AN AI READING LIST — FROM PRACTICAL PRIMERS TO SCI-FI SHORT STORIES

By TheWAY - 1월 31, 2019

AN AI READING LIST — FROM PRACTICAL PRIMERS TO SCI-FI SHORT STORIES

The best reading on AI, as recommended by the experts

Experts are already building a future world brimming with artificial intelligence, but here in the present most of us are still trying to figure out what AI even is. This is a technology that will influence many aspects of our lives, from jobs to entertainment to health care, but that also engages with fundamental questions about what it means to be human. Questions like, “what is the nature of creativity?” and “how do we define consciousness?” Posing the question “how can I understand AI?” is nearly as daunting as asking “what is the meaning of life?”

But as with that tricky life question, a sense of overawing complexity doesn’t mean we shouldn’t try.

In order to help, The Verge has assembled a reading list: a brief but diverse compendium of books, short stories, and blogs, all chosen by leading figures in the AI world to help you better understand artificial intelligence. It’s an eclectic selection that ranges from practical primers to Golden Age sci-fi, and while reading everything listed below won’t get you a job at Google (though it certainly couldn’t hurt), it will give you much-needed context for this confusing and exciting time.

So read, enjoy, and get to know the captivating world of AI a little bit better.

★ PROFILES OF THE FUTURE, BY ARTHUR C. CLARKE

Recommended by Greg Brockman and Ilya Sutskever, co-founders of OpenAI

Profiles of the Future, by Arthur C. Clarke
Graphic by Michele Doying / The Verge

“Profiles of the Future changed our beliefs about how rapidly AI might affect the world. We used to think of technological change as a gradual, slow process — the sum of many small innovations that, when zoomed out, create only the illusion of rapid technological change.

Profiles made us realize there are some highly important exceptions. While later chapters describe Arthur C. Clarke’s predictions about the future, early chapters analyze others’ predictions about technologies like airplanes, space travel, and nuclear power before their development. In each case, the technology was predicted by a small number of optimists amongst a very large, vocal set of genuinely accomplished experts who were confident that a particular dramatic technological advance would never be achieved (at least not on a practical timescale). As a result, even to most experts, massive technological change appeared to come ‘out of nowhere.’

How will long term progress in AI look? Will it follow a predictable trajectory, with the field having a clear view of the upcoming progress in the next 5-10 years, or will we stumble upon a surprising yet disproportionate advance in AI that will transform the world rapidly? The perspective in Profiles means these questions are worth pondering.”

★ THE BOOK OF WHY, BY JUDEA PEARL AND DANA MACKENZIE

Recommended by Rumman Chowdhury, Responsible AI lead at Accenture

Graphic by Michele Doying / The Verge

“An AI book with no robots, no doomsday scenarios, and no grandiose predictions of the future? How refreshing. This book’s humble and engaging writing style belies a deep hypothesis: the fundamental roots of our current systems of predictive modeling are wrong. According to the authors, we lack a language of causality; that is, quantifiable proof that one thing causes another. This is a fundamental weakness embedded in the history of statistics and tarnishes how we ask questions and seek answers.

The dirty secret of the AI and machine learning methods we use for prediction is that they cannot actually tell us with certainty whether some factor caused another, instead relying on millions of repetitions to give us high-value correlations. Many of our issues of biased outcomes in AI systems stem from an incomplete or poor understanding of interrelated variables (race and zip code, or socioeconomic status and education, for example). While still considered controversial (see Pearl’s debate with statistician Andrew Gelman on Twitter), The Book of Why presents a new narrative that questions and redefines the building blocks of our AI systems.”

★ “FRANCHISE,” BY ISAAC ASIMOV

Recommended by Tim Hwang, director of the Harvard-MIT Ethics and Governance of AI Initiative

“Franchise,” from If magazine, by Isaac Asimov
Graphic by Michele Doying / The Verge

“Asimov’s Robot series is perhaps the cliche reference that gets rolled out when talking about the social impact of artificial intelligence. It’s mostly a convenient excuse to repeat well-worn tropes about The Three Laws of Robotics and point out — sagely — that the dreams of building intelligent machines are long-standing.

