The tools that have delivered are specific, targeted solutions that are easy to use and provide teachers and students delight. Simple solutions, like Read 180, which helps accelerate learning for struggling students, still deliver 20 years later, now under Houghton Mifflin Harcourt instead of Scholastic. Accelerated Reader, a product that started more than 30 years ago, still motivates kids to read.
Companies that aim to provide student data in a usable fashion, like Schoology, still provide value.
the promise of data in education is still proving itself. It has taken awhile, but we’re getting to a point where data is more actionable. Renaissance just acquired Schoolzilla, which was launched in 2011, for this reason.
When it comes to devices, many kids today have access to iPads or Chromebooks. Although one-to-one computing hasn’t been as transformational as some predicted in 2010, we’ve certainly seen a huge shift
Most of these [textbook providers] companies tried to re-platform every unique product into one monolithic model, but the promise didn’t pan out—the products proved clunky and hard to use
Predictions that educators would want more assessment data to drive instruction have proven true. https://www.renaissance.com/
The prediction that digital reading would be simple and easy to implement has also proven true.
Virtual reality hasn’t panned out yet.
The rise of gaming in education was another prediction that has largely faded.
started to solve the challenge of data interoperability and portability.
Alongside that, privacy and data responsibility are still a problem
The role of the teacher, however, is still critical. Rather than take over responsibility for educating students, technology’s role should be—and increasingly is—to put multiple options into educators’ hands to easily solve different types of challenges for individual students.
The relationship between teens, screens and mental health is complex and multidirectional
Abby’s mom has sent her articles about research linking teen depression and suicide to screen use. A 2017 article in The Atlantic magazine — “Have Smartphones Destroyed a Generation?” — drew a link between negative trends in teens’ mental health and the rise of smartphones and social media.
The negative relationship between teens’ mental health and technology use is real — but tiny, the researchers found. “A teenager’s technology use can only predict less than 1% of variation in well-being. It’s so small that it’s surpassed by whether a teenager wears glasses to school.”
How to strike a balance? To start, try mentoring, not monitoring
Heitner’s work emphasizes a concept that’s also put forth by the American Academy of Pediatrics in its guidelines for parents: media mentoring.
Look for the good in your kids’ media interests
For Benji, Minecraft is a social space where he plays with other kids and pulls pranks. He says he wishes his parents understood more about his screen use — “why it’s entertaining and why we want to do it. And also, for YouTube, why I watch other people playing games. When you watch sports, you’re watching another person playing a game! Why is it so different when you’re watching a person play a video game?”
With the incorporation of cloud-based tools, K–12 schools are starting to consider more effective privacy and security measures, such as identity access management and managed cloud services from third-party vendors that can take responsibility for overseeing security.
Way back in 1983, I identified A.I. as one of 20 exponential technologies that would increasingly drive economic growth for decades to come.
Artificial intelligence applies to computing systems designed to perform tasks usually reserved for human intelligence using logic, if-then rules, decision trees and machine learning to recognize patterns from vast amounts of data, provide insights, predict outcomes and make complex decisions. A.I. can be applied to pattern recognition, object classification, language translation, data translation, logistical modeling and predictive modeling, to name a few. It’s important to understand that all A.I. relies on vast amounts of quality data and advanced analytics technology. The quality of the data used will determine the reliability of the A.I. output.
Machine learning is a subset of A.I. that utilizes advanced statistical techniques to enable computing systems to improve at tasks with experience over time. Chatbots like Amazon’s Alexa, Apple’s Siri, or any of the others from companies like Google and Microsoft all get better every year thanks to all of the use we give them and the machine learning that takes place in the background.
Deep learning is a subset of machine learning that uses advanced algorithms to enable an A.I. system to train itself to perform tasks by exposing multi-layered neural networks to vast amounts of data, then using what has been learned to recognize new patterns contained in the data. Learning can be Human Supervised Learning, Unsupervised Learningand/or Reinforcement Learning like Google used with DeepMind to learn how to beat humans at the complex game Go. Reinforcement learning will drive some of the biggest breakthroughs.
Autonomous computing uses advanced A.I. tools such as deep learning to enable systems to be self-governing and capable of acting according to situational data without human command. A.I. autonomy includes perception, high-speed analytics, machine-to-machine communications and movement. For example, autonomous vehicles use all of these in real time to successfully pilot a vehicle without a human driver.
