Artificial Intelligence Accelerated Transformation in The Healthcare Industry

The healthcare industry was a pioneer in the deployment of artificial intelligence (AI) technology. Due to the nature of the services and the vulnerability of a sizable portion of end users, there has been a significant amount of research and discussion on the concept of artificial intelligence. A mixed-method approach has been used to pinpoint the components of moral AI in the healthcare sector and look into how it affects value creation and market performance. Since AI technology is still developing in India, analysis is conducted in an Indian context. The understanding of how various AI components supported healthcare organisations and deliver better patient-centered care and evidence-based medicine was aided by these in-depth studies and analyses of the patient perspective

Celebrity as a political resource: the human rights now! campaign

The use of celebrities as endorsers of causes and even political candidates has become ubiquitous in modern culture. Aided by the rise of mass and social media the impact of celebrity on the organizations that use their power is seldom examined. This work critically reviews the role celebrity played in one of the first and largest events of its kind—Amnesty International’s Human Rights Now! global tour of rock musicians in 1989. It analyzes both the short-term human rights goals of the tour and the long-term influence the tour had on organizational culture

Catalog of Approaches to Impact Measurement: Assessing Social Impact in Private Ventures

To inform action impact investors could take to measure impact in a coordinated manner, The Rockefeller Foundation commissioned the study of impact assessment approaches presented here.It is natural to hope to find a single, turnkey solution that can address all measurement needs. In this study we conducted a survey of impact investors and complemented it with seven years of experience in the field of impact investing to discover what these investors want from impact measurement, and conducted in-depth interviews with over twenty entities that have developed and implemented approaches to measuring impact. Our survey of existing approaches was thorough but surely is not comprehensive; however the approaches are a good representation of the current state of play. What we found is that there is not one single measurement answer. Instead the answer depends on what solution is most appropriate for a particular investor's "impact profile" defined as the investor's level of risk tolerance and desired financial return, the particular sector in which the investor operates, geography, and credibility level of information about impact that the investor requires

Using ‘Appreciative Inquiry’ in India to improve infection control practices in maternity care : a qualitative study

ACKNOWLEDGEMENTS The inputs and facilitation of field work from the Gujarat state government officials are acknowledged. We express our gratitude to the doctors, nurses and other health facility staff for actively participating in the study. Our special thanks to Dr. Pritam Pal for capacity building of the research team for appreciative inquiry and Mr. Sanjay Joshi for follow-up of the AI process. We appreciate the help of Dr. Purvi Shah in data collection and preparing transcripts for the study. The study was funded by the John D. and Catherine T. MacArthur Foundation.Peer reviewedPublisher PD

Neural Paraphrase Identification of Questions with Noisy Pretraining

We present a solution to the problem of paraphrase identification of questions. We focus on a recent dataset of question pairs annotated with binary paraphrase labels and show that a variant of the decomposable attention model (Parikh et al., 2016) results in accurate performance on this task, while being far simpler than many competing neural architectures. Furthermore, when the model is pretrained on a noisy dataset of automatically collected question paraphrases, it obtains the best reported performance on the dataset

Pegxit Pressure: Evidence from the Classical Gold Standard

We develop a simple model that highlights the costs and benefits of fixed exchange rates as they relate to trade, and show that negative export-price shocks reduce fiscal revenue and increase the likelihood of an expected currency devaluation. Using a new high-frequency data set on commodity-price movements from the classical gold standard era, we then show that the model’s main prediction holds even for the canonical example of hard pegs. We identify a negative causal relationship between export-price shocks and currency-risk premia in emerging market economies, indicating that negative export-price shocks increased the probability that countries abandoned their pegs