But, the cliche misses the mark. In the Asimov oeuvre, it is the stories featuring the massive, impersonal Multivac — rather than the Robot series — that best capture the present day reality of machine learning. In contrast to the walking, talking robots of the Robot stories, Multivac is an unwieldy server farm that requires specialized expertise to operate and frequently produces outputs uninterpretable to the technicians that run it.

One story I’ve found myself revisiting over and over again is Asimov’s ‘Franchise,’ published as a short story in the August 1955 edition of If magazine. In it, a future America (2008), decides to reduce voting to a statistical model that extrapolates the outcomes of all elections based on a set of questions answered by one, extremely representative person.

‘Franchise’ deftly captures the weirdly recursive nature of prediction, and the personal stresses of being the focus of algorithmic analysis. Importantly, the story illustrates the real and tricky balance between predictability and legitimacy. Even if we could do a perfect job predicting voting behavior, or recidivism, or employment performance, what does it mean for this to be an automated process versus a human one? Give it a read.”

★ WEAPONS OF MATH DESTRUCTION, BY CATHY O’NEIL

Recommended by Kate Darling, Research Specialist at the MIT Media Lab

Weapons of Math Destruction, by Cathy O’Neil
Graphic by Michele Doying / The Verge

“At first, I wanted to recommend a speculative science fiction book. But sometimes our current reality is a more interesting dystopia. In January 2019, US Congresswoman Alexandria Ocasio-Cortez was ridiculed for claiming that algorithms can be biased. No matter your political affiliation, I think everyone can benefit from a basic understanding of the pitfalls in contemporary AI systems. This book, illustrated with fascinating (and terrifying) real-world examples, is a great primer on the algorithms and data that we’re using, the delegation of power to systems that can make or break people’s lives, and the completely disastrous ways that we get it all wrong. Cathy O’Neil is a mathematician and data scientist who went from academia to the world of Wall Street quants and later joined the Occupy Wall Street movement. Her acclaimed book covers the problems with algorithms in the finance industry, but also in the areas of criminal justice, employment, education, and many more. Many of the AI systems we’re currently deploying and are likely to use in the near future run into the issues that O’Neil highlights. This book should be required basic reading for anyone interested in artificial intelligence implementation.

★ THE DIAMOND AGE: OR, A YOUNG LADY’S ILLUSTRATED PRIMER, BY NEAL STEPHENSON

Recommended by Jeremy Howard, co-founder of fast.ai

The Diamond Age: Or, A Young Lady’s Illustrated Primer, by Neal Stephenson
Graphic by Michele Doying / The Verge

“The ‘Primer’ in the title refers to a leather-bound book. There are three Primers in existence, each one owned by a little girl. The primer is the greatest work of its creator, the top software engineer at the world’s most successful software company. Because, you see, it’s not an ordinary book; it is truly interactive, showing the reader exactly what they need at every moment, described in a way that is designed to maximize their interest. One of the three girls that owns a Primer is the protagonist, Nell, who after finding herself homeless discovers that the Primer has been teaching her all the skills she needs to survive, and to thrive. We follow her journey, guided by the Primer, from a little girl that’s lost everything, to a young woman who may just change the world.

I first read Diamond Age 20 years ago, and this message has stayed with me: technology can be harnessed to give opportunities to those that otherwise would not have them. As with all new technologies, there is today a knee-jerk reaction against ‘screens’ for children. There is no well-designed modern research to support this reaction. If we deny the opportunity to leverage technology in education, then we limit the best education to only those privileged enough to have access to the best teachers.

