Will Letter Grades Survive? — from edutopia.org by Laura McKenna
A century-old pillar of the school system is under fire as schools look to modernize student assessment.

Excerpt:

Under pressure from an unprecedented constellation of forces—from state lawmakers to prestigious private schools and college admissions offices—the ubiquitous one-page high school transcript lined with A–F letter grades may soon be a relic of the past.

In the last decade, at least 15 state legislatures and boards of education have adopted policies incentivizing their public schools to prioritize measures other than grades when assessing students’ skills and competencies. And more recently, over 150 of the top private high schools in the U.S., including Phillips Exeter and Dalton—storied institutions which have long relied on the status conveyed by student ranking—have pledged to shift to new transcripts that provide more comprehensive, qualitative feedback on students while ruling out any mention of credit hours, GPAs, or A–F grades.

 

 

“The grading system right now is demoralizing and is designed to produce winners and losers,” said Looney. “The purpose of education is not to sort kids—it’s to grow kids. Teachers need to coach and mentor, but with grades, teachers turn into judges. I think we can show the unique abilities of kids without stratifying them.”

 

 


There are other unanswered questions and challenges to be worked out, too. Will college admissions counselors have enough time, especially at large public colleges, to look meaningfully at dense digital portfolios of student work? Will the new transcripts create too much work and new training for K-12 teachers, as they struggle to measure hard-to-define categories of learning? Perhaps most importantly, will parents buy in?

 

 

 

Also relevant/see:

What Failing Students Want Us to Remember — from edutopia.org by Rebecca Alber
By seeing students as more than their grades, we can enable them to reach their potential.

Excerpt:

1. I am not my grade. I don’t get good grades or earn a lot of points on assignments even though I know some stuff. I often won’t even try because I know I’m going to get a bad grade. I wish there were other ways besides grades or points to show who I really am.

2. I can still contribute meaningfully. I like to help, but I pretend sometimes like I don’t and that I don’t care about being part of the school or my class. I protect myself because in school, the kids with good grades get picked to help more often.

3. I am not a disappointment. School is hard, and I know I let my teachers down, and when working in a group, I let down my classmates too. Because of this, I struggle to feel good about myself every day. What am I doing right? I wish in school that we could look at all the stuff we do right and not just mostly the things we do wrong.

4. Meet me where I am. There’s stuff I can do—just not this, right now, like this. I wish I had more time. I wish the directions and assignments made more sense to me. So much of school is so rushed and confusing.

5. Don’t give up. Find a way for me. I’m not sure why I don’t get it. I want someone to keep trying to find out. It’s not that I don’t want to do it, even though it sometimes looks like that. It helps when adults ask me questions. I can’t do it right now, but maybe someday I’ll be able to.

 

 

 

 

 

FREEDOM 2.0 – Blockchain’s Biggest Use Case with Richie Etwaru @richieetwaru — with thanks to Mike Mathews for his posting this on LinkedIn

Description:

While the Internet has profoundly impacted global society, new questions must be asked. When the human species reflects on the Internet in 2081 a hundred years after its invention will the Internet be viewed as good for our species, and has the impact of the set of adjacent inventions of the Internet furthered the triumph of the human species? Did we connect the last billion with mobility, did we distribute wealth meaningfully, and was basic healthcare democratized? Or, did social media coupled with mobile cameras create a spike in vanity that affected important social constructs such as love, self-esteem and family? Did AI create a new class system of robo sapiens that constrict freedom? And did we change the core of commerce of trust between citizens, communities and governments? Maybe; the Internet is only 49% of the story of our species, and the remaining 51% of our story is still unfolding. Richie will discuss the other 51% which he believes is blockchain, and how we can change the answers to some of these new types of questions of mankind.

 

 

 

 

 

 

 

The Advantages of Blockchain Technology — from hortonworks.com by Ryan Wheeler

Excerpt:

Blockchain ensures data objectivity—a single source of truth. Blockchain also represents a security layer that ensures that data is encrypted in such a way that only the people you want to can read your data. It makes it next to impossible for people to corrupt or manipulate the data—or even gain wrongful access to it—because the system raises an instant red flag when a problem occurs, and it uses a new, advanced encryption method to secure the data.

