Epistemic Paternalism Online

New media (highly interactive digital technology for creating, sharing, and consuming information) affords users a great deal of control over their informational diets. As a result, many users of new media unwittingly encapsulate themselves in epistemic bubbles (epistemic structures, such as highly personalized news feeds, that leave relevant sources of information out (Nguyen forthcoming)). Epistemically paternalistic alterations to new media technologies could be made to pop at least some epistemic bubbles. We examine one such alteration that Facebook has made in an effort to fight fake news and conclude that it is morally permissible. We further argue that many epistemically paternalistic policies can (and should) be a perennial part of the internet information environment

Algorithms and Autonomy

Algorithms influence every facet of modern life. However, delegating important decisions to machines gives rise to deep moral concerns about responsibility, transparency, fairness, and democracy. This book examines these concerns by connecting them to the human value of autonomy. This title is also available as Open Access on Cambridge Core

What We Informationally Owe Each Other

ABSTRACT: One important criticism of algorithmic systems is that they lack transparency. Such systems can be opaque because they are complex, protected by patent or trade secret, or deliberately obscure. In the EU, there is a debate about whether the General Data Protection Regulation (GDPR) contains a “right to explanation,” and if so what such a right entails. Our task in this chapter is to address this informational component of algorithmic systems. We argue that information access is integral for respecting autonomy, and transparency policies should be tailored to advance autonomy. To make this argument we distinguish two facets of agency (i.e., capacity to act). The first is practical agency, or the ability to act effectively according to one’s values. The second is what we call cognitive agency, which is the ability to exercise what Pamela Hieronymi calls “evaluative control” (i.e., the ability to control our affective states, such as beliefs, desires, and attitudes). We argue that respecting autonomy requires providing persons sufficient information to exercise evaluative control and properly interpret the world and one’s place in it. We draw this distinction out by considering algorithmic systems used in background checks, and we apply the view to key cases involving risk assessment in criminal justice decisions and K-12 teacher evaluation. The link below is to an open access version of the chapter

A Hybrid of Adaptation and Dynamic Routing based on SDN for Improving QoE in HTTP Adaptive VBR Video Streaming

Recently, HTTP Adaptive Streaming HAS has received significant attention from both industry and academia based on its ability to enhancing media streaming services over the Internet. Recent research solutions that have tried to improve HAS by adaptation at the client side only may not be completely effective without interacting with routing decisions in the upper layers. In this paper, we address the aforementioned issue by proposing a dynamic bandwidth allocation and management architecture for streaming video flows to improve users satisfaction. We also introduce an initial cross layer hybrid method that combines quality adaptation of variable bitrate video streaming over the HTTP protocol at the client side and SDN based dynamical routing. This scheme is enabled by the Software Defined Networking architecture that is now being considered as an emerging paradigm that disassociates the forwarding process from the routing process. SDN brings flexibility and the ability to flexibly change routing solutions, in turn resulting in dynamically improving the services provided in the application layer. Our experimental results show that the proposed solution offers significantly higher overall bitrates as well as smoother viewing experience than existing methods.Comment: 14 pages, 17 figures, IJCSNS International Journal of Computer Science and Network Security, http://paper.ijcsns.org/07_book/201907/20190708.pd

Student perspectives on a collaborative international doctorate of pharmacy program

Objectives: To evaluate the educational experience and teaching methods of the collaborative Doctorate of Pharmacy (PharmD) program between the University of Malta (UM) and the University of Illinois at Chicago (UIC). Methods: A 41-question survey was developed to identify student demographics, satisfaction with the PharmD program and the utility of the current curricular components. Students who enrolled in the program in May 2017 were invited to participate. The survey contained open-ended, 5-point Likert, and multiple-choice type questions. The primary outcomes were the overall satisfaction and student motivations for pursuing the program. Secondary outcomes included the level of difficulty of courses, evaluation of assessment methods, and confidence in an interdisciplinary team. Results: Thirty-six students completed the survey (a response rate of 83.7%). The mean age was 30.1 ± 7.9 years. The majority of the students pursued the PharmD program to improve their knowledge, skills, and opportunity for obtaining a clinical position. The mean overall satisfaction of the program was 3.81 ± 1.1 (5 = very satisfied). Among the core courses, Pharmacotherapeutics had the highest overall satisfaction (4.45 ± 0.91) and level of difficulty (3.84 ± 0.51). Students felt that the tutorials/recitation case discussion sessions were the most effective teaching method (48.4%) and ranked faculties conducting case-based lectures highest for overall performance. Most students felt somewhat confident (54.8%) for participating in a multidisciplinary team. Conclusions: The UM/UIC PharmD Program is a unique program, utilizing a hybrid model of teaching, including distance education, to expose students to a broad and challenging curriculum in clinical pharmacy practice. Students are satisfied with this collaborative, international postgraduate PharmD program.peer-reviewe

Aggregation of classifiers: a justifiable information granularity approach.

In this paper, we introduced a new approach of combining multiple classifiers in a heterogeneous ensemble system. Instead of using numerical membership values when combining, we constructed interval membership values for each class prediction from the meta-data of observation by using the concept of information granule. In the proposed method, the uncertainty (diversity) of the predictions produced by the base classifiers is quantified by the interval-based information granules. The decision model is then generated by considering both bound and length of the intervals. Extensive experimentation using the UCI datasets has demonstrated the superior performance of our algorithm over other algorithms including six fixed combining methods, one trainable combining method, AdaBoost, bagging, and random subspace