Our mission at fast.ai is to help provide access to AI tools and education to all. Technology is vital to this mission. Without it, our users and students wouldn’t have access to our online lessons and community, or the cloud compute platforms we rely on. However, I haven’t yet seen AI used to create a highly customized educational experience like the Primer. The technology foundations are largely in place now; it just needs someone to put them together. When that happens, we may hear of real-world stories like Nell’s.”

★ MACHINE LEARNING FOR HUMANS, BY VISHAL MAINI AND SAMER SABRI

Recommended by Demis Hassabis, co-founder and CEO of DeepMind

Machine Learning for Humans, by Vishal Maini and Samer Sabri
Graphic by Michele Doying / The Verge

“It’s surprisingly hard to recommend books about the nuts and bolts of AI that aren’t either too technical or too philosophical — I predict we’ll see a lot more over the next few years. I’d recommend Machine Learning For Humansas a good introduction that doesn’t require much prior knowledge, plus it’s free online. We were so impressed with it here [at DeepMind] that we ended up hiring one of its authors!

Another way to get to grips with AI is to use a subject you are more familiar with as a gateway. For example, most people know the basics of chess even if they haven’t played it much. Two expert chess players, Matthew Sadler and Natasha Regan, have just written a book called Game Changer about one of DeepMind’s recent research breakthroughs, AlphaZero, which learnt chess from scratch just by playing against itself to ultimately become the world’s strongest player. It’s one of the most comprehensive analyses of an advanced AI program ever undertaken and gives you a fascinating insight into how AI systems like AlphaZero work.”

★ SORTING THINGS OUT: CLASSIFICATION AND ITS CONSEQUENCES, BY GEOFFREY C. BOWKER AND SUSAN LEIGH STAR

Recommended by Meredith Whittaker, co-founder and co-director of the AI Now Institute at NYU

Sorting Things Out: Classification and its Consequences, by Geoffrey C. Bowker and Susan Leigh Star
Graphic by Michele Doying / The Verge

“This is an essential text for anyone grappling with issues of AI bias, fairness, and justice.

Whatever else they are, AI systems are systems of classification. In brief, they ‘learn’ what they know from data, and they use what they learn to classify what they ‘see.’ For example, an AI system for hiring might be taught what a ‘promising job candidate’ looks like by [inputting] videos of ‘successful workers.’ Show this AI system a candidate video, and it compares the video to its ‘successful worker’ composite, classifying the candidate as either promising, or not. Such systems are already in use, and the stakes are high: if, for instance, black women weren’t represented among the ‘successful workers’ training videos, then it’s unlikely the system would classify them as ‘promising’ and unlikely that a black woman would ever get hired.

Sorting Things Out engages with the politics and consequences of such classification practices, treating classification not as a reflection of ‘natural categories,’ but as a product of history, culture, and power in which ‘each category valorizes some point of view, and silences another.’ The book examines classification systems ranging from Apartheid South Africa’s racial passbook, which struggled to apply rigid racial categories to diverse human bodies, to the World Health Organization’s International Classification of Diseases, which requires a vast bureaucracy in its attempt to normalize cultural differences in the understanding of illness and health. By attending to these histories, the authors expose the contingency of categories we often take for granted, providing a foundational resource for understanding, critiquing, and contesting the AI systems that are currently automating classification across core social domains.”

★ THE MASTER ALGORITHM, BY PEDRO DOMINGOS

Recommended by James Vincent, AI and robotics reporter at The Verge

The Master Algorithm, by Pedro Domingos
Graphic by Michele Doying / The Verge

I’m obviously no luminary in the AI world, but as someone who covers this field for a living, I’ve read more than a few books to orient myself, so I do have some experience here. There are two titles in particular that hooked my interest early on and that I continue to recommend: The Master Algorithm, by Pedro Domingos, and Superintelligence, by Nick Bostrom.

