Searching for "ethics"

AI and ethics

Live Facebook discussion at SCSU VizLab on ethics and technology:

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

Ethics and AI

***** The student club, the Philosophical Society, has now been recognized by SCSU as a student organization ***

https://ed.ted.com/lessons/the-ethical-dilemma-of-self-driving-cars-patrick-lin

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:

http://blog.stcloudstate.edu/ims/2017/09/19/social-media-algorithms/

http://blog.stcloudstate.edu/ims/2018/10/02/social-media-monopoly/

 

 

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IoT (Internet of Things), Industry 4.0, Big Data, BlockChain,

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IoT (Internet of Things), Industry 4.0, Big Data, BlockChain, Privacy, Security, Surveilance

http://blog.stcloudstate.edu/ims?s=internet+of+things

peer-reviewed literature;

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 Ethics24(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 ACM60(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 Communication68(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 Theory18(1), 18–35. https://doi-org.libproxy.stcloudstate.edu/10.1177/1463499617735259

Kernaghan, K. (2014). Digital dilemmas: Values, ethics and information technology. Canadian Public Administration57(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 Communication9(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 ACM60(7), 7. https://doi-org.libproxy.stcloudstate.edu/10.1145/3102112

Fleetwood, J. (2017). Public Health, Ethics, and Autonomous Vehicles. American Journal of Public Health107(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 Ethics27(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 Practice21(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 Ethics21(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 Integrity19(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 Ethics21(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 & Neuroscience9(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

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http://www.cts.umn.edu/events/conference/2018

2018 CTS Transportation Research Conference

Keynote presentations will explore the future of driving and the evolution and potential of automated vehicle technologies.

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http://blog.stcloudstate.edu/ims/2016/02/26/philosophy-and-technology/

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more on AI in this IMS blog
http://blog.stcloudstate.edu/ims/2018/09/07/limbic-thought-artificial-intelligence/

AI and autonomous cars as ALA discussion topic
http://blog.stcloudstate.edu/ims/2018/01/11/ai-autonomous-cars-libraries/

and privacy concerns
http://blog.stcloudstate.edu/ims/2018/09/14/ai-for-education/

the call of the German scientists on ethics and AI
http://blog.stcloudstate.edu/ims/2018/09/01/ethics-and-ai/

AI in the race for world dominance
http://blog.stcloudstate.edu/ims/2018/04/21/ai-china-education/

coding ethics unpredictability

Franken-algorithms: the deadly consequences of unpredictable code

by  Thu 30 Aug 2018 

https://www.theguardian.com/technology/2018/aug/29/coding-algorithms-frankenalgos-program-danger

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.

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more on coding in this IMS blog
http://blog.stcloudstate.edu/ims?s=coding

ethics and AI

Ethik und Künstliche Intelligenz: Die Zeit drängt – wir müssen handeln

8/7/2108 Prof. Dr. theol. habil. Arne Manzeschke

https://www.pcwelt.de/a/ethik-und-ki-die-zeit-draengt-wir-muessen-handeln,3451885

Das Europäische Parlament hat es im vergangenen Jahr ganz drastisch formuliert. Eine neue industrielle Revolution steht an
1954 wurdeUnimate, der erste Industrieroboter , von George Devol entwickelt [1]. Insbesondere in den 1970er Jahren haben viele produzierende Gewerbe eine Roboterisierung ihrer Arbeit erfahren (beispielsweise die Automobil- und Druckindustrie).
Definition eines Industrieroboters in der ISO 8373 (2012) vergegenwärtigt: »Ein Roboter ist ein frei und wieder programmierbarer, multifunktionaler Manipulator mit mindestens drei unabhängigen Achsen, um Materialien, Teile, Werkzeuge oder spezielle Geräte auf programmierten, variablen Bahnen zu bewegen zur Erfüllung der verschiedensten Aufgaben«.

Ethische Überlegungen zu Robotik und Künstlicher Intelligenz

Versucht man sich einen Überblick über die verschiedenen ethischen Probleme zu verschaffen, die mit dem Aufkommen von ›intelligenten‹ und in jeder Hinsicht (Präzision, Geschwindigkeit, Kraft, Kombinatorik und Vernetzung) immer mächtigeren Robotern verbunden sind, so ist es hilfreich, diese Probleme danach zu unterscheiden, ob sie

1. das Vorfeld der Ethik,

2. das bisherige Selbstverständnis menschlicher Subjekte (Anthropologie) oder

3. normative Fragen im Sinne von: »Was sollen wir tun?« betreffen.

