The latest Artificial Intelligence (AI) in Insurance market report offers a detailed analysis of growth driving factors, challenges, and opportunities that will govern the industry expansion in the ensuing years. Besides, it delivers a complete assessment of several industry segments to provide a clear picture of the top revenue prospects of this industry vertical. According to industry analysts, the market is projected to accrue notable gains while recording a CAGR of XX% over the forecast period 2020-2025. Considering the impact of Covid-19, except from healthcare industries, the global health crisis has turned out to be a nightmare for majority of businesses. While some have successfully made changes to their business model or pivoted the entire organization's mission, others continue to face an onslaught of challenges.

TEHRAN, Iran (AP) -- Iran's supreme leader on Saturday demanded the "definitive punishment" of those behind the killing of a scientist who led Tehran's disbanded military nuclear program, as the Islamic Republic blamed Israel for a slaying that has raised fears of reignited tensions across the Middle East. After years of being in the shadows, the image of Mohsen Fakhrizadeh suddenly was to be seen everywhere in Iranian media, as his widow spoke on state television and officials publicly demanded revenge on Israel for the scientist's slaying. Israel, long suspected of killing Iranian scientists a decade ago amid earlier tensions over Tehran's nuclear program, has yet to comment on Fakhrizadeh's killing Friday. However, the attack bore the hallmarks of a carefully planned, military-style ambush, the likes of which Israel has been accused of conducting before. The attack has renewed fears of Iran striking back against the U.S., Israel's closest ally in the region, as it did earlier this year when a U.S. drone strike killed a top Iranian general.

Middle east is one of the top tech destinations where artificial intelligence is playing a significant role. The region is known for its oil wells, which are major contributors to the region's economy. Slowly the economy is shifting its base from petrochemicals to technology. The region is slowly shifting its economic dependence on oil wells. According to an IDC report, spending on AI in the region is expected to grow at an annual growth of 19%.

Linking clinical narratives to standardized vocabularies and coding systems is a key component of unlocking the information in medical text for analysis. However, many domains of medical concepts lack well-developed terminologies that can support effective coding of medical text. We present a framework for developing natural language processing (NLP) technologies for automated coding of under-studied types of medical information, and demonstrate its applicability via a case study on physical mobility function. Mobility is a component of many health measures, from post-acute care and surgical outcomes to chronic frailty and disability, and is coded in the International Classification of Functioning, Disability, and Health (ICF). However, mobility and other types of functional activity remain under-studied in medical informatics, and neither the ICF nor commonly-used medical terminologies capture functional status terminology in practice. We investigated two data-driven paradigms, classification and candidate selection, to link narrative observations of mobility to standardized ICF codes, using a dataset of clinical narratives from physical therapy encounters. Recent advances in language modeling and word embedding were used as features for established machine learning models and a novel deep learning approach, achieving a macro F-1 score of 84% on linking mobility activity reports to ICF codes. Both classification and candidate selection approaches present distinct strengths for automated coding in under-studied domains, and we highlight that the combination of (i) a small annotated data set; (ii) expert definitions of codes of interest; and (iii) a representative text corpus is sufficient to produce high-performing automated coding systems. This study has implications for the ongoing growth of NLP tools for a variety of specialized applications in clinical care and research.

How can we assess the value of data objectively, systematically and quantitatively? Pricing data, or information goods in general, has been studied and practiced in dispersed areas and principles, such as economics, marketing, electronic commerce, data management, data mining and machine learning. In this article, we present a unified, interdisciplinary and comprehensive overview of this important direction. We examine various motivations behind data pricing, understand the economics of data pricing and review the development and evolution of pricing models according to a series of fundamental principles. We discuss both digital products and data products. We also consider a series of challenges and directions for future work.

How should computer science and social science collaborate to build a common model? How should they proceed to gather data that is really useful to the modelling? How can they design a survey that is tailored to the target model? This paper aims to answer those crucial questions in the framework of a multidisciplinary research project. This research addresses the issue of co-constructing a model when several disciplines are involved, and is applied to modelling human behaviour immediately after an earthquake. The main contribution of the work is to propose a tool dedicated to multidisciplinary dialogue. It also proposes a reflexive analysis of the enriching intellectual process carried out by the different disciplines involved. Finally, from working with an anthropologist, a complementary view of the multidisciplinary process is given.

Recently, several studies have investigated active learning (AL) for natural language processing tasks to alleviate data dependency. However, for query selection, most of these studies mainly rely on uncertainty-based sampling, which generally does not exploit the structural information of the unlabeled data. This leads to a sampling bias in the batch active learning setting, which selects several samples at once. In this work, we demonstrate that the amount of labeled training data can be reduced using active learning when it incorporates both uncertainty and diversity in the sequence labeling task. We examined the effects of our sequence-based approach by selecting weighted diverse in the gradient embedding approach across multiple tasks, datasets, models, and consistently outperform classic uncertainty-based sampling and diversity-based sampling.

SCI COMMUN### Infectious diseases The 11th Ebola outbreak in the Democratic Republic of the Congo (DRC) is officially over, giving the country respite from the disease for the first time in more than 2 years. On 18 November, the World Health Organization (WHO) announced that no new cases had been identified for 42 days, twice the incubation period for the deadly virus. The outbreak, in the western Équateur province, started in late May, just as a bigger one in the eastern DRC was coming to an end. (That outbreak had killed 2200 people.) The Équateur outbreak sickened 130 and killed 55; a campaign that vaccinated more than 40,000 people is credited with helping end it. Special portable coolers that keep the vaccine at −80°C for up to 1 week allowed health workers to administer the shots in communities deep in the rainforest, accessible only by boat or helicopter. The same technology will be useful in efforts to distribute COVID-19 vaccines in Africa, says Matshidiso Moeti, WHO's regional director. The coronavirus pandemic complicated the fight against Ebola, WHO says, but the expertise gained by local health workers in earlier outbreaks in the region was a major advantage. They will remain on the lookout for potential flare-ups. $1,000,000 —Gift from entertainer Dolly Parton in April to support development of Moderna's coronavirus vaccine, which the company last week said showed an efficacy of 94.5%. “I felt so proud to have been part of that little seed money,” Parton told BBC. ### Marine ecology The Allen Coral Atlas, a project to map the world's shallow coral reefs with high-resolution satellites, last week launched a monitoring system to detect coral bleaching events as they occur. When corals face extreme heat, they expel their algal symbionts, leaving them bone white and vulnerable to stress; repeated bleaching episodes, growing more common with global warming, can cause massive die-offs. The system detects the whitening using imagery from the privately owned Planet satellite constellation, processed with machine learning. A pilot has begun in Hawaii to use the data as an early warning system for researchers, to help them identify and study species both vulnerable and resistant to warming extremes. The monitoring of bleaching is expected to expand next year to shallow reefs globally. ### Diagnostics The U.S. Food and Drug Administration (FDA) issued its first emergency use authorization last week for an at-home diagnostic test that can detect the pandemic coronavirus in just minutes. However, the test might not be widely available until spring 2021. Produced by Lucira Health, a biotech company, it is expected to cost less than $50 and require a doctor's prescription. The company says it will soon distribute tests in parts of California and Florida; it says it needs time to scale up manufacturing for national distribution. Lucira's test amplifies viral genetic material, making it nearly as accurate as laboratory tests that use the polymerase chain reaction, the current gold standard. FDA previously approved at-home tests that must be mailed to a laboratory for analysis. Several other companies are working on rapid antigen tests, which detect viral particles, for home use. But concerns remain about antigen tests' reliability. Still, some public health specialists consider widely available, low-cost, at-home testing vital for controlling the pandemic. ### Funding A new U.S. National Institutes of Health (NIH) award will allow early-career investigators who want to shift research directions when applying for their first independent award to submit a proposal without first generating preliminary data to support their idea. Reviewers will instead assess the soundness of the project's approach. The Katz award is named for Stephen Katz, a longtime champion of young researchers who was director of the National Institute of Arthritis and Musculoskeletal and Skin Diseases when he died in 2018. The grant will build on an NIH policy that prioritizes proposals from early-stage investigators—those no more than 10 years from completing their training who are applying for their first research grant. The policy has been credited with raising their numbers from fewer than 600 supported in 2013 to more than 1300 last year. Applications for the first Katz awards are due on 26 January 2021. ### Leadership Democrats in Congress say a political appointee given a senior post at the U.S. National Institute of Standards and Technology (NIST) is unfit for the job because he lacks technical skills and holds pseudoscientific views about racial differences on IQ tests. On 9 November, Jason Richwine, an independent public policy analyst, took up the new position of deputy undersecretary of commerce for standards and technology, and Commerce Secretary Wilbur Ross subsequently issued an order that would put Richwine in charge of the $1 billion research agency if NIST Director Walter Copan leaves or is fired. On 17 November, Representative Eddie Bernice Johnson (D–TX), who leads the science committee in the U.S. House of Representatives, asked Ross to justify the moves. Richwine has advocated for more restrictive immigration policies, and his 2009 doctoral thesis argued that lower IQ scores by Mexican and Hispanic immigrants suggest a genetic component to intelligence that is “likely to persist over several generations.” ### Diversity The editors of Nature Communications say they are reviewing a paper that drew scalding criticism after it suggested that encouraging female junior scientists to work with female mentors could “hinder the careers of women.” The 17 November study, led by data scientist Bedoor AlShebli of New York University, Abu Dhabi, examined 3 million mentor-protégé pairs and how gender influenced the impact of papers later published by the protégés. Female protégés, it concluded, did better if they worked with male mentors. Critics pounced, noting the authors ignored reviewer complaints about the study's methods and arguing the journal was promoting a harmful and unfounded message. The article's authors said they welcome the review. ### Animal diseases European authorities reported on 19 November they have detected highly pathogenic avian influenza in 302 birds in eight countries. Only 18 cases were in poultry; most of the rest were in wild birds, the European Food Safety Authority and its partners said. The number of infected birds is expected to rise with winter migrations. Several flu strains were identified, but no people were reported to be infected, and the risk of that occurring is considered low; researchers studying the viruses found no genetic markers indicating they had adapted to infect mammals. But the threat to poultry is high, and the report's authors recommended bird producers increase precautions against infections. VACCINE APPLICATION Days after making public the final analysis of their 40,000-person COVID-19 vaccine trial, which found 95% efficacy, Pfizer and its German partner BioNTech filed for emergency authorization of the messenger RNA vaccine from the U.S. Food and Drug Administration—the first such request for a vaccine during the pandemic. They plan to seek additional approvals in other countries soon. Pfizer hopes to supply up to 50 million doses this year. REMDESIVIR PANNED A World Health Organization panel recommended against using the antiviral drug remdesivir to treat most hospitalized COVID-19 patients. Its review of four studies of 7000 people found that the drug, which the U.S. Food and Drug Administration approved last month for hospitalized patients, did not reduce mortality or speed recovery. But the panel encouraged further study of it. AMMO BAN Denmark has become the first nation to ban all lead-based hunting ammunition, including bullets and shotgun pellets, to protect wildlife. Hunters annually release about 2 tons of lead into Denmark's environment; waterbirds and other species eat the toxic material and die. European regulators are considering a ban like Denmark's.

Like it or not, artificial intelligence (AI) is already part of our daily lives. From the smartphones in our pockets to the Alexa virtual assistants on our kitchen counters, AI and its applications are accepted norms today. While we appreciate that AI can automate repetitive workplace tasks or even drive a car, the reality is that its implications are much further reaching. Luminaries like Elon Musk and Bill Gates have spoken out about the potential downsides of AI. At times, they have even issued outright warnings.

On Thursday, 26 November, Prof. Andrew Murray, will deliver the Sixth T.M.C. Asser Lecture – 'Almost Human: Law and Human Agency in the Time of Artificial Intelligence'. Asser Institute researcher Dr. Dimitri Van Den Meerssche had the opportunity to speak with professor Murray about his perspective on the challenges posed by Artificial Intelligence to our human agency and autonomy – the backbone of the modern rule of law. A conversation on algorithmic opacity, the peril of dehumanization, the illusionary ideal of the'human in the loop' and the urgent need to go beyond'ethics' in the international regulation of AI. One central observation in your Lecture is how Artificial Intelligence threatens human agency. Could you elaborate on your understanding of human agency and how it is being threatened? In my Lecture I refer to the definition of agency by legal philosopher Joseph Raz. He argues that to be fully in control of one's own agency and decisions you need to have capacity, the availability of options and the freedom to exercise that choice without interference. My claim is that there are four ways in which the adoption and use of algorithms affect our autonomy, and particularly Raz's third requirement: that we are to be free from coercion. First, there is an internal and positive impact. This happens when an algorithm gives us choices, which have been limited by pre-determined values – values that we cannot observe. The second impact is internal and negative. In this scenario, choices are removed because of pre-selected values.