Superintelligence is the book about the threat posed by artificial general intelligence, or AGI, written by Oxford philosophy professor Bostrom. It’s inspired some questionable pronouncements from tech leaders on the threat from killer robots (which deserve to be taken with a barrel of salt in my opinion), but is the best introduction I’ve read to the problem of making smart machines safe; a problem which applies whether they’re super-smart or actually quite dumb. And despite the gloomy topic, this non-fiction book is a surprisingly fun read, feeling closer to science fiction at times.

The Master Algorithm, meanwhile, is a broader read that provides an excellent introduction to the technical aspects of AI. It walks you through all the basic components and concepts, from evolutionary algorithms to Bayesian probability, while showing how machine learning as a field cross-pollinates with disciplines like neuroscience and psychology. Domingos occasionally, I think, overstates the raw power of AI (these aren’t magical systems; they’re often deeply flawed, as other books in our reading list illustrate), but even that is a good reminder of how the very potential of this technology can hypnotize.

SOURCE : https://www.theverge.com/2019/1/29/18200585/understand-ai-artificial-intelligence-reading-list-books-scifi

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Will Artificial Intelligence Soon Tell Us How To Live?

By TheWAY - 1월 30, 2019

Will Artificial Intelligence Soon Tell Us How To Live?

AI to advise us how to structure our days for the most fulfilling life?DEPOSITPHOTOS ENHANCED BY COGWORLD

“What people don’t realize is that we are on the verge of a paradigmatic shift in thinking on par with the Copernican Revolution,” says Dr. Angel Iscovich. “The way we make our most personal decisions—from our partners, to our health choices, to yes, even our daily routines— is going to transform due to the falling cost of data storage and rising computing power.”

If you only happened to glance at what Dr. Iscovich said, let me repeat the latter part as it bears further mention. According to him, in the future, AI will advise us how to structure our days for the most fulfilling life. It will literally tell us what to do for optimal living. Iscovich’s assertion comes as the result of a new book he is writing with six-time New York Times bestselling author Joe Garner and myself entitled, Time Bubble: The Art and Science of Routine.

An experienced CEO in the healthcare industry, Iscovich is chairman of the Board of Directors for Potentia Analytics, named in 2018 as one of the Top 10 Intelligence Solution Providers by Healthcare Tech. He received his post graduate training in Psychiatry from the Maine Medical Center in Portland, Maine. While serving as Associate Clinical Professor at the USC Keck School of Medicine in the LA County Medical Center, Iscovich became intrigued by the subject of routine from witnessing how humans behave in stressful environments, such as emergencies. “Interestingly, the harrowing E.R. frontline experience pales in many ways to the environment we all live in today,” says Iscovich. “It’s hard not to be absorbed — and disturbed — by the events of our times: mass killings and unpredictable violence; regional wars, which devastate whole countries, displacing millions; intolerance of others’ race or religious beliefs and personal freedoms. Then there’s political strife, which, as we all know, has become increasingly strident and belligerent. On top of these, we are bombarded daily with a barrage of stimuli and distractions, especially through our smartphones.”

Though Iscovich works in the tech sector, the very eye of the storm when it comes to perpetuating our 24/7/365 go-go culture, his new book bucks 21st century conventional wisdom by suggesting the best way to navigate our noisy new world is to reject constant novelty — to reduce the relentless pelting of fresh content minute by minute. Iscovich’s disruptive big idea is that we need to carve out mental space for ourselves away from the madding hubbub to bring order to our lives.

Case study after case study, cited in the book, bolsters Iscovich’s thinking, revealing humans not only require structure, they thrive in it. At every stage of life, people do best when following a routine or what he terms a “time-bubble.” A time-bubble is a kind of mental barrier between the world and the individual, comprised of the activities we choose to occupy our days.

According to Iscovich’s findings, when we stick to a plan — when we do the same things in a predictable fashion — we develop balance and wellbeing, despite the curve balls life throws at us. “The reality is, as biological organisms, our bodies and minds perform best when maintaining an equilibrium,” explains Iscovich. “We feel best when our environment is familiar, and our lives possess consistency.”