Die folgenden Überlegungen geben einen kurzen Aufriss, mit welchen Fragen wir uns jeweils beschäftigen sollten, wie die verschiedenen Fragenkreise zusammenhängen, und woran wir uns in unseren Antworten orientieren können.

Aufgabe der Ethik ist es, solche moralischen Meinungen auf ihre Begründung und Geltung hin zu befragen und so zu einem geschärften ethischen Urteil zu kommen, das idealiter vor der Allgemeinheit moralischer Subjekte verantwortet werden kann und in seiner Umsetzung ein »gelungenes Leben mit und für die Anderen, in gerechten Institutionen« [8] ermöglicht. Das ist eine erste vage Richtungsangabe.

Normative Fragen lassen sich am Ende nur ganz konkret anhand einer bestimmten Situation bearbeiten. Entsprechend liefert die Ethik hier keine pauschalen Urteile wie: »Roboter sind gut/schlecht«, »Künstliche Intelligenz dient dem guten Leben/ist dem guten Leben abträglich«.

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more on Artificial Intelligence in this IMS blog
http://blog.stcloudstate.edu/ims?s=artifical+intelligence

Social Media Etiquette Ethics

Social Media Etiquette & Ethics: A Guide for Personal, Professional & Brand Use.

Published on , Marketing Professor & Researcher

https://www.linkedin.com/pulse/social-media-etiquette-ethics-guide-personal-brand-use-quesenberry

definition:

Etiquette is the proper way to behave and Ethics studies ideas about good and bad behavior. Both combine into Professionalism, which is the skill, good judgment, and polite behavior expected from a person trained to do a job such as social media marketing. Because social media blurs the lines between our personal and professional lives it is useful to look at actions in social media from three perspectives: Personal (as an individual), Professional (as an employee or perspective employee) and Brand (as an organization). To simplify the discussion I have created questions for each category in the Social Media Etiquette and Ethics Guide below. Click here to download.

Before you post or comment in a personal capacity consider:

  1. Is it all about me? No one likes someone who only talks about themselves. The same applies in social media. Balance boasting with complimenting.
  2. Am I stalking someone? It is good to be driven and persistent but be careful not to cross the line into creepy. Don’t be too aggressive in outreach.
  3. Am I spamming them? Not everything or even the majority of what you post should ask for something. Don’t make everything self-serving.
  4. Am I venting or ranting? Venting and ranting may feel good, but research says it doesn’t help and no matter how justified you feel, it never presents you in a positive light. Do not post negative comments or gossip.
  5. Did I ask before I tagged? You had a great time and want to share those memories, but your friends, family or employer may have different standards than a friends. Check before you tag people in posts.
  6. Did I read before commenting or sharing? Don’t make yourself look foolish by not fully reviewing something you are commenting on or sharing with others. Don’t jump to conclusions.
  7. Am I grateful and respectful? Don’t take people for granted. Respond and thank those who engage with you.
  8. Is this the right medium for the message? Not everything should be said in social media. Consider the feelings of the other person. Some messages should be given in person, by phone or email.
  9. Am I logged into the right account? There are too many corporate examples of embarrassing posts meant for personal jokes that went out on official brand accounts. Always double check which account you are on. Don’t post personal information on brand accounts.

Before you post or comment as a professional consider:

  1. Does it meet the Social Media Policy? Most organizations have official social media policies that you probably received when hired. Don’t assume you know what the policy says. Many employees have been fired for not following company social media regulations. Make sure you know and follow employer or client requirements.
  2. Does it hurt my company’s reputation? No matter how many disclaimers you put on your accounts such as “views are my own” certain content and behavior will negatively impact your employer. If your bio states where you work, your personal account represents your employer.
  3. Does it help my company’s marketing? Employee advocacy is an important strategy. Have a positive impact on your company’s image and when you can advocate for your brand in social.
  4. Would my boss/client be happy to see it? You may not have “friended” your boss or client but a co-worker may have and your post is only a share or screen grab away. Even private accounts are never fully private.
  5. Am I being open about who I work for? It is good to post positive content about your employer and it is nice to receive gifts, but if you are trying to pass it off as unbiased opinion that is wrong. Be transparent about your financial connections.
  6. Am I being fair and accurate? Everyone is entitled to their person opinion, but if your opinion tends to always be unfounded and seems to have an agenda it will reflect negatively upon you. Criticism is welcome when it is constructive and opinion is backed by evidence.
  7. Am I being respectful and not malicious? People can get very insensitive, judgmental and angry in social media posts. That does not convey a professional image. Don’t post what you wouldn’t say in person. Even an outburst in person fades in memory, but a malicious post is there forever.
  8. Does it respect intellectual property? Not everything on the Internet is free. Check for or get permission to post company or client brand assets and content.
  9. Is this confidential information? As an employee or contractor you are granted access to privileged and confidential information. Don’t assume it is fine to share. Do not disclose non-public company or client information.