Blockchain is both reactionary—alerting users to changes—and proactive, by preventing the security threat. And even if the data is somehow breached, it still can’t be used. The effects have already been seen in the healthcare industry, where technologies using blockchain have provided the proper balance of security and governance for people’s health data.

 

 

 

From DSC:
Interesting to see this new platform developing, one that combines 2 big trends — blockchain and freelancing:

 

 

 

Also interesting to see:

 

“Peculium: The first savings system in cryptocurrency utilizing AIEVE and Blockchain Technology with artificial intelligence. PECULIUM revolutionizes savings management by deploying immutable Smart-Contracts over Ethereum blockchain.”

 

 

 

 

 

Addendum/also see:

 

The blockchain provides a rich, secure, and transparent platform on which to create a global network for higher learning. This Internet of value can help to reinvent higher education in a way the Internet of information alone could not.

 

 

 

The legal and ethical minefield of AI: ‘Tech has the power to do harm as well as good’ — from theguardian.com by Joanna Goodman

Excerpt:

Artificial intelligence and machine learning tools are already embedded in our lives, but how should businesses that use such technology manage the associated risks?

As artificial intelligence (AI) penetrates deeper into business operations and services, even supporting judicial decision-making, are we approaching a time when the greatest legal mind could be a machine? According to Prof Dame Wendy Hall, co-author of the report Growing the Artificial Intelligence Industry in the UK, we are just at the beginning of the AI journey and now is the time to set boundaries.

“All tech has the power to do harm as well as good,” Hall says. “So we have to look at regulating companies and deciding what they can and cannot do with the data now.”

AI and robotics professor Noel Sharkey highlights the “legal and moral implications of entrusting human decisions to algorithms that we cannot fully understand”. He explains that the narrow AI systems that businesses currently use (to draw inferences from large volumes of data) apply algorithms that learn from experience and feed back to real-time and historical data. But these systems are far from perfect.

Potential results include flawed outcomes or reasoning, but difficulties also arise from the lack of transparency. This supports Hall’s call for supervision and regulation. Businesses that use AI in their operations need to manage the ethical and legal risks, and the legal profession will have a major role to play in assessing and apportioning risk, responsibility and accountability.

 

 

Also see:

 

 

 

 

Blockchain and Distributed Web: Why You Should Care — from ideou.com

Excerpt:

To help get our heads around emerging tech, we invited our IDEO friends, IDEO CoLab, in for a Creative Confidence Series session about emerging tech (and why you should care).

In this first session, we sat down with CoLab’s Joe Gerber and Gavin McDermott to talk about the distributed web and blockchain and why it’s important to experiment with these emerging technologies. Many people conflate blockchain and bitcoin, but as Joe and Gavin discussed, bitcoin is just the tip of the spear and one small piece of a larger movement of blockchain and the distributed web. In this post, we’ll break down why, as Joe and Gavin say, the web is being rewritten from the inside out.

First, some definitions:

  • Blockchain: A blockchain is a peer-to-peer network that logs shared information about transactions. It’s provable because the transaction is validated by a broad network of computers. Joe quoted Vitalik Buterin likening blockchain to “a database we all agree on.” The magic of blockchain is that it solves the problem of digital abundance and computers’ innate ability for infinite copying by creating scarcity, ensuring that only one copy of something exists.
  • Bitcoin: Bitcoin is a cryptocurrency that uses blockchain technology, but there are a number of different applications for blockchain including contracts (smart contracts) and other types of information.
  • Distributed web: A movement that’s a complete reimagining of today’s internet infrastructure, it includes new and different protocols. We rely on protocols every day for things like email (simple mail transfer protocol, SMTP, allows Gmail, Yahoo Mail or Hotmail to all communicate) or for web browsing (hypertext transfer protocol, HTTP). In the distributed web, new peer-to-peer networks that do not rely on centralization are being built.

 

These technologies are still in their early days of construction and the blueprints are changing every day. What Joe and Gavin would recommend is that you start to experiment and prototype with these technologies to test assumptions for how they could affect your business. Don’t get ready, get started.