We need look no further than the case study of Angel Martinez to witness Iscovich’s theory in action. Prior to serving as Chairman of the Board of Deckers Brands (best known for Uggs and Tevas), Martinez co-founded Reebok. A high performer in the business world, Martinez’s achievements are especially impressive in light of his personal history. A native from Cuba, he didn’t see his parents for more than thirty-four years. His grandmother’s sister and her husband adopted him when he was three-years-old before fleeing to the US. Unfortunately, the Cuban revolution prevented his immediate family from joining him in the South Bronx for decades.

Bereft of a traditional support system and wanting to make his parents proud back home, Martinez vowed to succeed. He built a disciplined personal routine based on the physical act of running. “The summer of my freshman year, I decided I was going to run five miles every single day,” Martinez says. To hold himself accountable, he pledged that if he missed his quota, he would run ten miles to make up for it. “I had a job where I remember getting off at 4:30 p.m.,” says Martinez. “From there, I would go home, and by 5:00, I was off and running. I really had to hustle, too, because I had another job that began at 7:00 p.m., and I didn’t want to miss putting in the five miles I promised myself.”

As Iscovich recounts in the book, Martinez’s self-imposed time-bubble, centered around running, developed within him a strong work ethic, which later paid off handsomely. After graduating from college, he opened running-shoe stores in Mountain Valley and Alameda, which led to Reebok, a tremendously profitable company. Martinez’s example demonstrates Iscovich’s larger point: developing and living within a consistent routine can bring the body the balance it craves. Of course, another word for balance is homeostasis. And as biology informs us, all organisms on Earth strive for homeostasis: to find food when hungry, warmth when cold, shelter from the elements.

But humans strive for other things, too: meaning and fulfillment. The German philosopher Friedrich Nietzsche once wrote, “He who has a why to live can bear almost any how.” What’s different about the era we live in as opposed to Nietzsche’s 19th century, is that with the emergence of technology, in particular AI, we needn’t depend on our own brains to develop the best routine; instead we can outsource such decision-making to thinking machines. Why? As it turns out, computers know a lot more about us than we do.

Just consider the Fitbit. Nonjudgmental, available on demand, and endlessly patient, it contains an infallible record of our biometric data. Right now, many users only utilize their devices to monitor their health goals, whether they be getting better REM-sleep or walking a certain number of steps per day. But this only represents a tiny sliver of what’s possible when it comes to AI’s full range of capabilities. What distinguishes third-wave computing (today’s processors) from past computing epochs is their ability not merely to process complex calculations but to offer predictive insights.

Put simply: AI can learn from data sets to offer us helpful suggestions. Our computers can do our thinking for us.

Certainly, it might seem odd to turn to a computer to tell how us how to better live, but there is precedent behind this notion. Already, the AI-based traffic app Waze tells us which route to take to and from destinations. Similarly, dating sites like Match.com and eHarmony rely on algorithms backed by big data to determine romantic matches rather than something as analog as butterflies in the stomach.

It’s important to note turning to technology is not the only answer to solve the crisis humanity finds itself in. Iscovich’s book emphasizes the importance of creating a stable environment while pointing out AI is an invention created by human intelligence and therefore one of our greatest tools and assets. Still, outsourcing how we make life choices to a computer fits within a pattern of evolving thought processes surrounding decision-making. In the last few thousand years humans have shifted beliefs when it comes to which authorities to follow. Once upon a time, kings ruled us with “divine” authority from God. Later, we internalized our decision-making as religion lost its sway and modern liberalist ideas swept the world. However, in the future, it’s conceivable many of our choices will be influenced or made for us through algorithms based on data.