Before posting or commenting as a brand on a social account consider:

  1. Does it speak to my target market? Social media is unique from traditional marketing and requires a different perspective to be effective. Be sure to focus on your target’s wants and needs not yours.
  2. Does it add value? Social media only works if people view and share it. Make your content educational, insightful or entertaining to grab interest and draw engagement.
  3. Does it fit the social channel? Don’t post content ideal for Twitter on Instagram or Reddit. Each channel has its own culture and community. Make sure each post fits the channel’s environment, mission and policies or standards.
  4. Is it authentic and transparent? Trying to trick people into clicking a link or making a purchase will get you nowhere. Don’t hide or exclude any relevant information.
  5. Is it real and unique? Bots can automate tasks and be a great time saver, but use them for the right actions. Don’t use auto responses and create anything that could be perceived as spam.
  6. Is it positive and respectful? It may be fine to talk trash about competitors or complain about customers in the office, but not in social media. Don’t badmouth the competition or customers.
  7. Does it meet codes of conduct? As professionals we are part of trade associations that set standards of conduct. Be sure you are meeting these ethical standards such as the Word of Mouth Marketing Association’s Code of Ethics.
  8. Does it meet all laws and regulations? Government has been catching up with social media and have issued regulations and laws you must follow. See guides on requirements like the FTC social media endorsement guidelines.
  9. Does it meet the Social Media Policy? Most likely your brand or a client’s brand has a social media policy. Ensure you follow your own company standards.

 

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more on social media netiquette in this IMS blog
http://blog.stcloudstate.edu/ims?s=social+media+netiquette

Research and Ethics: If Facebook can tweak our emotions and make us vote, what else can it Do?

If Facebook can tweak our emotions and make us vote, what else can it do?

http://www.businessinsider.com/facebook-calls-experiment-innovative-2014-7#ixzz36PtsxVfL

Google’s chief executive has expressed concern that we don’t trust big companies with our data – but may be dismayed at Facebook’s latest venture into manipulation

Please consider the information on Power, Privacy, and the Internet and details on ethics and big data in this IMS blog entry:http://blog.stcloudstate.edu/ims/2014/07/01/privacy-and-surveillance-obama-advisor-john-podesta-every-country-has-a-history-of-going-over-the-line/

important information:
Please consider the SCSU Research Ethics and the IRB (Institutional Review Board) document:
http://www.stcloudstate.edu/graduatestudies/current/culmProject/documents/ResearchEthicsandQualitative–IRBPresentationforGradStudentsv2.2011.pdf
For more information, please contact the SCSU Institutional Review Board : http://www.stcloudstate.edu/irb/default.asp

The Facebook Conundrum: Where Ethics and Science Collide

http://blogs.kqed.org/mindshift/2014/07/the-facebook-conundrum-where-ethics-and-science-collide

The field of learning analytics isn’t just about advancing the understanding of learning. It’s also being applied in efforts to try to influence and predict student behavior.

Learning analytics has yet to demonstrate its big beneficial breakthrough, its “penicillin,” in the words of Reich. Nor has there been a big ethical failure to creep lots of people out.

“There’s a difference,” Pistilli says, “between what we can do and what we should do.”

Reimagining Minnesota State

Reimagining Minnesota State: Forum Session 2 – Jan. 14, 2019 reservation

Posted by InforMedia Services on Monday, January 14, 2019

Reimagining Minnesota State 

Monday, January 14, 2019

10:00 a.m. – 12:00 p.m.

Session 2: The Digital Age: The Impact and Future Possibilities Offered by Data and Technology

Thank you for registering to participate in the second Reimagining Minnesota State forum. The Forums have been designed to spark not only individual reflection but what we hope can serve as catalysts for discussions in a variety of venues. The Forum will be recorded and available for viewing on the Reimagining website.