Augmented thinking: Over the next five years and beyond, A.I. will become increasingly embedded at the chip level into objects, processes, products and services, and humans will augment their personal problem-solving and decision-making abilities with the insights A.I. provides to get to a better answer faster.
Technology is not good or evil, it is how we as humans apply it. Since we can’t stop the increasing power of A.I., I want us to direct its future, putting it to the best possible use for humans.
distributed computing + power encryption = the future of Internet
the Dark Net is going mainstream, liberty, freedom, democracy; neither entirely dark, not entirely light, both things
The threat that tech monopolies pose to democracies is about more than the prices they charge: it’s the concentration of power, data and control over the public space — and their ability to wield this power over a growing number of economic activities, especially in the infrastructure and technologies of the future. The following companies operate as either monopolies or oligopolies in their respective fields: Google, Facebook, Uber, Airbnb, Amazon, Twitter, Instagram, Spotify. Integrated into everything, everywhere, their technology will blanket the world.
cultural hegemony.” That is, where domination can be achieved through controlling the ideas and assumptions available to the public. The idea, associated with philosopher and politician Antonio Gramsci
In 1995, left-wing academics Richard Barbrook and Andy Cameron detailed the philosophy and ideas of the new tech wunderkinds, christening it “The Californian Ideology.” This ideology represented a fusion of the cultural bohemianism of San Francisco and entrepreneurial free market zeal.
All you needed to get to utopia was a belief in “disruption,” the idea that progress is achieved through smashing up old industries and institutions and replacing them with something new and digital.
Money and ideas in Silicon Valley have a very complicated relationship. Silicon Valley runs according to a Faustian pact: money in exchange for world-changing ideas.
Over the years, the big tech firms have very carefully cultivated the Californian Ideology. Even though they are massive multi-billion-dollar corporations with huge PR teams, they pitch themselves as anti-establishment.The worse these companies behave and the richer they become, the more they spend on looking cool and talking about fairness and community.
And to whom do we look in order to solve our collective social problems? It’s no longer the state, but the modern tech-geek superhero.
Total victory for the monopoly is not over economics or politics. It’s over assumptions, ideas and possible futures.
When: Friday, September 28, 8:30am-3:00pm Where: Wilson Research Collaboration Studio, Wilson Library Cost: Free; advanced registration is required
1968 was one of the most turbulent years of the 20th century. 2018 marks the 50th anniversary of that year’s landmark political, social and cultural events–events that continue to influence our world today.
Focusing on the importance of this 50 year anniversary we are calling out to all faculty, staff, students, and community partners to participate the workshop ‘Mapping 1968, Conflict and Change’. This all-day event is designed to bring people together into working groups based on common themes. Bring your talent and curiosity to apply an interdisciplinary approach to further explore the spatial context of these historic and/or current events. Learn new skills on mapping techniques that can be applied to any time in history. To compliment the expertise that you bring to the workshop, working groups will also have the support of library, mapping, and data science experts to help gather, create, and organize the spatial components of a given topic.
Workshop sponsors: Institute for Advanced Studies (IAS), U-Spatial, Liberal Arts Technologies & Innovation Services (LATIS), Digital Arts, Science & Humanities (DASH), and UMN Libraries.
Henneping County scanned the deeds, OCR, Python script to search. Data in an open source. covenant data. Local historian found microfishes, the language from the initial data. e.g. eugenics flavor: arian, truncate.
storymaps.arcgis.com/en/gallery https://storymaps.arcgis.com/en/gallery/#s=0 cloud-based mapping software. ArcGIS Online. organizational account for the U, 600 users. over 700 storymaps creates within the U, some of them are not active, share all kind of data: archive data on spreadsheet, but also a whole set of data within the software; so add the data or use the ArcGIS data and use templates. web maps into the storymap app, Living Atlas: curated set of data: hunderd sets of data, from sat images, to different contents. 846 layers of data, imagery, besides org account, one can create maps within the free account with limited access. data browser to use my own data – Data Enrichment to characterized my data. census data from 2018 and before,
make plan, create a storyboard, writing for the web, short and precise (not as writing for a journal), cartographic style, copyright, citing the materials, choosing the right map scale for each page. online learning materials, some only thru org account ESRI academy has course catalogue. Mapping 101, Dekstop GIS 101, Collector 101, Imagery 101, SQL 101, Story Maps 101,
The “Mapping 1968, Conflict and Change” planning committee is very pleased with the amount of interest and the wonderful attendance at Friday’s gathering. Thank you for attending and actively participating in this interdisciplinary workshop!
To re-cap and learn more on your thoughts and expectations of the workshop we would be grateful if you can take a few moments to complete the workshop evaluation. Please complete the evaluation even if you were unable to attend last Friday, there are questions regarding continued communication and the possibility for future events of this kind.
U.S. retail giant Walmart has applied to the U.S. Patent & Trademark Office (USPTO) to patent a blockchain system for deliveries, according to an official patent document released August 30.
Walmart has applied for a number of blockchain-related patents in the U.S. in the past year. According to Investopedia, blockchain technology enhancement is mainly being used by the retailed in order to “help Walmart keep pace with its rivals,” such as Amazon.
Recently, Walmart applied for a patent on systems and methods for managing smart appliances via blockchain. The tech would allow users to customize levels of access and control for appliances such as portable computing devices.
In mid-July, the retail giant patented the technology for a blockchain-powered delivery management system that can keep delivered items safe until their purchasers are able to sign for and collect them.
Between the “dumb” fixed algorithms and true AI lies the problematic halfway house we’ve already entered with scarcely a thought and almost no debate, much less agreement as to aims, ethics, safety, best practice. If the algorithms around us are not yet intelligent, meaning able to independently say “that calculation/course of action doesn’t look right: I’ll do it again”, they are nonetheless starting to learn from their environments. And once an algorithm is learning, we no longer know to any degree of certainty what its rules and parameters are. At which point we can’t be certain of how it will interact with other algorithms, the physical world, or us. Where the “dumb” fixed algorithms – complex, opaque and inured to real time monitoring as they can be – are in principle predictable and interrogable, these ones are not. After a time in the wild, we no longer know what they are: they have the potential to become erratic. We might be tempted to call these “frankenalgos” – though Mary Shelley couldn’t have made this up.
Twenty years ago, George Dyson anticipated much of what is happening today in his classic book Darwin Among the Machines. The problem, he tells me, is that we’re building systems that are beyond our intellectual means to control. We believe that if a system is deterministic (acting according to fixed rules, this being the definition of an algorithm) it is predictable – and that what is predictable can be controlled. Both assumptions turn out to be wrong.“It’s proceeding on its own, in little bits and pieces,” he says. “What I was obsessed with 20 years ago that has completely taken over the world today are multicellular, metazoan digital organisms, the same way we see in biology, where you have all these pieces of code running on people’s iPhones, and collectively it acts like one multicellular organism.“There’s this old law called Ashby’s law that says a control system has to be as complex as the system it’s controlling, and we’re running into that at full speed now, with this huge push to build self-driving cars where the software has to have a complete model of everything, and almost by definition we’re not going to understand it. Because any model that we understand is gonna do the thing like run into a fire truck ’cause we forgot to put in the fire truck.”
Walsh believes this makes it more, not less, important that the public learn about programming, because the more alienated we become from it, the more it seems like magic beyond our ability to affect. When shown the definition of “algorithm” given earlier in this piece, he found it incomplete, commenting: “I would suggest the problem is that algorithm now means any large, complex decision making software system and the larger environment in which it is embedded, which makes them even more unpredictable.” A chilling thought indeed. Accordingly, he believes ethics to be the new frontier in tech, foreseeing “a golden age for philosophy” – a view with which Eugene Spafford of Purdue University, a cybersecurity expert, concurs. Where there are choices to be made, that’s where ethics comes in.
our existing system of tort law, which requires proof of intention or negligence, will need to be rethought. A dog is not held legally responsible for biting you; its owner might be, but only if the dog’s action is thought foreseeable.
model-based programming, in which machines do most of the coding work and are able to test as they go.
As we wait for a technological answer to the problem of soaring algorithmic entanglement, there are precautions we can take. Paul Wilmott, a British expert in quantitative analysis and vocal critic of high frequency trading on the stock market, wryly suggests “learning to shoot, make jam and knit”
The venerable Association for Computing Machinery has updated its code of ethics along the lines of medicine’s Hippocratic oath, to instruct computing professionals to do no harm and consider the wider impacts of their work.