Recognizing our growing dependence on predictive technology, Iscovich is developing a software application offering various routines people could employ to bring balance to their lives — and even possibly attain something as subjective as purpose and meaning. “This idea isn’t as far-fetched as one might think,” says Iscovich. “AI requires data to work. It thrives on information. Our app would function similarly to a smartwatch, learning about a person all day long. It would take in biometric data, such as heart rate, blood pressure, and breathing rate to learn what’s working in a person’s life and what might be improved.”

Though the app is still in the early stages, Iscovich conceives of a time in the not too distant future when the technology works in tandem with users’ goals. For instance, after analyzing data, the app might suggest new ways to structure your own time-bubble. “It could recommend you break up your day by doing twenty-minute naps or meditations to lower your resting heart rate,” says Iscovich. “It could also get you out of your comfort zone, establishing new neural pathways by suggesting you do unusual activities. It might recommend you take the whole day off to visit a new city. Likewise, it could tell you to explore a museum to get inspired based on what it knows about your interests.”

Though the promise behind the app is its ability to know us better than ourselves and therefore suggest ways to live more happily, it might feel like relying on AI to plan one’s life is akin to cheating. After all, “Know thyself” is the commandment Socrates, the father of Philosophy, once extolled. If humanity’s search for meaning comprises a never-ending struggle to gain knowledge and wisdom through experience and introspection, what happens to us once we let an artificial mind steer the ship? Is this not an abdication of our duties to ourselves? Maybe. But not necessarily.

Burdened by arduous responsibilities, jobs, and duties, existence in the 21st century is far from a walk in the park, even for the most affluent of us. Recognizing how AI-enhanced apps are already optimizing our lives and even saving them in some cases, is it too crazy to believe our computers might one day dream up better modes of living for us? “In my clinical practice, I saw so many patients dissatisfied by the ways their lives were going,” says Iscovich. “They were lost, confused. Miserable. So many of us feel alone and sad today. Why not turn to outside assistance?”

Certainly, technology is no panacea for all of the problems we face as a society and as people. Moreover, even if Iscovich succeeds in developing an app for suggesting our ideal routines, there will never be an app that can live our lives for us. Existence itself will continue to be our privilege — and our burden — as thinking carbon-based creatures. However, with the growing power of AI to improve our quality of life, a time-bubble app just might bring us greater balance, meaning, and happiness.

SOURCE : https://www.forbes.com/sites/cognitiveworld/2019/01/27/will-artificial-intelligence-soon-tell-us-how-to-live/#7c3a55f52938

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Will big data make everyone healthier?

By TheWAY - 1월 28, 2019

Will big data make everyone healthier?

New Zealand’s first ever health conference looking at artificial intelligence was organised to give the health system “a shake-up”.

Dr Marise Stuart, an organiser of the Hack Aotearoa conference, said New Zealand’s heath system needed to “pick up its game” in the use of artificial intelligence (AI). Last week’s conference explored how predictive data, smart technologies and robotics could improve the health of New Zealanders.

“There’s a junior doctors' strike going on now and a lot of that could be prevented by having good IT because junior doctors spend so much of their time typing. That’s just one small snag in the health system that AI could hugely have an effect on.”

Over two days, the 200-plus attendees heard examples from overseas and local speakers of how AI could assist doctors, as well as of risks involved with collecting and using data.

Scripps Research Translational Institute Professor Eric Topol, described as a guru in digital medicine, said the human side of technology was helping us to understand it better than ever before.

“All these layers of information, the physiology from sensors, the anatomy from scans, the different biologic layers from DNA, protein, metabolites, the microbiomes, the epigenome. If we can have all these layers of information for any given person, we could deliver far better care and prevention.”

Computers being able to pick up information from eye scans when humans couldn't was a good example, Topol said.

“If you give international retina specialists a photograph of the retina and you ask them 'Is this from a male or a female?', the response is 50-50. They can’t do any better than that. For deep learning algorithms the accuracy is 97 percent. That’s pretty astounding.”

Another example was detecting an eye disease related to diabetes. Diabetic retinopathy can lead to blindness and is often underdiagnosed. An AI system capable of recognising 90 percent of diabetic retinopathy cases has now been developed.

“Now the receptionist in a doctor’s office can obtain retinal images and through deep learning and cloud-based analytics the determination of what grade of retinopathy can be determined."

However, Topol feels the hype of AI has exceeded the science.

“We’re short on validation and long on promise. Ultimately we would like to see the implementation, which really hasn’t started except in a few pockets around the world.”

He stressed the need for peer-reviewed studies and real-world, clinical validation.

“If you feed a computer biased data, you’re going to have biased algorithms."

A challenge for AI is that healthcare's existing risks could be exacerbated depending on the data used to train an AI system. In a paper published in Nature, Topol gave the example of algorithms used to diagnose melanoma which lack the inclusion of skin colour.

Massachusetts Institute of Technology Laboratory clinical research director and principal research scientist Dr Leo Celi works with data and algorithms. The topic of algorithms working for all populations is close to his heart.

“If you feed a computer biased data, you’re going to have biased algorithms. Every time we create a model, we make sure the model is performing consistently across different populations.”

This testing needed to be repeated to ensure it kept its accuracy over time, and algorithms shouldn't be patented because they have a limited application, Celi said. Instead, revenue for algorithm creators should lie in continuously testing and recalibrating an algorithm, he said.

“Data collection without reciprocity begins to look a lot like surveillance.”

Another focus of the Hack Aoteroa conference was Māori health, and how big data could be used in an intelligent way to “hack” the health system to improve it.

Andrew Sporle, a Māori researcher who reviews big data projects, shared concerns around the use of data.

“Māori death rates are still 1.8 times higher than non-Māori. Is that due to the healthcare system? Well, yes.”

He said more of the same would not solve inequity: “We need to focus on disparities, or we risk making them worse.”

Collecting data now could help prevent problems for Māori youth as they age. However, Sporle urged caution around this.

“We need to start thinking about what is the process of this engagement? Is it based on social licence? Or is it a basis of partnership or ownership and control?

“The top-down approach we’ve had so far hasn’t delivered.”

A Treaty model based on engaged partnership was what we needed.

“Data collection without reciprocity begins to look a lot like surveillance.”

Without clear benefits, and results matching the hype, he worried it would be “game over” for funding, and for people’s willingness to share their data.

New Zealand’s biggest insurer - and holder of many years’ worth of injury data - was a major sponsor of the event.

Accident Compensation Corporation CEO Scott Pickering said the use of data had become more critical in ACC's day-to-day operations.

“We are part of the wider trend in insurance, shifting from detect and repair to predict and prevent. We’re spending millions more on injury prevention each year and we are increasing the use of our data analytics.”

Data about injuries that happened within hospitals while patients were receiving treatment could be used to stop future hospital-caused injuries, Dr Leo Celi told the conference.

“You could build a system where an algorithm could in real-time predict a treatment injury," said Celi.

“Nothing exists in the world like this.”

SOURCE : https://www.newsroom.co.nz/2019/01/21/407803/will-big-data-make-everyone-healthier

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How Big Data Triggered Travel Industry Success?

By TheWAY - 1월 27, 2019

How Big Data Triggered Travel Industry Success?

MEETING INFORMATION NEED OF TRAVEL INDUSTRY

In this world of modernization, every industry is working by depending upon some kind of information. The foremost thing which is kept in mind in pursuit of their goals is accurate information. One of the major service industry is travel industry and therefore need for the information is larger for this industry. You can say that the travel industry majorly depends on accurate data related to various aspects. A larger amount of Information through Big Data has changed various aspects of the business industry, research and studies etc. The company collects information from Big Data, process that in organized form through travel portal development and uses that in the day to day operations.

