21st Century Learning and Teaching

When was the last time you saw a creepy ad on Facebook, which seemed to know about a product you were discussing with a coworker? Or when was the last time you noticed that your Google search had been modified to suit variables like your current location and personal interests?

These micro-events happen on a daily basis for most of us, and are reminders of how valuable and how ubiquitous our data really is. Data is the currency of the new world, and with 2.5 quintillion bytes of data created each day, that status isn’t going away anytime soon.

The problem is, data scientists and analysts are constantly talking about the potential for how to use this data, but too few are talking about the ethics. If we’re going to keep pushing for better systems built on big data, we need to democratize and popularize the ethical conversation surrounding them.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Ethics

https://gustmees.wordpress.com/2013/12/21/privacy-in-the-digital-world-shouldnt-we-talk-about-it/

https://www.scoop.it/t/securite-pc-et-internet/?&tag=tracking

https://www.scoop.it/t/securite-pc-et-internet/?&tag=Privacy

https://www.scoop.it/t/securite-pc-et-internet/?&tag=Big+Data

Growing of smart IoT has generated many major impacts on transportation development, of which one underlying big story is the thriving of big data driven smart transportation nowadays. We are moving from IT to data technology (DT) time, and we are entering a “results driven” era in transportation. As the front and center of the smart IoT transformed mobility, transportation data sets grow rapidly while they are increasingly gathered from more connected sensors, devices, actuators in real-world applications. In 2016, over 823.0 million air trip passengers were reported by U.S. airlines and over 25 million public transit trips was generated daily.  

The data traffic associated with mobility and transportation is estimated to be roughly 0.6 exabytes every month by 2020 (about 9 percent of total US wireless data traffic), and will grow to 9.4 exabytes every month by 2030. Although the quantity of the data available is indeed large, that is not the most striking characteristic of “big data” in the smart IoT era concerning transportation. The challenge in big data driven transportation rarely refers to the large volume or size of data; rather, it often refers to extracting value from data with certain innovative methods, i.e. how to analyze the data and to gather meaningful insights that can be used to inform decisions makers.

Many concurrent novel technologies and employments have emerged within the big data driven smart mobility ecosystem, emanating from the transportation needs of different stakeholders for better safety, reliability, sustainability, and automation.

For public transportation, big data analytics have transformed both the plan and operations phases on planning and demand modeling, predictive maintenance, and event response. New big data tech-savvy has brought more personalized services to public transportation users, such as offering ancillary services to providing recommendations about additional destinations to visit as part of an upgrade to the passenger’s journey, etc.

The big data driven smart public transportation influences both automated and human decision-making, which has clearly played a big part in re-energizing public transport network, and has offered plenty of opportunities to improve the public transportation experience with improved reliability and safety.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data..

Everyday, there are 4 million blog posts, 100,000 news articles and 500,000 hours of video published on the Internet. A wealth of information and knowledge. A wealth of information and knowledge that is lost for most companies, at least for the most part.

Lost?

Step 1: content curation
Not entirely. Thanks to content curation technology, the Web can now be filtered. With content curation tools and platforms such as Scoop.it (among others of course), we can use more or less sophisticated ways to filter this huge amount of content that is published daily to zoom in on what matters to us. Good content curation technology is essential. It saves people a huge amount of time looking for content to share for marketing purposes or information that helps their organization make better decisions. And perhaps as importantly, without these filters, we would just be able to search – not discover. We would still find answers to what we don’t know but we wouldn’t know what we don’t know.

But until recently, all the solutions we’ve offered to deal with information overload – ours included – have revolved around the same basic idea: more – or more sophisticated – filters.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Curation

De gros titres, tels que "Algorithmes - les vrais maîtres du monde ?" ou "Les algorithmes influencent-ils notre quotidien ?", sont à la une des journaux, notamment dans le contexte du Big Data. Dans ce dossier, nous expliquerons ce que sont les algorithmes, comment ils fonctionnent et à quoi ils servent. Nous aborderons également les aspects éthiques.

Un algorithme est une instruction ou une règle logique et explicite sur la manière dont un problème est à résoudre, et se compose de différentes étapes exécutées l'une après l'autre ou simultanément. Pour la majorité des algorithmes, une entrée donnée conduit toujours à la même sortie. Dans la plupart des cas, les algorithmes s'appliquent sous forme de logiciels informatiques, mais ils peuvent également être formulés en langage humain. L'exemple le plus illustre d'un algorithme de notre quotidien est une recette de cuisine.

D'où vient le nom ?

