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Artificial intelligence in insurance: Where does Europe stand?

#artificialintelligence

Where does the European insurance industry stand in terms of advanced analytics, AI and automation? Do we see that traditional methods of data analysis are now being labeled by the term "machine learning"? Maybe the industry is more advanced than that: Are real chatbots, for example, already ubiquitous? Let's have a closer look. I had the opportunity to visit the "Insurance AI and Analytics Europe" conference in London.


Intelligent people have a higher risk of mental illness

Daily Mail

Intelligent people have double the risk of mental illness compared to their lesser-intelligent peers - and more often suffer anxiety-related physical woes, a new study has found. Researchers at Pitzer College screened 3,715 members of Mensa, the IQ society, for anxiety, depression, autism, ADHD and other disorders.All of the participants had an IQ over 130, significantly higher than the 85-115 average. The study revealed 20 percent of the intelligent group suffered anxiety and depression, compared to 10 percent of the general population. Intriguingly, the participants also seemed more susceptible to asthma, allergies and poor immunity. Experts say the study offers an unprecedented insight into the links between intelligence and mental illness, as well as the links between mood disorders and physical illnesses.


French scientists find anomaly in retinal cells that may be the cause of dyslexia

The Japan Times

PARIS – A duo of French scientists said Wednesday they may have found a physiological, and seemingly treatable, cause for dyslexia hidden in tiny light-receptor cells in the human eye. In people with the reading disability, the cells were arranged in matching patterns in both eyes, which may be to blame for confusing the brain by producing "mirror" images, the co-authors wrote in the journal Proceedings of the Royal Society B. In non-dyslexic people, the cells are arranged asymmetrically, allowing signals from the one eye to be overridden by the other to create a single image in the brain. "Our observations lead us to believe that we indeed found a potential cause of dyslexia," study co-author Guy Ropars of the University of Rennes, told AFP. It offers a "relatively simple" method of diagnosis, he added, by simply looking into a subject's eyes. Furthermore, "the discovery of a delay (of about 10 thousandths of a second) between the primary image and the mirror image in the opposing hemispheres of the brain, allowed us to develop a method to erase the mirror image that is so confusing for dyslexic people" -- using an LED lamp.


How we determine who's to blame

MIT News

How do people assign a cause to events they witness? Some philosophers have suggested that people determine responsibility for a particular outcome by imagining what would have happened if a suspected cause had not intervened. This kind of reasoning, known as counterfactual simulation, is believed to occur in many situations. For example, soccer referees deciding whether a player should be credited with an "own goal" -- a goal accidentally scored for the opposing team -- must try to determine what would have happened had the player not touched the ball. This process can be conscious, as in the soccer example, or unconscious, so that we are not even aware we are doing it.


The outcome of this virtual riot depends on your emotions

Engadget

In RIOT 2, an interactive film by Karen Palmer, controlling these emotions is the key to your escape. Yet the ongoing melding of games and film into interactive narratives raises the question of how we should control these new experiences naturally. "Conversation, facial expression, intonation of our voice, physical gesture -- all of those are the natural language of human interaction. "In my opinion, fear is the most powerful emotion," Palmer, originally from London, said.


Certificate in Introduction to Data Mining and Machine Learning using Python

@machinelearnbot

This is a programming oriented, hands-on training for starting a career in Data Mining and Machine Learning, and to acquire the necessary skills in statistical and inferential thinking. After this course, many of the things you read and hear about Data Science, Artificial Intelligence and Machine learning would make a lot more sense. The applications of this field span from marketing analysis and forecasts, predicting demands for products, making intelligent business decisions, cyber security and threat detection, predicting poll and survey results, and too many others to mention here. This course will enable participants to learn the foundation skills through programming, in arguably the most popular Data Science language today--Python.


No One Knows How to Define 'Self-Driving Car' -- And It's Becoming a Problem

WIRED

"Consumers every day are seeing this conflation of automated vehicles, self-driving vehicles, and autonomous vehicles," says Greg Rogers, a policy analyst with the transportation think tank the Eno Center. "If there's inconsistency with how things are named across different semiautonomous features that have different capabilities, that can lead to confusion for consumers both when they're purchasing systems and when they're using systems," says Hillary Abraham, who worked on the research and studies how humans interact with driver assistance systems at MIT. Engineers have specialized language for automation, a five-level system that explains what drivers are responsible for, and when. "This study should be a call to action--the industry needs to solve these issues," says Bryan Reimer, an MIT researcher who studies human driving behavior and worked on the research on brand names.


Bayesian Estimation of Signal Detection Models, Part 1

@machinelearnbot

First, we'll compute for each trial whether the participant's response was a hit, false alarm, correct rejection, or a miss. For a single subject, d' can be calculated as the difference of the standardized hit and false alarm rates (Stanislaw and Todorov 1999): Its inverse, \(\Phi {-1}\), converts a proportion (such as a hit rate or false alarm rate) into a z score. We can use R's proportion to z-score function (\(\Phi {-1}\)), qnorm(), to calculate each participant's d' and c from the counts of hits, false alarms, misses and correct rejections: This data frame now has point estimates of every participant's d' and c. The implied EVSDT model for participant 53 is shown in Figure 1. Figure 1: The equal variance Gaussian signal detection model for the first participant in the data, based on manual calculation of the parameter's point estimates.


The best way to tell how someone is feeling

Daily Mail

In the world of cognitive psychology, engaging in two complex tasks simultaneously hurts a person's performance on both tasks. In one case, participants listened to a computerized voice reading a transcript of an interaction - a condition without the usual emotional inflection of human communication. In one case, participants listened to a computerized voice reading a transcript of an interaction - a condition without the usual emotional inflection of human communication. In the world of cognitive psychology, engaging in two complex tasks simultaneously (i.e., watching and listening) hurts a person's performance on both tasks.


Why trust is key for AI adoption in consumer goods supply chain

#artificialintelligence

Despite a promising future, adoption of artificial intelligence (AI) in consumer goods manufacturing and supply chain management has been much slower than in the technology, retailing and financial services sectors due to a lack of data for analytic tools to work on, according to a supply chain expert. Lee noted that the application of AI in supply chain management has been slower than in other industries because industry participants are reluctant to share their operating data. To make data sharing work in the long supply chain of manufacturing, Lee said it was key to have a platform that allows all participants to share their data in a secured manner for mutual benefit. Still, Lee said even without the sharing of internal data such as retailer inventory and available factory production capacity, plenty of data is already available to Fung Group's supply chain management unit Li & Fung that can be used to add value and save costs.