The industry is getting conscious about the collection of required information from various sources. Information may be related to accommodation, flight booking, vehicle, tourism, and other areas. Information works as a success-oriented asset for the travel industry. The enormous increase in the number of travelers increases the feedback and suggestion from them. Travelers help companies to grow faster than their competitors. Several companies engaged in the travel industry got an opportunity to grow. To achieve growth become possible with efficient use of information. It is necessary for the companies to find out which of the collected information is suitable and which is not.

Here are some advantages of Big Data analytics for travel industry

Increased Customer Experience

The information collected from the user helps companies to give them a user-friendly experience. The enhanced implementation of Big Data in the travel sector made the booking and exploration easy for travelers. Also, brought an opportunity to give more customized experience to the user. With larger database companies are able to provide best hotel booking at affordable price, best flight booking engine for cheapest fare and much more info.

Pricing Policies

Pricing is a significant part when a traveler thinks for a journey. The Big Data analyzer search for the rival data such as trends in the market, what competitors offering etc. The information technology made it possible for the company to go for automated process and develop continuity in pricing policies and user experience. The customer always looks for the best service at affordable prices. A great analysis of the market helps companies to develop customer-oriented pricing policies. Ultimately the only customer will bring success.

Differentiated Services

To withstand in the competition it is necessary to show some uniqueness in your services. Along with this, it should be the motive of the company to make travel easier and wonderful for traveler. With the efficient and effective use of information, companies can show some differentiation in their services and attract more customers than before through effective travel portal development. The unique features in your services further help in customer happiness, increase in surplus and increase in customer visits on website.

Integrity And Enhanced Commercial Policies

The integrity of the company is the most valuable asset to gain customer confidence. To do so the company needs to be in touch with their customer on a timely basis to get accurate information. The better knowledge of the customer helps in building strong policies for advertisement and promotion of their travel products. The policies help in retaining existing customer along with attracting more customers. The more affordable services company will provide more will be the growth rate and goodwill of the business. The Big Data helps to provide the right direction to all the information beneficial for the travel industry.

Understand Customer Travel Needs

The most important thing for the travel industry is to ascertain changes in the customer need. Through help of Big Data companies are becoming able to understand the customer need and made efforts to meet them. There are different analyser for airline database, customer reviews, and social representation to show search results as per traveler requirement. The airline analytic helps to advance the flight booking engine. Big data offered companies what they looking for such as info of hotel, air and other data.

Challenges A Travel Company Face With Information

Users always left the path for information when they take a journey , makes the booking online , details of the journey stores in the database and connected through GPS throughout the journey. Updated information increases personalized experience of customer. The collection of updated information is not an easy task, it requires time and skills.

Here are the major problems faced by travel company with information

Inadequate data

This is one of the biggest challenge travel industry facing these days. Travel industry is the major one and generates a huge amount of data. Due to competition in the industry timely processing of accurate info is needed to gain profit. Selecting adequate data from wide amount of data takes time and huge investment of the company which may result in losing opportunity.

Use of Internet

A major part of the population is using internet. The companies find the opportunities to connect with their customer anywhere but this also bring challenges with it. The use of excess devices by customer leaves huge amount of the data in the company database which is a difficult task to manage.

Organisational Arrangement

The rise of technology brought changes in the working style of companies. Now everything is digitalized which is ultimately a challenge. Digitalisation increases the need for travel technology company along with cultural changes towards data. In case of airline industry cultural changes require effective flight booking engine, advance employee skills, increased customer experience and improved working efficiency of flights along with huge investment.

Faster Speed

The travel sector covers every part of the traveler journey. For covering every part we need advanced technology. The multiple factors affects the travel planning of a customer such as climate, fare, hotel charges etc.Travel company needs to take care of the customer uninterrupted experience, faster response and confidence of customer in services. Everything brings a challenge for the companies.

SOURCE : https://thriveglobal.com/stories/how-big-data-triggered-travel-industry-success/

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