Below are the directions whether you are attending in person or by live stream.

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notes Plamen Miltenoff

John O’Brien, President and CEO of EDUCAUSE

http://www.minnstate.edu/board/reimagining/docs/PDF_Final-Final-Minnesota-State-OBrien-Remarks-011319.pdf

from ad hoc to systemic institutional innovations

ask Rachel for the two books announced

Bryan Mark GIll AR library tour

Bryan Rachel OER “visit”

Catherine Haslag: Is there any research to show students retention in an online class vs a face-to-face course?

the challenge is not collecting, but integrating, using data.

silos = cylinder of excellence.

technology innovation around advising. iPASS resources.

adaptive learning systems – how students advance through the learning process.

games and simulations Bryan Mark Gill. voice recognition,

next 3 to 5 years AR. by 2023 40% with AR and VR

AI around the controversial. Chatbot and Voice assistants.

Unizin: 13 founding members to develop platform, Canvas, instructional services, data for predictive analytic, consistent data standard among institutions,

University innovation Alliance. Analytics as the linchpin for students’ success. graduation rates increase. racial gap graduation. Georgia State.

digital ethics. Mark Gill and Susana Nuccetelli. digital ethics: Susana Nuccetelli brought her students from the Philosophy Dept to Mark Gill’s SCSu Vizlab so we can discuss ethics and AI, last semester. jobrien@educause.edu

Tiffany Beth Mfume

http://www.minnstate.edu/board/reimagining/docs/Mfume-Minnesota.State.1-14-2019.pdf

assistant vice president for student success and prevention Morgan State U

the importance of training in technology adoption

Dr. Peter Smith, Orkand Endowed Chair and Professor of Innovative Practices in Higher Education at University of Maryland University College 

social disruption, national security issue,
Allan Taft Candadian researcher, 700 hours / year learning something. 14 h/w.
learners deserve recognition
free range learning.
how do we get a value on people from a different background? knowledge discrimination. we value it on where they learned it. then how you learned it and what you can do with it. talent and capacity not recognized.

we, the campus, don’t control the forces for a very first time. MIT undergrad curricula is free, what will happen. dynamics at work here. declining student numbers, legislation unhappy. technology had made college more expensive, not less. doing the right thing, leads to more disruption. local will be better, if done well. workplace can become a place for learning.
learning is a social activity. distance learning: being on the farthest raw of 300 Princeton lecture. there is a tool and there is people; has to have people at the heart.
what will work not only for MN, but for each of the campuses, the personalization.

staying still is death.

Panel discussion

what is the role of faculty in the vendor and discussions about technology. a heat map shows that IT people were testing the vendor web site most, faculty and student much less.

 

Finland ideas for US education

OPINION: Can this 12-step program from Finland aid U.S. education?

 Finland system consistently receives top marks from UNICEF, the OECD and the World Economic Forum.
Many U.S. states are similar in population size and demographics to Finland, and education is largely run at the state level. In the economically depressed forest region of North Karelia — on the Russian border — where we spent much of our time, the unemployment rate is nearly 15 percent, compared with under 5 percent in America and our home state of New York. However, the U.S. child poverty rate is four times higher than Finland’s.
Delegations and universities from China and around the developing world are visiting Finland to learn how to improve their own school systems.Singapore has launched a series of Finnish-style school reforms.

n Finland, we heard none of the clichés common in U.S. education reform circles, like “rigor,” “standards-based accountability,” “data-driven instruction,” “teacher evaluation through value-added measurement” or getting children “college- and career-ready” starting in kindergarten.

Instead, Finnish educators and officials constantly stressed to us their missions of helping every child reach his or her full potential and supporting all children’s well-being. “School should be a child’s favorite place,” said Heikki Happonen, an education professor at the University of Eastern Finland and an authority on creating warm, child-centered learning environments.

How can the United States improve its schools? We can start by piloting and implementing these 12 global education best practices, many of which are working extremely well for Finland:

1) Emphasize well-being.

2) Upgrade testing and other assessments. 

3) Invest resources fairly.

4) Boost learning through physical activity. 

5) Change the focus. Create an emotional atmosphere and physical environment of warmth, comfort and safety so that children are happy and eager to come to school. Teach not just basic skills, but also arts, crafts, music, civics, ethics, home economics and life skills.

6) Make homework efficient. Reduce the homework load in elementary and middle schools to no more than 30 minutes per night, and make it responsibility-based rather than stress-based.

