Blended Reality, a cross-curricular applied research program through which they create interactive experiences using virtual reality, augmented reality and 3D printing tools. Yale is one of about 20 colleges participating in the HP/Educause Campus of the Future project investigating the use of this technology in higher education.
Interdisciplinary student and professor teams at Yale have developed projects that include using motion capture and artificial intelligence to generate dance choreography, converting museum exhibits into detailed digital replicas, and making an app that uses augmented reality to simulate injuries on the mannequins medical students use for training.
The perspectives and skills of art and humanities students have been critical to the success of these efforts, says Justin Berry, faculty member at the Yale Center for Collaborative Arts and Media and principal investigator for the HP Blended Reality grant.
Artificial intelligence and mixed reality have driven demand in learning games around the world, according to a new report by Metaari. A five-year forecast has predicted that educational gaming will reach $24 billion by 2024, with a compound annual growth rate of 33 percent and a quadrupling of revenues. Metaari is an analyst firm that tracks advanced learning technology.
Many educational institutions maintain their own data centers. “We need to minimize the amount of work we do to keep systems up and running, and spend more energy innovating on things that matter to people.”
what’s the difference between machine learning (ML) and artificial intelligence (AI)?
Jeff Olson: That’s actually the setup for a joke going around the data science community. The punchline? If it’s written in Python or R, it’s machine learning. If it’s written in PowerPoint, it’s AI.
machine learning is in practical use in a lot of places, whereas AI conjures up all these fantastic thoughts in people.
What is serverless architecture, and why are you excited about it?
Instead of having a machine running all the time, you just run the code necessary to do what you want—there is no persisting server or container. There is only this fleeting moment when the code is being executed. It’s called Function as a Service, and AWS pioneered it with a service called AWS Lambda. It allows an organization to scale up without planning ahead.
How do you think machine learning and Function as a Service will impact higher education in general?
The radical nature of this innovation will make a lot of systems that were built five or 10 years ago obsolete. Once an organization comes to grips with Function as a Service (FaaS) as a concept, it’s a pretty simple step for that institution to stop doing its own plumbing. FaaS will help accelerate innovation in education because of the API economy.
If the campus IT department will no longer be taking care of the plumbing, what will its role be?
I think IT will be curating the inter-operation of services, some developed locally but most purchased from the API economy.
As a result, you write far less code and have fewer security risks, so you can innovate faster. A succinct machine-learning algorithm with fewer than 500 lines of code can now replace an application that might have required millions of lines of code. Second, it scales. If you happen to have a gigantic spike in traffic, it deals with it effortlessly. If you have very little traffic, you incur a negligible cost.
In 2018 we witnessed a clash of titans as government and tech companies collided on privacy issues around collecting, culling and using personal data. From GDPR to Facebook scandals, many tech CEOs were defending big data, its use, and how they’re safeguarding the public.
1. Companies will face increased pressure about the data AI-embedded services use.
2. Public concern will lead to AI regulations. But we must understand this tech too.
In 2018, the National Science Foundation invested $100 million in AI research, with special support in 2019 for developing principles for safe, robust and trustworthy AI; addressing issues of bias, fairness and transparency of algorithmic intelligence; developing deeper understanding of human-AI interaction and user education; and developing insights about the influences of AI on people and society.
This investment was dwarfed by DARPA—an agency of the Department of Defence—and its multi-year investment of more than $2 billion in new and existing programs under the “AI Next” campaign. A key area of the campaign includes pioneering the next generation of AI algorithms and applications, such as “explainability” and common sense reasoning.
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Artificial intelligence (AI) and machine learning are no longer fantastical prospects seen only in science fiction. Products like Amazon Echo and Siri have brought AI into many homes,
Kelly Calhoun Williams, an education analyst for the technology research firm Gartner Inc., cautions there is a clear gap between the promise of AI and the reality of AI.
Artificial intelligence is a broad term used to describe any technology that emulates human intelligence, such as by understanding complex information, drawing its own conclusions and engaging in natural dialog with people.
Machine learning is a subset of AI in which the software can learn or adapt like a human can. Essentially, it analyzes huge amounts of data and looks for patterns in order to classify information or make predictions. The addition of a feedback loop allows the software to “learn” as it goes by modifying its approach based on whether the conclusions it draws are right or wrong.
AI can process far more information than a human can, and it can perform tasks much faster and with more accuracy. Some curriculum software developers have begun harnessing these capabilities to create programs that can adapt to each student’s unique circumstances.
