Ren, a former engineer with the People’s Liberation Army who went into consumer electronics, played the patriotic card, cautioning Jiang that ‘switching equipment technology was related to national security, and that a nation that did not have its own switching equipment was like one that lacked its own military’ (1). A quarter of a century later, other countries, led by the US, have belatedly grasped the wisdom of Ren’s remarks; the technology in question today is 5G
The company operates networks in 170 countries and employs more than 194,000 people.
This summer it overtook Samsung as the world’s biggest seller of smartphones… boast some of the most advanced artificial intelligence capabilities on the market.
spending more than 10% of its annual profits on research and development. In 2019 it spent over $15bn — more than Apple and Microsoft — and the budget for 2020 is $20bn. (For comparison, the R&D spend of the entire German car industry in 2018 was roughly $30bn.)
Huawei and 5G are only a small part of a much larger geoeconomic and geopolitical struggle in which China is trying to gain the upper hand over the US.
Washington’s campaign against Chinese tech includes firms such as the state-owned ZTE, another important player in the 5G field, WeChat and TikTok and many other lesser-known companies. But Huawei is its main target.
Washington sees Huawei as an arch-example of China’s rogue behaviour (widely mistaken for meritocratic market success) — stealing intellectual property, bullying partners and undercutting competitors
Project Information Literacy, a nonprofit research institution that explores how college students find, evaluate and use information. It was commissioned by the John S. and James L. Knight Foundation and The Harvard Graduate School of Education.
focus groups and interviews with 103 undergraduates and 37 faculty members from eight U.S. colleges.
To better equip students for the modern information environment, the report recommends that faculty teach algorithm literacy in their classrooms. And given students’ reliance on learning from their peers when it comes to technology, the authors also suggest that students help co-design these learning experiences.
While informed and critically aware media users may see past the resulting content found in suggestions provided after conducting a search on YouTube, Facebook, or Google, those without these skills, particularly young or inexperienced users, fail to realize the culpability of underlying algorithms in the resultant filter bubbles and echo chambers (Cohen, 2018).
Media literacy education is more important than ever. It’s not just the overwhelming calls to understand the effects of fake news or addressing data breaches threatening personal information, it is the artificial intelligence systems being designed to predict and project what is perceived to be what consumers of social media want.
it’s time to revisit the Eight Key Concepts of media literacy with an algorithmic focus.
Literacy in today’s online and offline environments “means being able to use the dominant symbol systems of the culture for personal, aesthetic, cultural, social, and political goals” (Hobbs & Jensen, 2018, p 4).
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.
what i find most important: Future IT Workforce: Deploying a broad array of modern recruitment, retention, and employment practices to develop a resilient IT talent pipeline for the institution
Digital Integrations: Ensuring system interoperability, scalability, and extensibility, as well as data integrity, security, standards, and governance, across multiple applications and platforms
Engaged Learning: Incorporating technologies that enable students to create content and engage in active learning in course curricula
Student Retention and Completion: Developing the capabilities and systems to incorporate artificial intelligence into student services to provide personalized, timely support
Administrative Simplification: Applying user-centered design, process improvement, and system reengineering to reduce redundant or unnecessary efforts and improve end-user experiences
Improved Enrollment: Using technology, data, and analytics to develop an inclusive and financially sustainable enrollment strategy to serve more and new learners by personalizing recruitment, enrollment, and learning experiences
Workforce of the Future: Using technology to develop curriculum, content, and learning experiences that prepare students for the evolving workforce
Holistic Student Success: Applying technology and data, including artificial intelligence, to understand and address the numerous contributors to student success, from finances to health and wellness to academic performance and degree planning (my note: this is what Christine Waisner, Mark Gill and Plamen Miltenoff are trying to do with their VR research)
Improved Teaching: Strengthening engagement among faculty, technologists, and researchers to achieve the true and expanding potential of technology to improve teaching
Student-Centric Higher Education: Creating a student-services ecosystem to support the entire student life cycle, from prospecting to enrollment, learning, job placement, alumni engagement, and continuing education
a two-day conference about artificial intelligence in education organized by a company called Squirrel AI.
he believes that having AI-driven tutors or instructors will help them each get the individual approach they need.
the Chinese government has declared a national goal of surpassing the U.S. in AI technology by the year 2030, so there is almost a Sputnik-like push for the tech going on right now in China.