7) Trust educators and children. Give them professional respect, creative freedom and autonomy, including the ability to experiment, take manageable risks and fail in the pursuit of success.

8) Shorten the school day. Deliver lessons through more efficient teaching and scheduling, as Finland does. Simplify curriculum standards to a framework that can fit into a single book, and leave detailed implementation to local districts.

9) Institute universal after-school programs.

10) Improve, expand and destigmatize vocational and technical education.   Encourage more students to attend schools in which they can acquire valuable career/trade skills.

11) Launch preventive special-education interventions early and aggressively. 

12) Revamp teacher training toward a medical and military model. Shift to treating the teaching profession as a critical national security function requiring government-funded, graduate-level training in research and collaborative clinical practice, as Finland does.

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more on Finland Phenomenon in this IMS blog
http://blog.stcloudstate.edu/ims?s=finland+phenomenon

Preparing Learners for 21st Century Digital Citizenship

ID2ID webinar (my notes on the bottom)

Digital Fluency: Preparing Learners for 21st Century Digital Citizenship
Eighty-five percent of the jobs available in 2030 do not yet exist.  How does higher education prepare our learners for careers that don’t yet exist?  One opportunity is to provide our students with opportunities to grow their skills in creative problem solving, critical thinking, resiliency, novel thinking, social intelligence, and excellent communication skills.  Instructional designers and faculty can leverage the framework of digital fluency to create opportunities for learners to practice and hone the skills that will prepare them to be 21st-century digital citizens.  In this session, join a discussion about several fluencies that comprise the overarching framework for digital fluency and help to define some of your own.

Please click this URL to join. https://arizona.zoom.us/j/222969448

Dr. Jennifer Sparrow, Senior Director for Teaching and Learning with Technology and Affiliate Assistant Professor of Learning, Design, and Technology at Penn State.    The webinar will take place on Friday, November 9th at 11am EST/4pm UTC (login details below)  

https://arizona.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=e15266ee-7368-4378-b63c-a99301274877

My notes:

Jennifer does NOT see phone use for learning as an usage to obstruct. Similarly as with the calculator some 30-40 years ago, it was frowned upon, so now is technology. To this notion, added the fast-changing job market: new jobs created, old disappearing (https://www.nbcnews.com/news/us-news/students-are-being-prepared-jobs-no-longer-exist-here-s-n865096)

how DF is different from DLiteracy? enable students define how new knowledge can be created through technology. Not only read and write, but create poems, stories, if analogous w learning a language. slide 4 in https://www.slideshare.net/aidemoreto/vr-library

communication fluency. be able to choose the correct media. curiosity/failure fluency; creation fluency (makerspace: create without soldering, programming, 3Dprinting. PLA filament-corn-based plastic; Makers-in-residence)

immersive fluency: video 360, VR and AR. enable student to create new knowledge through environments beyond reality. Immersive Experiences Lab (IMEX). Design: physical vs virtual spaces.

Data fluency: b.book. how to create my own textbook

rubrics and sample projects to assess digital fluency.

https://er.educause.edu/articles/2018/3/digital-fluency-preparing-students-to-create-big-bold-problems

https://events.educause.edu/annual-conference/2018/agenda/ethics-and-digital-fluency-in-vr-and-immersive-learning-environments

Literacy Is NOT Enough: 21st Century Fluencies for the Digital Age (The 21st Century Fluency Series)
https://www.amazon.com/Literacy-NOT-Enough-Century-Fluencies/dp/1412987806

What is Instructional Design 2.0 or 3.0? deep knowledge and understanding of faculty development. second, once faculty understands the new technology, how does this translate into rework of curriculum? third, the research piece; how to improve to be ready for the next cycle. a partnership between ID and faculty.

