, and the sender has access to additional information regarding the payoffs. The sender can commit to revealing a noisy signal regarding the realization of the payoffs of various actions, and would like to do so as to maximize her own payoff assuming a perfectly rational receiver. We examine the sender's optimization task in three of the most natural input models for this problem, and essentially pin down its computational complexity in each. When the payoff distributions of the different actions are i.i.d. and given explicitly, we exhibit a polynomial-time (exact) algorithm, and a "simple" $(1-1/e)$-approximation algorithm. Our optimal scheme for the i.i.d. setting involves an analogy to auction theory, and makes use of Border's characterization of the space of reduced-forms for single-item auctions. When action payoffs are independent but non-identical with marginal distributions given explicitly, we show that it is #P-hard to compute the optimal expected sender utility. Finally, we consider a general (possibly correlated) joint distribution of action payoffs presented by a black box sampling oracle, and exhibit a fully polynomial-time approximation scheme (FPTAS) with a bi-criteria guarantee. We show that this result is the best possible in the black-box model for information-theoretic reasons

Internet Use for Health Information among American Indians: Facilitators and Inhibitors

Our research team explored Internet use among a heterogeneous American Indian (AI) population to determine Internet use in relation to health information seeking behaviors. Participants examined an AI culturally-tailored tobacco website as an example to explain what they wanted in an AI Internet health site. Using community-based participatory research, we conducted 10 focus groups with non-college AI men and women (N=96), stratified by age (18-29, 30-49, and 50 and over) to better understand their perceptions of Internet use and health information needs. We found that Internet use varied greatly among all strata. Participants referenced WebMD© more than any other website, but participants were not pleased with the design and navigation. When examining the sample website, participants across strata stressed that recreational and traditional tobacco use should be discussed. Participants in all strata desired a simple website design with easy to read text accompanied by images. In order to gain and maintain cultural respect, participants stated that web designers should be aware that some images hold cultural meaning, particularly tobacco. Baseline data are needed for AI’s use of the Internet to obtain health information; this research is helpful to address health inequalities among AI, particularly access to web-based health information

Identity dynamics as a barrier to organizational change

This article seeks to explore the construction of group and professional identities in situations of organizational change. It considers empirical material drawn from a health demonstration project funded by the Scottish Executive Health Department, and uses insights from this project to discuss issues that arise from identity construction(s) and organizational change. In the course of the project studied here, a new organizational form was developed which involved a network arrangement with a voluntary sector organization and the employment of “lay-workers” in what had traditionally been a professional setting. Our analysis of the way actors made sense of their identities reveals that characterizations of both self and other became barriers to the change process. These identity dynamics were significant in determining the way people interpreted and responded to change within this project and which may relate to other change-oriented situations

Active Class Incremental Learning for Imbalanced Datasets

Incremental Learning (IL) allows AI systems to adapt to streamed data. Most existing algorithms make two strong hypotheses which reduce the realism of the incremental scenario: (1) new data are assumed to be readily annotated when streamed and (2) tests are run with balanced datasets while most real-life datasets are actually imbalanced. These hypotheses are discarded and the resulting challenges are tackled with a combination of active and imbalanced learning. We introduce sample acquisition functions which tackle imbalance and are compatible with IL constraints. We also consider IL as an imbalanced learning problem instead of the established usage of knowledge distillation against catastrophic forgetting. Here, imbalance effects are reduced during inference through class prediction scaling. Evaluation is done with four visual datasets and compares existing and proposed sample acquisition functions. Results indicate that the proposed contributions have a positive effect and reduce the gap between active and standard IL performance.Comment: Accepted in IPCV workshop from ECCV202

Reproducibility of aortic intima-media thickness in infants using edge-detection software and manual caliper measurements

Background: Aortic intima-media thickness measured by transabdominal ultrasound (aIMT) is an intermediate phenotype of cardiovascular risk. We aimed to (1) investigate the reproducibility of aIMT in a population-derived cohort of infants; (2) establish the distribution of aIMT in early infancy; (3) compare measurement by edge-detection software to that by manual sonographic calipers; and (4) assess the effect of individual and environmental variables on image quality. Methods. Participants were term infants recruited to a population-derived birth cohort study. Transabdominal ultrasound was performed at six weeks of age by one of two trained operators. Thirty participants had ultrasounds performed by both operators on the same day. Data were collected on environmental (infant sleeping, presence of a sibling, use of sucrose, timing during study visit) and individual (post-conception age, weight, gender) variables. Two readers assessed image quality and measured aIMT by edge-detection software and a subset by manual sonographic calipers. Measurements were repeated by the same reader and between readers to obtain intra-observer and inter-observer reliability. Results: Aortic IMT was measured successfully using edge-detection in 814 infants, and 290 of these infants also had aIMT measured using manual sonographic calipers. The intra-reader intra-class correlation (ICC) (n = 20) was 0.90 (95% CI 0.76, 0.96), mean difference 1.5 μm (95% LOA -39, 59). The between reader ICC using edge-detection (n = 20) was 0.92 (95% CI 0.82, 0.97) mean difference 2 μm (95% LOA -45.0, 49.0) and with manual caliper measurement (n = 290) the ICC was 0.84 (95% CI 0.80, 0.87) mean difference 5 μm (95% LOA -51.8, 61.8). Edge-detection measurements were greater than those from manual sonographic calipers (mean aIMT 618 μm (50) versus mean aIMT 563 μm (49) respectively; p < 0.001, mean difference 44 μm, 95% LOA -54, 142). With the exception of infant crying (p = 0.001), no associations were observed between individual and environmental variables and image quality. Conclusion: In a population-derived cohort of term infants, aIMT measurement has a high level of intra and inter-reader reproducibility. Measurement of aIMT using edge-detection software gives higher inter-reader ICC than manual sonographic calipers. Image quality is not substantially affected by individual and environmental factors. © 2014 McCloskey et al.; licensee BioMed Central Ltd

Syndromic surveillance to assess the potential public health impact of the Icelandic volcanic ash plume across the United Kingdom, April 2010

The Eyjafjallajökull volcano in Iceland erupted on 14 April 2010 emitting a volcanic ash plume that spread across the United Kingdom and mainland Europe. The Health Protection Agency and Health Protection Scotland used existing syndromic surveillance systems to monitor community health during the incident: there were no particularly unusual increases in any of the monitored conditions. This incident has again demonstrated the use of syndromic surveillance systems for monitoring community health in real time

Reinventing College Physics for Biologists: Explicating an epistemological curriculum

The University of Maryland Physics Education Research Group (UMd-PERG) carried out a five-year research project to rethink, observe, and reform introductory algebra-based (college) physics. This class is one of the Maryland Physics Department's large service courses, serving primarily life-science majors. After consultation with biologists, we re-focused the class on helping the students learn to think scientifically -- to build coherence, think in terms of mechanism, and to follow the implications of assumptions. We designed the course to tap into students' productive conceptual and epistemological resources, based on a theoretical framework from research on learning. The reformed class retains its traditional structure in terms of time and instructional personnel, but we modified existing best-practices curricular materials, including Peer Instruction, Interactive Lecture Demonstrations, and Tutorials. We provided class-controlled spaces for student collaboration, which allowed us to observe and record students learning directly. We also scanned all written homework and examinations, and we administered pre-post conceptual and epistemological surveys. The reformed class enhanced the strong gains on pre-post conceptual tests produced by the best-practices materials while obtaining unprecedented pre-post gains on epistemological surveys instead of the traditional losses.Comment: 35 pages including a 15 page appendix of supplementary material

Efficacy of weekly teriparatide does not vary by baseline fracture probability calculated using FRAX

Summary The aim of this study was to determine the efficacy of once-weekly teriparatide as a function of baseline fracture risk. Treatment with once-weekly teriparatide was associated with a statistically significant 79 % decrease in vertebral fractures, and in the cohort as a whole, efficacy was not related to baseline fracture risk. Introduction Previous studies have suggested that the efficacy of some interventions may be greater in the segment of the population at highest fracture risk as assessed by the FRAX® algorithms. The aim of the present study was to determine whether the antifracture efficacy of weekly teriparatide was dependent on the magnitude of fracture risk. Methods Baseline fracture probabilities (using FRAX) were computed from the primary data of a phase 3 study (TOWER) of the effects of weekly teriparatide in 542 men and postmenopausal women with osteoporosis. The outcome variable comprised morphometric vertebral fractures. Interactions between fracture probability and efficacy were explored by Poisson regression. Results The 10-year probability of major osteoporotic fractures (without BMD) ranged from 7.2 to 42.2 %. FRAX-based hip fracture probabilities ranged from 0.9 to 29.3 %. Treatment with teriparatide was associated with a 79 % (95 % CI 52–91 %) decrease in vertebral fractures assessed by semiquantitative morphometry. Relative risk reductions for the effect of teriparatide on the fracture outcome did not change significantly across the range of fracture probabilities (p = 0.28). In a subgroup analysis of 346 (64 %) participants who had FRAX probabilities calculated with the inclusion of BMD, there was a small but significant interaction (p = 0.028) between efficacy and baseline fracture probability such that high fracture probabilities were associated with lower efficacy. Conclusion Weekly teriparatide significantly decreased the risk of morphometric vertebral fractures in men and postmenopausal women with osteoporosis. Overall, the efficacy of teriparatide was not dependent on the level of fracture risk assessed by FRAX in the cohort as a whole