more on AI in this IMS blog
more on AI in this IMS blog
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.
more on AI in education in this IMS blog
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.
more on machine learning in this IMS blog
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.
Meanwhile, the public was amazed at technological advances like Boston Dynamic’s Atlas robot doing parkour, while simultaneously being outraged at the thought of our data no longer being ours and Alexa listening in on all our conversations.
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.
Federally funded initiatives, as well as corporate efforts (such as Google’s “What If” tool) will lead to the rise of explainable AI and interpretable AI, whereby the AI actually explains the logic behind its decision making to humans. But the next step from there would be for the AI regulators and policymakers themselves to learn about how these technologies actually work. This is an overlooked step right now that Richard Danzig, former Secretary of the U.S. Navy advises us to consider, as we create “humans-in-the-loop” systems, which require people to sign off on important AI decisions.
Google invested $25 million in AI for Good and Microsoft added an AI for Humanitarian Action to its prior commitment. While these are positive steps, the tech industry continues to have a diversity problem
Ryan Calo from the University of Washington explains that it matters how we talk about technologies that we don’t fully understand.
<h3 “>Sharpen the digital transformationstrategy for your business.
Enroll today in Digital Transformation: From AI and IoT to Cloud, Blockchain, and Cybersecurity
In a rapidly expanding digital marketplace, legacy companies without a clear digital transformation strategy are being left behind. How can we stay on top of rapid—and sometimes radical—change? How can we position our organizations to take advantage of new technologies? How can we track and combat the security threats facing all of us as we are swept forward into the future?
<h3 “>Your Learning Journey
This online program takes you through the fundamentals of digital technologies transforming our world today. Led by MIT faculty at the forefront of data science, participants will learn the history and application of transformative technologies such as blockchain, artificial intelligence, cloud computing, IoT, and cybersecurity as well as the implications of employing—or ignoring—digitalization.
Join our discussion on #technology and #ethics. share your opinions, suggestions, ideas
Posted by InforMedia Services on Thursday, November 1, 2018
Heard on Marketplace this morning (Oct. 22, 2018): ethics of artificial intelligence with John Havens of the Institute of Electrical and Electronics Engineers, which has developed a new ethics certification process for AI: https://standards.ieee.org/content/dam/ieee-standards/standards/web/documents/other/ec_bios.pdf
***** The student club, the Philosophical Society, has now been recognized by SCSU as a student organization ***
Could it be the case that a random decision is still better then predetermined one designed to minimize harm?
similar ethical considerations are raised also:
in this sitcom
https://www.theatlantic.com/sponsored/hpe-2018/the-ethics-of-ai/1865/ (full movie)
This TED talk:
IoT (Internet of Things), Industry 4.0, Big Data, BlockChain,
IoT (Internet of Things), Industry 4.0, Big Data, BlockChain, Privacy, Security, Surveilance
Keyword search: ethic* + Internet of Things = 31
Baldini, G., Botterman, M., Neisse, R., & Tallacchini, M. (2018). Ethical Design in the Internet of Things. Science & Engineering Ethics, 24(3), 905–925. https://doi-org.libproxy.stcloudstate.edu/10.1007/s11948-016-9754-5
Berman, F., & Cerf, V. G. (2017). Social and Ethical Behavior in the Internet of Things. Communications of the ACM, 60(2), 6–7. https://doi-org.libproxy.stcloudstate.edu/10.1145/3036698
Murdock, G. (2018). Media Materialties: For A Moral Economy of Machines. Journal of Communication, 68(2), 359–368. https://doi-org.libproxy.stcloudstate.edu/10.1093/joc/jqx023
Carrier, J. G. (2018). Moral economy: What’s in a name. Anthropological Theory, 18(1), 18–35. https://doi-org.libproxy.stcloudstate.edu/10.1177/1463499617735259
Kernaghan, K. (2014). Digital dilemmas: Values, ethics and information technology. Canadian Public Administration, 57(2), 295–317. https://doi-org.libproxy.stcloudstate.edu/10.1111/capa.12069
Koucheryavy, Y., Kirichek, R., Glushakov, R., & Pirmagomedov, R. (2017). Quo vadis, humanity? Ethics on the last mile toward cybernetic organism. Russian Journal of Communication, 9(3), 287–293. https://doi-org.libproxy.stcloudstate.edu/10.1080/19409419.2017.1376561
Keyword search: ethic+ + autonomous vehicles = 46
Cerf, V. G. (2017). A Brittle and Fragile Future. Communications of the ACM, 60(7), 7. https://doi-org.libproxy.stcloudstate.edu/10.1145/3102112
Fleetwood, J. (2017). Public Health, Ethics, and Autonomous Vehicles. American Journal of Public Health, 107(4), 632–537. https://doi-org.libproxy.stcloudstate.edu/10.2105/AJPH.2016.303628
HARRIS, J. (2018). Who Owns My Autonomous Vehicle? Ethics and Responsibility in Artificial and Human Intelligence. Cambridge Quarterly of Healthcare Ethics, 27(4), 599–609. https://doi-org.libproxy.stcloudstate.edu/10.1017/S0963180118000038