 

 

 

 

 

Top 10 Technology Trends for 2018: IEEE Computer Society Predicts the Future of Tech — from computer.org

Excerpts:

The top 10 technology trends predicted to reach adoption in 2018 are:

  1. Deep learning (DL)
  2. Digital currencies.
  3. Blockchain.
  4. Industrial IoT.
  5. Robotics.
  6. Assisted transportation.
  7. Assisted reality and virtual reality (AR/VR).
  8. Ethics, laws, and policies for privacy, security, and liability.
  9. Accelerators and 3D.
  10. Cybersecurity and AI.

Existing Technologies: We did not include the following technologies in our top 10 list as we assume that they have already experienced broad adoption:

A. Data science
B. “Cloudification”
C. Smart cities
D. Sustainability
E. IoT/edge computing

 

 

 


Also relevant/see:


 

 

 

From DSC:
Regarding the article below…why did it take Udacity needing to team up with Infosys to offer this type of program and curriculum? Where are the programs in institutions of traditional higher education on this?  Are similar programs being developed? If so, how quickly will they come to market? I sure hope that such program development is in progress..and perhaps it is. But the article below goes to show us that alternatives to traditional higher education seem to be more responsive to the new, exponential pace of change that we now find ourselves in.

We have to pick up the pace! To do this, we need to identify any obstacles to our institutions adapting to this new pace of change — and then address them immediately. I see our current methods of accreditation as one of the areas that we need to address. We’ve got to get solid programs to market much faster!

And for those folks in higher ed who say change isn’t happening rapidly — that it’s all a bunch of hype — you likely still have a job. But you need to go talk with some people who don’t, or who’ve had their jobs recently impacted big time. Here are some suggestions of folks to talk with:

  • Taxi drivers who were impacted by Lyft and by Uber these last 5-10 years; they may still have their jobs, if they’re lucky. But they’ve been impacted big time…and are likely driving for Lyft and/or Uber as well as their former employers; they’re likely to have less bargaining power than they used to as the supply of drivers has skyrocketed. (By the way, the very existence of such organizations couldn’t have happened without the smartphone and mobile-related technologies/telecommunications.)
  • Current managers and former employees at hotels/motels about the impacts on their industry by AirBnB over a similar time frame
  • Hiring managers at law firms who’ve cut back on hiring entry-level lawyers…work that’s increasingly being done by software (example)
  • Employees who worked at brick and mortar retailers who have been crushed by Amazon.com’s online-based presence (in not that long of time, by the way). For example, below is what our local Sears store looks like these days…go find an employee who used to work at Sears or a Sears automotive-related store:

 

This is what our local Sears store looks like today

This picture is for those who say there is no disruption.
You call
this hype?!

 

The above example list — that’s admittedly woefully incomplete — doesn’t include the folks displaced by technology over the last several decades, such as:

  • Former bank tellers who lost their jobs to ATMs
  • Checkout clerks at the grocery stores who lost their jobs to self-service stations
  • Check-in agents at the airports who lost their jobs to self-service stations
  • Etc., etc., etc.

Institutions of traditional higher education
need to pick up the pace — big time!

 


Infosys and Udacity team up to train 500 engineers in autonomous technologies — from by Leah Brown
Infosys’ COO Ravi Kumar explains how these individuals can apply what they learn to other industries.

Excerpt (emphasis DSC):

Infosys, a global technology consulting firm, recently partnered with online learning platform Udacity to create a connected service that provides training for autonomous vehicles, and other services for B2B providers of autonomous vehicles.

TechRepublic’s Dan Patterson met with Infosys’ COO Ravi Kumar to discuss how autonomous technology can help create new industries.

Autonomous technology is going to be an emerging technology of the future, Kumar said. So Infosys and Udacity came together and developed a plan to train 500 engineers on autonomous technologies, and teach them how to apply it to other industries.

 

Per Wikipedia:
Udacity is a for-profit educational organization founded by Sebastian Thrun, David Stavens, and Mike Sokolsky offering massive open online courses (MOOCs). According to Thrun, the origin of the name Udacity comes from the company’s desire to be “audacious for you, the student.” While it originally focused on offering university-style courses, it now focuses more on vocational courses for professionals.