Le terme algorithme est dérivé du nom du mathématicien et géographe korasmien Muhammad Ibn Musa al-Khuwarizmi, originaire de la région de l'Iran d'aujourd'hui, qui a passé la majeure partie de sa vie à Bagdad. En 825, il écrit un manuel sur les chiffres indiens et y explique également le fonctionnement des algorithmes. Le livre sur les chiffres, que nous connaissons aujourd'hui sous le nom de "chiffres arabes", a été traduit en latin au 12e siècle. La dernière partie de son nom (al-Khuwarizmi) a été traduite par "Algorismi". Les premiers mots étaient "Dixit Algorismi" (Algorismi a dit), d'où s'est finalement dérivé le terme algorithme.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Algorithm

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

Big Data is powerful on its own. So is artificial intelligence. What happens when the two are merged?

Big data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the coming decade. As big data initiatives mature, organizations are now combining the agility of big data processes with the scale of artificial intelligence (AI) capabilities to accelerate the delivery of business value.

Big Data and AI at MetLife

Pete Johnson is one of the most experienced executives working in the field of big data and AI within industry today. Having worked in the field of artificial intelligence for a generation dating back to his academic career at Yale University, Johnson now leads big data and AI initiatives as a fellow at MetLife. Johnson previously held positions as senior vice president for Strategic Technology with Mellon Bank and served as the executive vice president and chief technology officer of Cognitive Systems Inc. (CSI), an early artificial intelligence company specializing in natural language processing, expert systems, case-based reasoning, and data mining. CSI was founded by several members of the Yale University faculty in 1981, when Johnson completed his MS in computer science.

Johnson, whom I’ve known for over a decade, is a regular participant in a series of executive thought-leadership breakfasts that I host for senior industry executives to share perspectives on topics in big data, AI, and machine learning among their peers. Participants in the most recent executive breakfasts have included chief data officers, chief analytics officers, chief digital officers, chief technology officers, and heads of big data for firms including AIG, American Express, Blackrock, Charles Schwab, CitiGroup, General Electric (GE), MetLife, TD Ameritrade, VISA, and Wells Fargo, among others.

As a long-suffering expert in the field of artificial intelligence, Johnson observes three critical ways in which big data is now empowering AI:

1. Big data technology — We have the ability now to process huge quantities of data that previously required extremely expensive hardware and software, or “commodity parallelism.”
2. Availability of large data sets — ICR, transcription, voice and image files, weather data, and logistics data are now available in ways that were never possible in the past; even old “paper sourced” data is coming online.
3. Machine learning at scale — “Scaled up” algorithms such as recurrent neural networks and deep learning are powering the breakthrough of AI.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=AI

https://www.scoop.it/t/21st-century-innovative-technologies-and-developments/?&tag=AI

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=machine+learning

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Deep+Learning

The concept of Big Data is a relatively new one. It denotes the availability of vast volumes and sources of data, which were not available before. By itself, Big Data is powerful, and when combined with Artificial Intelligence and machine learning, the opportunities presented by this combination are just endless.  As big data moves to the maturity phase, firms are now looking for ways to combine the scale of AI and the agility of Big Data processes to bring about an acceleration on the delivery of the much-needed business value.

The Power of Combining AI and Big Data
Most businesses are data-driven. As a result, firms with the right type and quantity of data has the upper hand over rivals. Convergence between AI and big data is promising. Firms can now access large volumes of broken down and categorized data by their usefulness. Traditional computer processors cannot process big data. Big data can best be processed by a GPU database, which has the flexibility needed to handle a significant amount of data of different types.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=AI

https://www.scoop.it/t/21st-century-innovative-technologies-and-developments/?&tag=AI

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

The best place to discover and seamlessly analyze open data

Big Data and Social Physics Understanding big data, how to use it to improve companies, cities, and government, and best-practice for privacy.

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http://www.scoop.it/t/21st-century-learning-and-teaching/?tag=Social+Physics

Machine learning can drive tangible business value for a wide range of industries — but only if it is actually put to use. Despite the many machine learning discoveries being made by academics, new research papers showing what is possible, and an increasing amount of data available, companies are struggling to deploy machine learning to solve real business problems. In short, the gap for most companies isn’t that machine learning doesn’t work, but that they struggle to actually use it.

How can companies close this execution gap? In a recent project we illustrated the principles of how to do it. We used machine learning to augment the power of seasoned professionals — in this case, project managers — by allowing them to make data-driven business decisions well in advance. And in doing so, we demonstrated that getting value from machine learning is less about cutting-edge models, and more about making deployment easier.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=machine+learning

FIGURE 1 J'ai montré dans un post précédent, l'importance contemporaine de la curation collaborative de données.  Les compétences dans ce domaine sont au coeur de la nouvelle litéracie algorithmique.