Keeling, G. (2018). Legal Necessity, Pareto Efficiency & Justified Killing in Autonomous Vehicle Collisions. Ethical Theory & Moral Practice, 21(2), 413–427. https://doi-org.libproxy.stcloudstate.edu/10.1007/s10677-018-9887-5
Hevelke, A., & Nida-Rümelin, J. (2015). Responsibility for Crashes of Autonomous Vehicles: An Ethical Analysis. Science & Engineering Ethics, 21(3), 619–630. https://doi-org.libproxy.stcloudstate.edu/10.1007/s11948-014-9565-5
Getha-Taylor, H. (2017). The Problem with Automated Ethics. Public Integrity, 19(4), 299–300. https://doi-org.libproxy.stcloudstate.edu/10.1080/10999922.2016.1250575
Keyword search: ethic* + artificial intelligence = 349
Etzioni, A., & Etzioni, O. (2017). Incorporating Ethics into Artificial Intelligence. Journal of Ethics, 21(4), 403–418. https://doi-org.libproxy.stcloudstate.edu/10.1007/s10892-017-9252-2
Köse, U. (2018). Are We Safe Enough in the Future of Artificial Intelligence? A Discussion on Machine Ethics and Artificial Intelligence Safety. BRAIN: Broad Research in Artificial Intelligence & Neuroscience, 9(2), 184–197. Retrieved from http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3daph%26AN%3d129943455%26site%3dehost-live%26scope%3dsite
Keynote presentations will explore the future of driving and the evolution and potential of automated vehicle technologies.
more on AI in this IMS blog
AI and autonomous cars as ALA discussion topic
and privacy concerns
the call of the German scientists on ethics and AI
AI in the race for world dominance
Artificial intelligence could have a profound impact on learning, but it also raises key questions.
By Dennis Pierce, Alice Hathaway 08/29/18
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.
For instance, a Seattle-based nonprofit company called Enlearn has developed an adaptive learning platform that uses machine learning technology to create highly individualized learning paths that can accelerate learning for every student. (My note: about learning and technology, Alfie Kohn in http://blog.stcloudstate.edu/ims/2018/09/11/educational-technology/)
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?
more on AI in education in this IMS blog
more on AR in this IMS blog
more on China education in this IMS blog
Robert Ubell (Columnist) Feb 20, 2019
dean of web-based distance learning
Neck and neck for the top spot in the LMS academic vendor race are Blackboard—the early entry and once-dominant player—and coming-up quickly from behind, the relatively new contender, Canvas, each serving about 6.5 million students . The LMS market today is valued at $9.2 billion.
Faced with increasingly complex communication technologies—voice, video, multimedia, animation—university faculty, expert in their own disciplines, find themselves technically perplexed, largely unprepared to build digital courses.
instructional designers, long employed by industry, joined online academic teams, working closely with faculty to upload and integrate interactive and engaging content.
nstructional designers, as part of their skillset, turned to digital authoring systems, software introduced to stimulate engagement, encouraging virtual students to interface actively with digital materials, often by tapping at a keyboard or touching the screen as in a video game. Most authoring software also integrates assessment tools, testing learning outcomes.
With authoring software, instructional designers can steer online students through a mixtape of digital content—videos, graphs, weblinks, PDFs, drag-and-drop activities, PowerPoint slides, quizzes, survey tools and so on. Some of the systems also offer video editing, recording and screen downloading options
As with a pinwheel set in motion, insights from many disciplines—artificial intelligence, cognitive science, linguistics, educational psychology and data analytics—have come together to form a relatively new field known as learning science, propelling advances in a new personalized practice—adaptive learning.
Of the top providers, Coursera, the Wall Street-financed company that grew out of the Stanford breakthrough, is the champion with 37 million learners, followed by edX, an MIT-Harvard joint venture, with 18 million. Launched in 2013, XuetangX, the Chinese platform in third place, claims 18 million.
Former Yale President Rick Levin, who served as Coursera’s CEO for a few years, speaking by phone last week, was optimistic about the role MOOCs will play in the digital economy. “The biggest surprise,” Levin argued, “is how strongly MOOCs have been accepted in the corporate world to up-skill employees, especially as the workforce is being transformed by job displacement. It’s the right time for MOOCs to play a major role.”
In virtual education, pedagogy, not technology, drives the metamorphosis from absence to presence, illusion into reality. Skilled online instruction that introduces peer-to-peer learning, virtual teamwork and other pedagogical innovations stimulate active learning. Online learning is not just another edtech product, but an innovative teaching practice. It’s a mistake to think of digital education merely as a device you switch on and off like a garage door.
more on online learning in this IMS blog
Creating A Cost-Free Course
1 2 Next