 


 

But times are changing. Artificial intelligence (AI) and robotics are facilitating the automation of a growing number of “doing” tasks. Today’s AI-enabled, information-rich tools are increasingly able to handle jobs that in the past have been exclusively done by people—think tax returns, language translations, accounting, even some kinds of surgery. These shifts will produce massive disruptions to employment and hold enormous implications for you as a business leader. (mckinsey.com)

 


 

 

AI: Embracing the promises and realities — from the Allegis Group

Excerpts:

What will that future be? When it comes to jobs, the tea leaves are indecipherable as analysts grapple with emerging technologies, new fields of work, and skills that have yet to be conceived. The only certainty is
that jobs will change. Consider the conflicting predictions put forth by the analyst community:

  • According to the Organization of Economic Cooperation and Development, only 5-10% of labor would be displaced by intelligent automation, and new job creation will offset losses.  (Inserted comment from DSC: Hmmm. ONLY 5-10%!? What?! That’s huge! And don’t count on the majority of those people becoming experts in robotics, algorithms, big data, AI, etc.)
  • The World Economic Forum27 said in 2016 that 60% of children entering school today will work in jobs that do not yet exist.
  • 47% of all American job functions could be automated within 20 years, according to the Oxford Martin School on Economics in a 2013 report.
  • In 2016, a KPMG study estimated that 100 million global knowledge workers could be affected by robotic process automation by 2025.

Despite the conflicting views, most analysts agree on one thing: big change is coming. Venture Capitalist David Vandergrift has some words of advice: “Anyone not planning to retire in the next 20 years should be paying pretty close attention to what’s going on in the realm of AI. The supplanting (of jobs) will not happen overnight: the trend over the next couple of decades is going to be towards more and more automation.”30

While analysts may not agree on the timing of AI’s development in the economy, many companies are already seeing its impact on key areas of talent and business strategy. AI is replacing jobs, changing traditional roles, applying pressure on knowledge workers, creating new fields of work, and raising the demand for certain skills.

 

 

 

 

 

The emphasis on learning is a key change from previous decades and rounds of automation. Advanced AI is, or will soon be, capable of displacing a very wide range of labor, far beyond the repetitive, low-skill functions traditionally thought to be at risk from automation. In many cases, the pressure on knowledge workers has already begun.

 

 

 

 

Regardless of industry, however, AI is a real challenge to today’s way of thinking about work, value, and talent scarcity. AI will expand and eventually force many human knowledge workers to reinvent their roles to address issues that machines cannot process. At the same time, AI will create a new demand for skills to guide its growth and development. These emerging areas of expertise will likely be technical or knowledge-intensive fields. In the near term, the competition for workers in these areas may change how companies focus their talent strategies.

 

 

 

 

How artificial intelligence could transform government — from Deloitte University Press
Cognitive technologies have the potential to revolutionize the public sector—and save billions of dollars

Excerpt:

The rise of more sophisticated cognitive technologies is, of course, critical to that third era, aiding advances in several categories:

  • Rules-based systems capture and use experts’ knowledge to provide answers to tricky but routine problems. As this decades-old form of AI grows more sophisticated, users may forget they aren’t conversing with a real person.
  • Speech recognition transcribes human speech automatically and accurately. The technology is improving as machines collect more examples of conversation. This has obvious value for dictation, phone assistance, and much more.
  • Machine translation, as the name indicates, translates text or speech from one language to another. Significant advances have been made in this field in only the past year.8 Machine translation has obvious implications for international relations, defense, and intelligence as well as, in our multilingual society, numerous domestic applications.
  • Computer vision is the ability to identify objects, scenes, and activities in naturally occurring images. It’s how Facebook sorts millions of users’ photos, but it can also scan medical images for indications of disease and identify criminals from surveillance footage. Soon it will allow law enforcement to quickly scan license plate numbers of vehicles stopped at red lights, identifying suspects’ cars in real time.
  • Machine learning takes place without explicit programming. By trial and error, computers learn how to learn, mining information to discover patterns in data that can help predict future events. The larger the datasets, the easier it is to accurately gauge normal or abnormal behavior. When your email program flags a message as spam, or your credit card company warns you of a potentially fraudulent use of your card, machine learning may be involved. Deep learning is a branch of machine learning involving artificial neural networks inspired by the brain’s structure and function.9
  • Robotics is the creation and use of machines to perform automated physical functions. The integration of cognitive technologies such as computer vision with sensors and other sophisticated hardware has given rise to a new generation of robots that can work alongside people and perform many tasks in unpredictable environments. Examples include drones, robots used for disaster response, and robot assistants in home health care.
  • Natural language processing refers to the complex and difficult task of organizing and understanding language in a human way. This goes far beyond interpreting search queries, or translating between Mandarin and English text. Combined with machine learning, a system can scan websites for discussions of specific topics even if the user didn’t input precise search terms. Computers can identify all the people and places mentioned in a document or extract terms and conditions from contracts. As with all AI-enabled technology, these become smarter as they consume more accurate data—and as developers integrate complementary technologies such as machine translation and natural language processing.

We’ve developed a framework that can help government agencies assess their own opportunities for deploying these technologies. It involves examining business processes, services, and programs to find where cognitive technologies may be viable, valuable, or even vital. Figure 8 summarizes this “Three Vs” framework. Government agencies can use it to screen the best opportunities for automation or cognitive technologies.

 

 

 

 

WE ARE NOT READY FOR THIS! Per Forrester Research: In US, a net loss of 7% of jobs to automation — *in 2018*!

Forrester predicts that AI-enabled automation will eliminate 9% of US jobs in 2018 — from forbes.com by Gil Press

Excerpt (emphasis DSC):

A new Forrester Research report, Predictions 2018: Automation Alters The Global Workforce, outlines 10 predictions about the impact of AI and automation on jobs, work processes and tasks, business success and failure, and software development, cybersecurity, and regulatory compliance.

We will see a surge in white-collar automation, half a million new digital workers (bots) in the US, and a shift from manual to automated IT and data management. “Companies that master automation will dominate their industries,” Forrester says. Here’s my summary of what Forrester predicts will be the impact of automation in 2018:

Automation will eliminate 9% of US jobs but will create 2% more.
In 2018, 9% of US jobs will be lost to automation, partly offset by a 2% growth in jobs supporting the “automation economy.” Specifically impacted will be back-office and administrative, sales, and call center employees. A wide range of technologies, from robotic process automation and AI to customer self-service and physical robots will impact hiring and staffing strategies as well as create a need for new skills.

 

Your next entry-level compliance staffer will be a robot.

 

From DSC:

Are we ready for a net loss of 7% of jobs in our workforce due to automation — *next year*? Last I checked, it was November 2017, and 2018 will be here before we know it.

 

***Are we ready for this?! ***

 

AS OF TODAY, can we reinvent ourselves fast enough given our current educational systems, offerings, infrastructures, and methods of learning?

 

My answer: No, we can’t. But we need to be able to — and very soon!

 

 

There are all kinds of major issues and ramifications when people lose their jobs — especially this many people and jobs! The ripple effects will be enormous and very negative unless we introduce new ways for how people can learn new things — and quickly!

That’s why I’m big on trying to establish a next generation learning platform, such as the one that I’ve been tracking and proposing out at Learning from the Living [Class] Room. It’s meant to provide societies around the globe with a powerful, next generation learning platform — one that can help people reinvent themselves quickly, cost-effectively, conveniently, & consistently! It involves providing, relevant, up-to-date streams of content that people can subscribe to — and drop at any time. It involves working in conjunction with subject matter experts who work with teams of specialists, backed up by suites of powerful technologies. It involves learning with others, at any time, from any place, at any pace. It involves more choice, more control. It involves blockchain-based technologies to feed cloud-based learner profiles and more.

But likely, bringing such a vision to fruition will require a significant amount of collaboration. In my mind, some of the organizations that should be at the table here include:

  • Some of the largest players in the tech world, such as Amazon, Google, