Surrogates and Artificial Intelligence: Why AI Trumps Family

The increasing accuracy of algorithms to predict values and preferences raises the possibility that artificial intelligence technology will be able to serve as a surrogate decision-maker for incapacitated patients. Following Camillo Lamanna and Lauren Byrne, we call this technology the autonomy algorithm (AA). Such an algorithm would mine medical research, health records, and social media data to predict patient treatment preferences. The possibility of developing the AA raises the ethical question of whether the AA or a relative ought to serve as surrogate decision-maker in cases where the patient has not issued a medical power of attorney. We argue that in such cases, and against the standard practice of vesting familial surrogates with decision making authority, the AA should have sole decision-making authority. This is because the AA will likely be better at predicting what treatment option the patient would have chosen. It would also be better at avoiding bias and, therefore, choosing in a more patient-centered manner. Furthermore, we argue that these considerations override any moral weight of the patient\u27s special relationship with their relatives

The Common Rule’s “Reasonable Person” Standard for Informed Consent

Laura Odwazny and Benjamin Berkman have raised several challenges regarding the new reasonable person standard in the revised Common Rule, which states that informed consent requires potential research subjects be provided with information a reasonable person would want to know to make an informed decision on whether to participate in a study. Our aim is to offer a response to the challenges Odwazny and Berkman raise, which include the need for a reasonable person standard that can be applied consistently across institutional review boards and that does not stigmatize marginal groups. In response, we argue that the standard ought to be based in an ordinary rather than ideal person conception of reasonable person and that the standard ought to employ what we call a liberal constraint: the reasonability standard must be malleable enough such that a wide variety of individuals with different, unique value systems would endorse it. We conclude by suggesting some of the likely consequences our view would have, if adopted

Few-shot classification in Named Entity Recognition Task

For many natural language processing (NLP) tasks the amount of annotated data is limited. This urges a need to apply semi-supervised learning techniques, such as transfer learning or meta-learning. In this work we tackle Named Entity Recognition (NER) task using Prototypical Network - a metric learning technique. It learns intermediate representations of words which cluster well into named entity classes. This property of the model allows classifying words with extremely limited number of training examples, and can potentially be used as a zero-shot learning method. By coupling this technique with transfer learning we achieve well-performing classifiers trained on only 20 instances of a target class.Comment: In proceedings of the 34th ACM/SIGAPP Symposium on Applied Computin

Concert recording 2017-01-25

[Track 1]. Passaggio rotto from Book 2 of Ayres for the violin / Nicola Matteis -- [Tracks 2-4]. Partia #4 in E minor for 2 violins and basso from Muscalsche ergotzung / Johann Pachelbel -- [Track 5]. Partia #5 in G minor from Artifiosus concentur pro camera / Johann Vilsmayr -- [Track 6]. Sonata #4 / Heinrich Biber -- [Tracks 7-9].Sonata for violin and piano, K. 454 / W.A. Mozart -- [Track 10]. The dream, Op. 38 #5 / Serge Rachmaninoff -- [Tracks 11-13]. Sonata for violin and piano #3 in C minor / Edvard Grieg

The Use of Online Panel Data in Management Research: A Review and Recommendations

Management scholars have long depended on convenience samples to conduct research involving human participants. However, the past decade has seen an emergence of a new convenience sample: online panels and online panel participants. The data these participants provide—online panel data (OPD)—has been embraced by many management scholars owing to the numerous benefits it provides over “traditional” convenience samples. Despite those advantages, OPD has not been warmly received by all. Currently, there is a divide in the field over the appropriateness of OPD in management scholarship. Our review takes aim at the divide with the goal of providing a common understanding of OPD and its utility and providing recommendations regarding when and how to use OPD and how and where to publish it. To accomplish these goals, we inventoried and reviewed OPD use across 13 management journals spanning 2006 to 2017. Our search resulted in 804 OPD-based studies across 439 articles. Notably, our search also identified 26 online panel platforms (“brokers”) used to connect researchers with online panel participants. Importantly, we offer specific guidance to authors, reviewers, and editors, having implications for both micro and macro management scholars

Aerodynamics for the ADEPT SR-1 Flight Experiment

Adaptable, Deployable, Entry, and Placement Technology (ADEPT) is a combination of a heatshield and an aerodynamic decelerator for atmospheric entry applications. The ADEPT Sounding Rocket (SR)-1 mission was a suborbital flight experiment of an 0.7 m-diameter ADEPT to verify system-level performance and to characterize dynamic stability behavior. The aerodynamic database for ADEPT SR-1 was constructed from non-continuum and continuum flowfield computations, along with data from recent ADEPT ground testing and the IRVE-3 flight test vehicle. High-altitude (free-molecular and transitional regimes) data were generated using DSMC methods. Pre-flight predictions of continuum static aerodynamics coefficients were derived from Reynolds-Averaged Navier-Stokes solutions at conditions along a design trajectory, with comparisons to available ground test data of the nano-ADEPT geometry. Dynamic pitch damping characteristics were taken from functional forms developed for the IRVE-3 flight test vehicle through ballistic range testing. Comparison of pre-flight predictions to post-flight reconstruction of aerodynamic force and moment coefficients is presented

Low-Cost, Commercial Scale Production of Sofosbuvir

Recent advances in antiviral therapeutics have produced highly effective small molecule drugs to treat Hepatitis C, a deadly infection of the liver. Sofosbuvir, a hepatitis C drug developed by Gilead Sciences, is a breakthrough treatment due to its low side effects and high cure rate. However, the cost of treatment is extraordinarily high, priced at $84,000 per treatment in the US. In response to backlash regarding the cost barriers in developing countries, Gilead has reached licensing agreements with generic pharmaceutical companies to produce the drug for markets in low-income countries such as India, Kenya, and Cuba among others. The report describes a cost-effective, commercial scale process design for the production of sofosbuvir. The proposed production facility is designed to deliver 350,000 kg/year of the active pharmaceutical ingredient, enough to treat 10 million patients per year. The production will be completed over one hundred batches, requiring operation of 120 days/year. Assuming an 11-year period of operation, detailed economic analysis suggests that this is a profitable venture with an IRR of 67.7$1.2 billion USD

Solar Sails: Towards An Early Profitable PowerSat

Successful development of space solar power would provide vast quantities of clean electrical energy for the next few billion years. Such a prize is worth considerable effort and risk. However, the technical difficulties and the huge scale of proposed systems, requiring enormous up front costs and long development times, have prevented SSP from making much progress. If a way could be found to field a small SSP system profitably, even if limited to niche markets, operational progress could be made with relatively small investments over short time scales. This visualization explores the concept of a “thin-film heliogyro” – a solar sail - as a lower cost approach to producing energy in space and transmitting it to earth as an infrared (IR) power beam. Advisors: Al Globus, Tyler Ayres, John Bowditch Solar Sails: Towards an Early Profitable PowerSat from Space Communication Journal on Vimeo