Researchers at the Fraunhofer Institute for Microelectronic Circuits and Systems IMS have developed AIfES, an artificial intelligence (AI) concept for microcontrollers and sensors that contains a completely configurable artificial neural network. AIfES is a platform-independent machine learning library which can be used to realize self-learning microelectronics requiring no connection to a cloud or to high-performance computers. The sensor-related AI system recognizes handwriting and gestures, enabling for example gesture control of input when the library is running on a wearable.
a machine learning library programmed in C that can run on microcontrollers, but also on other platforms such as PCs, Raspberry PI and Android.
Because of technological advances and the sheer amount of data now available about billions of other people, discretion no longer suffices to protect your privacy. Computer algorithms and network analyses can now infer, with a sufficiently high degree of accuracy, a wide range of things about you that you may have never disclosed, including your moods, your political beliefs, your sexual orientation and your health.
There is no longer such a thing as individually “opting out” of our privacy-compromised world.
In 2017, the newspaper The Australian published an article, based on a leaked document from Facebook, revealing that the company had told advertisers that it could predict when younger users, including teenagers, were feeling “insecure,” “worthless” or otherwise in need of a “confidence boost.” Facebook was apparently able to draw these inferences by monitoring photos, posts and other social media data.
In 2017, academic researchers, armed with data from more than 40,000 Instagram photos, used machine-learning tools to accurately identify signs of depression in a group of 166 Instagram users. Their computer models turned out to be better predictors of depression than humans who were asked to rate whether photos were happy or sad and so forth.
Computational inference can also be a tool of social control. The Chinese government, having gathered biometric data on its citizens, is trying to use big data and artificial intelligence to single out “threats” to Communist rule, including the country’s Uighurs, a mostly Muslim ethnic group.
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Zeynep Tufekci and Seth Stephens-Davidowitz: Privacy is over
Date: Wednesday, April 3rd Time: 3:30 PM to 4:15 PM Conference Session: Concurrent Session 3 Streamed session Lead Presenter: Brian Kane (General Design LLC) Track: Research: Designs, Methods, and Findings Location: Juniper A Session Duration: 45min Brief Abstract:What happens when you apply design thinking to AI? AI presents a fundamental change in the way people interact with machines. By applying design thinking to the way AI is made and used, we can generate an unlimited amount of new ideas for products and experiences that people will love and use.https://onlinelearningconsortium.org/olc-innovate-2019-session-page/?session=6964&kwds=
Notes from the session:
design thinking: get out from old mental models. new narratives; get out of the sci fi movies.
narrative generators:
we need machines to make mistakes. Ai even more then traditional software.
Lessons learned: don’t replace people
Date: Thursday, April 4th Time: 8:45 AM to 9:30 AM Conference Session: Concurrent Session 4 Streamed session Lead Presenter: Matt Crosslin (University of Texas at Arlington LINK Research Lab) Track: Experiential and Life-Long Learning Location: Cottonwood 4-5 Session Duration: 45min Brief Abstract:How can teachers utilize chatbots and artificial intelligence in ways that won’t remove humans out of the education picture? Using tools like Twine and Recast.AI chatobts, this session will focus on how to build adaptive content that allows learners to create their own heutagogical educational pathways based on individual needs.++++++++++++++++
Date: Thursday, April 4th Time: 9:45 AM to 10:30 AM Conference Session: Concurrent Session 5 Streamed session Lead Presenter: Maikel Alendy (FIU Online) Co-presenter: Sky V. King (FIU Online – Florida International University) Track: Teaching and Learning Practice Location: Cottonwood 4-5 Session Duration: 45min Brief Abstract:“This is Us” demonstrates how leveraging storytelling in learning engages students to effectively communicate their authentic story, transitioning from consumerism to become creators and influencers. Addressing responsibility as a digital citizen, information and digital literacy, online privacy, and strategies with examples using several edtech tools, will be reviewed.++++++++++++++++++
Date: Thursday, April 4th Time: 11:15 AM to 12:00 PM Conference Session: Concurrent Session 6 Streamed session Lead Presenter: Kristin Bushong (Arizona State University ) Co-presenter: Heather Nebrich (Arizona State University) Track: Effective Tools, Toys and Technologies Location: Juniper C Session Duration: 45min Brief Abstract:Considering today’s overstimulated lifestyle, how do we engage busy learners to stay on task? Join this session to discover current efforts in implementing ubiquitous educational opportunities through customized interests and personalized learning aspirations e.g., adaptive math tools, AI support communities, and memory management systems.+++++++++++++
Date: Thursday, April 4th Time: 1:15 PM to 2:00 PM Conference Session: Concurrent Session 7 Streamed session Lead Presenter: Katie Linder (Oregon State University) Co-presenter: June Griffin (University of Nebraska-Lincoln) Track: Teaching and Learning Practice Location: Cottonwood 4-5 Session Duration: 45min Brief Abstract:The concept of High-impact Educational Practices (HIPs) is well-known, but the conversation about transitioning HIPs online is new. In this session, contributors from the edited collection High-Impact Practices in Online Education will share current HIP research, and offer ideas for participants to reflect on regarding implementing HIPs into online environments.https://www.aacu.org/leap/hipshttps://www.aacu.org/sites/default/files/files/LEAP/HIP_tables.pdf+++++++++++++++++++++++
Date: Thursday, April 4th Time: 3:45 PM to 5:00 PM Streamed session Lead Presenter: Manoush Zomorodi (Stable Genius Productions) Track: N/A Location: Adams Ballroom Session Duration: 1hr 15min Brief Abstract:How can we ensure that students and educators thrive in increasingly digital environments, where change is the only constant? In this keynote, author and journalist Manoush Zomorodi shares her pioneering approach to researching the effects of technology on our behavior. Her unique brand of journalism includes deep-dive investigations into such timely topics as personal privacy, information overload, and the Attention Economy. These interactive multi-media experiments with tens of thousands of podcast listeners will inspire you to think creatively about how we use technology to educate and grow communities.Friday
Date: Friday, April 5th Time: 8:30 AM to 9:30 AM Streamed session Lead Presenter: Michael Caulfield (Washington State University-Vancouver) Track: N/A Location: Adams Ballroom Position: 2 Session Duration: 60min Brief Abstract:Years ago, John Lyndon (then Johnny Rotten) sang that “anger is an energy.” And he was right, of course. Anger isn’t an emotion, like happiness or sadness. It’s a reaction, a swelling up of a confused urge. I’m a person profoundly uncomfortable with anger, but yet I’ve found in my professional career that often my most impactful work begins in a place of anger: anger against injustice, inequality, lies, or corruption. And often it is that anger that gives me the energy and endurance to make a difference, to move the mountains that need to be moved. In this talk I want to think through our uneasy relationship with anger; how it can be helpful, and how it can destroy us if we’re not careful.++++++++++++++++
Date: Friday, April 5th Time: 10:45 AM to 11:30 AM Conference Session: Concurrent Session 10 Streamed session Lead Presenter: Laurie Daily (Augustana University) Co-presenter: Sharon Gray (Augustana University) Track: Problems, Processes, and Practices Location: Juniper A Session Duration: 45min Brief Abstract:The purpose of this session is to explore the implementation of a Community of Practice to support professional development, enhance online course and program development efforts, and to foster community and engagement between and among full and part time faculty.+++++++++++++++
Date: Friday, April 5th Time: 11:45 AM to 12:30 PM Conference Session: Concurrent Session 11 Streamed session Lead Presenter: Katrina Rainer (Strayer University) Co-presenter: Jennifer M McVay-Dyche (Strayer University) Track: Teaching and Learning Practice Location: Cottonwood 2-3 Session Duration: 45min Brief Abstract:Learning is more effective and organic when we teach through the art of storytelling. At Strayer University, we are blending the principles story-driven learning with research-based instructional design practices to create engaging learning experiences. This session will provide you with strategies to strategically infuse stories into any lesson, course, or curriculum.
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.