netnography

Xu Zhang. (2017). The Quality of Virtual Communities: A Case Study of Chinese Overseas Students in WeChat Groups. Global Studies Journal, 10(3), 19–26. https://doi.org/10.18848/1835-4432/CGP/v10i03/19-26
p. 23-24.
“Netnography” has been developed for online community researchers. It is “net” plus “ethnography,” which is based on the traditional ethnography and combines with the qualitative analysis for online interactive contents forms of virtual community members. The aim of doing netnographic research is to study the subculture, interactive process and characteristics of collective behaviors of online communities (Kozinets 2009). Follow the development of Internet technology, the web–based method is more convenient and cost–effect in data collection. Members in virtual groups create a large number of interactive texts, pictures, network expressions and other original information over time, which provides an extremely rich database to researchers. Moreover, from the data collection’s point of view, this online observation method will not interfere with the whole research process, which is better than questionnaires and quantitative modeling (Moisander and Valtonen 2006). Additionally, Kozinets (2009) also pointed that netnogrpahy emphasize on the research background, observers not only focus on the text during communications but also need to pay attention to the characteristics of language, history, meaning and communication types. Even parse fonts, symbols, images and photo data. These content of studies are significant in social communication, which is called “Cultural Artifact.” On the other hand, netnography is based on traditional ethnography as a methodology; therefore it inherits the research processes of ethnographic method. Kozients (2009) reinterpreted these procedures for netnography as Firstly, to determine the research target and understand its cultural characteristics; Secondly, to collect and analyze information; Thirdly, to ensure the credibility of interpretation; Fourthly, pay attention to research ethics; Lastly, to obtain respondents feedbacks. To make my research adapting to this guidelines, I make my research process as 1. To target on Plymouth Chinese overseas students and to explain the Chinese guanxi; 2. To collect and analyze data through the existing WeChat group created by Plymouth Chinese Students and Scholars Association (CSSA); 3. To confirm the identity of key influencers in this virtual group; 4. To get feedbacks from respondent as much as possible.
https://en.wikipedia.org/wiki/Netnography

What is Netnography from Harrison Hayes, LLC
https://nsuworks.nova.edu/tqr/vol15/iss5/13/

Incompetent Leader

The Most Common Type of Incompetent Leader

Scott Gregory  MARCH 30, 2018

https://hbr.org/2018/03/the-most-common-type-of-incompetent-leader

Researchers have studied managerial derailment — or the dark side of leadership — for many years. The key derailment characteristics of bad managers are well documented and fall into three broad behavioral categories: (1) “moving away behaviors,” which create distance from others through hyper-emotionality, diminished communication, and skepticism that erodes trust; (2) “moving against behaviors,” which overpower and manipulate people while aggrandizing the self; and (3) “moving toward behaviors,” which include being ingratiating, overly conforming, and reluctant to take chances or stand up for one’s team. The popular media is full of examples of bad leaders in government, academia, and business with these characteristics.

Absentee leadership rarely comes up in today’s leadership or business literature, but research shows that it is the most common form of incompetent leadership.

Absentee leaders are people in leadership roles who are psychologically absent from them. They were promoted into management, and enjoy the privileges and rewards of a leadership role, but avoid meaningful involvement with their teams. Absentee leadership resembles the concept of rent-seeking in economics — taking value out of an organization without putting value in. As such, they represent a special case of laissez-faire leadership, but one that is distinguished by its destructiveness.

Having a boss who lets you do as you please may sound ideal, especially if you are being bullied and micromanaged by your current boss. However, a 2015 survey of 1,000 working adults showed that eight of the top nine complaints about leaders concerned behaviors that were absent; employees were most concerned about what their bosses didn’t do.

Research shows that being ignored by one’s boss is more alienating than being treated poorly. The impact of absentee leadership on job satisfaction outlasts the impact of both constructive and overtly destructive forms of leadership. Constructive leadership immediately improves job satisfaction, but the effects dwindle quickly. Destructive leadership immediately degrades job satisfaction, but the effects dissipate after about six months. In contrast, the impact of absentee leadership takes longer to appear, but it degrades subordinates’ job satisfaction for at least two years. It also is related to a number of other negative outcomes for employees, like role ambiguityhealth complaints, and increased bullying from team members. Absentee leadership creates employee stress, which can lead to poor employee health outcomes and talent drain, which then impact an organization’s bottom line.

Because absentee leaders don’t actively make trouble, their negative impact on organizations can be difficult to detect, and when it is detected, it often is considered a low-priority problem. Thus, absentee leaders are often silent organization killers. Left unchecked, absentee leaders clog an organization’s succession arteries, blocking potentially more effective people from moving into important roles while adding little to productivity. Absentee leaders rarely engage in unforgivable bouts of bad behavior, and are rarely the subject of ethics investigations resulting from employee hotline calls. As a result, their negative effect on organizations accumulates over time, largely unchecked.

Constructive leadership creates high engagement and productivity, while destructive leadership kills engagement and productivity. 

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more on what makes “great leader” in this IMS blog

leader charts

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