GoGuardian, a Los Angeles company, uses machine learning technology to improve the accuracy of its cloud-based Internet filtering and monitoring software for Chromebooks. (My note: that smells Big Brother).Instead of blocking students’ access to questionable material based on a website’s address or domain name, GoGuardian’s software uses AI to analyze the actual content of a page in real time to determine whether it’s appropriate for students. (my note: privacy)
serious privacy concerns. It requires an increased focus not only on data quality and accuracy, but also on the responsible stewardship of this information. “School leaders need to get ready for AI from a policy standpoint,” Calhoun Williams said. For instance: What steps will administrators take to secure student data and ensure the privacy of this information?
despite China’s many technological advances, in this new cyberspace race, the West had the lead.
Xi knew he had to act. Within twelve months he revealed his plan to make China a science and technology superpower. By 2030 the country would lead the world in AI, with a sector worth $150 billion. How? By teaching a generation of young Chinese to be the best computer scientists in the world.
Today, the US tech sector has its pick of the finest minds from across the world, importing top talent from other countries – including from China. Over half of Bay Area workers are highly-skilled immigrants. But with the growth of economies worldwide and a Presidential administration hell-bent on restricting visas, it’s unclear that approach can last.
In the UK the situation is even worse. Here, the government predicts there’ll be a shortfall of three million employees for high-skilled jobs by 2022 – even before you factor in the immigration crunch of Brexit. By contrast, China is plotting a homegrown strategy of local and national talent development programs. It may prove a masterstroke.
In 2013 the city’s teenagers gained global renown when they topped the charts in the PISA tests administered every three years by the OECD to see which country’s kids are the smartest in the world. Aged 15, Shanghai students were on average three full years ahead of their counterparts in the UK or US in maths and one-and-a-half years ahead in science.
Teachers, too, were expected to be learners. Unlike in the UK, where, when I began to teach a decade ago, you might be working on full-stops with eleven-year-olds then taking eighteen-year-olds through the finer points of poetry, teachers in Shanghai specialised not only in a subject area, but also an age-group.
Shanghai’s success owed a lot to Confucian tradition, but it fitted precisely the best contemporary understanding of how expertise is developed. In his book Why Don’t Kids Like School? cognitive Dan Willingham explains that complex mental skills like creativity and critical thinking depend on our first having mastered the simple stuff. Memorisation and repetition of the basics serve to lay down the neural architecture that creates automaticity of thought, ultimately freeing up space in our working memory to think big.
Seung-bin Lee, a seventeen-year-old high school graduate, told me of studying fourteen hours a day, seven days a week, for the three years leading up to the Suneung, the fearsome SAT exam taken by all Korean school leavers on a single Thursday each November, for which all flights are grounded so as not to break students’ concentration during the 45 minutes of the English listening paper.
Korea’s childhoods were being lost to a relentless regime of studying, crushed in a top-down system that saw them as cyphers rather than kids.
A decade ago, we consoled ourselves that although kids in China and Korea worked harder and did better on tests than ours, it didn’t matter. They were compliant, unthinking drones, lacking the creativity, critical thinking or entrepreneurialism needed to succeed in the world. No longer. Though there are still issues with Chinese education – urban centres like Shanghai and Hong Kong are positive outliers – the country knows something that we once did: education is the one investment on which a return is guaranteed. China is on course to becoming the first education superpower.
Troublingly, where education in the UK and US has been defined by creativity and independent thinking – Shanghai teachers told me of visits to our schools to learn about these qualities – our direction of travel is now away from those strengths and towards exams and standardisation, with school-readiness tests in the pipeline and UK schools minister Nick Gibb suggesting kids can beat exam stress by sitting more of them. Centres of excellence remain, but increasingly, it feels, we’re putting our children at risk of losing out to the robots, while China is building on its strong foundations to ask how its young people can be high-tech pioneers. They’re thinking big – we’re thinking of test scores.
soon “digital information processing” would be included as a core subject on China’s national graduation exam – the Gaokao – and pictured classrooms in which students would learn in cross-disciplinary fashion, designing mobile phones for example, in order to develop design, engineering and computing skills. Focusing on teaching kids to code was short-sighted, he explained. “We still regard it as a language between human and computer.” (My note: they are practically implementing the Finland’s attempt to rebuild curricula)
“If your plan is for one year,” went an old Chinese saying, “plant rice. If your plan is for ten years, plant trees. If your plan is for 100 years, educate children.” Two and half thousand years later chancellor Gwan Zhong might update his proverb, swapping rice for bitcoin and trees for artificial intelligence, but I’m sure he’d stand by his final point.