La figure 1 présente ces compétences de manière systématique et, ce faisant, elle met en ordre les savoir-faire intellectuels et pratiques tout comme les « savoir-être » éthiques…

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Curation

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Intelligence+collective

Big data analytics is the process of examining large and varied data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.

Big data can be analysed for insights that lead to better decisions and strategic business moves. The Big Data market is expected to grow to $66.79 Billion by 2021, with investment in analytics hardware, software, services and data scientists pouring in.

WHAT ARE THE INFLUENCERS SAYING?

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

Big data analytics can play a crucial role in helping patients get healthcare at a lower cost.

Today, healthcare costs are much higher than they should be and have been growing steadily over the past 20 years. In fact, according to a study by McKinsey, healthcare expenses represent nearly 17.6% of United States’ GDP. Due to the rising cost of healthcare, it’s time to look at smart, data-driven ideas.

From autonomous cars to Internet of Things, big data has percolated almost every industry. It’s no surprise that the healthcare industry, with its large amount of data, is on the verge of big data-driven transformation, perhaps more than any other field.

Healthcare analytics has the potential to reduce treatment costs, predict outbreak of epidemics as well as preventable diseases and improve the quality of life. Here are 5 examples of how big data analytics in healthcare can help save lives.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

À l’ère du Big Data, l’intelligence collective des êtres humains permet de générer de nombreuses données pour résoudre certains des principaux problèmes de l’humanité. De même, elle permet d’analyser certaines données plus efficacement que les algorithmes informatiques. Découvrez la relation étroite entre intelligence collective et Big Data.

Intelligence collective : définition

La notion d’intelligence collective désigne une intelligence de groupe, ou une intelligence partagée émergeant de la collaboration, des efforts collectifs ou de la compétition entre plusieurs individus. Cette intelligence collective permet de prendre des décisions par consensus. Les systèmes de vote, les réseaux sociaux, et les autres méthodes permettant de quantifier l’activité de masse peuvent être considérés comme des intelligences collectives.

L’intelligence collective peut être perçue comme une propriété émergente de la synergie entre le savoir offert par les données, les logiciels, le hardware informatique, et les experts de domaines spécifiques, permettant de prendre de meilleures décisions au moment opportun.

Plus simplement, l’intelligence collective résulte de l’association entre les humains et les nouvelles façons de traiter l’information.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Intelligence+collective

Manche sind genervt von ihnen, andere können gar nicht genug bekommen – Tests auf Facebook, die das eigene Profil analysieren und dabei Daten sammeln.

Wie soll ich mit solchen Tests umgehen? BEE SECURE rät:

Unzureichende Datenschutzerklärungen, intransparente Informationen und zweifelhafte Geschäftsmodelle bestimmen die „Szene“ dieser Tests. Da diese Tests so gut wie keinen Mehrwert haben, sondern vermutlich sowieso nach dem Zufallsprinzip arbeiten, empfiehlt BEE SECURE, sie zu meiden. Die Risiken, dass die eigenen Daten verkauft oder gar in Fake-Profilen verwendet werden, sind größer als der Nutzen, den diese „lustigen“ Tests bieten.

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https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

I wanted to share some recent work that we have been doing inside EMC Global Services, to create a “Big Data Storymap” that would help clients understand the big data journey in a pictorial format. The goal of a storymap is to provide a graphical visualization that uses metaphors and themes to educate our clients …

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http://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

A third of U.S. middle and high school students use mobile devices issued by their schools. Many others use their own devices for their schoolwork, using software such as the widely adopted Google Apps for Education. If you have children in school, chances are good that people and organizations you don’t know are collecting massive quantities of information about your children and using this information for purposes you know nothing about.

We don’t know much about how children’s information is used, or by whom, or for what purpose

Once data is collected and the company that collected it uses it for its stated purpose, there is little in law or policy that prevents the company from also using the information for other purposes, such as “product development.” It may also sell the information to others for their use or archive it for possible later use. Many bills bearing on student privacyhave been introduced in the past several years in Congress and state legislatures, and several of them have been enacted into law. However, protection of student privacy remains limited.

Our recent report explores how corporate entities use their involvement with schools to gather student data and how those data may be used for marketing and other non-school-related purposes. Although most people probably know that digital marketers targetand track children on the devices they use, many would be surprised to learn that schools now serve both as a portal to and reinforcer of digital marketing messages to children. In so doing, they lend companies that collect, sell, analyze, and buy data both enhanced credibility and access to vast amounts of education-related data.

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https://gustmees.wordpress.com/2013/12/21/privacy-in-the-digital-world-shouldnt-we-talk-about-it/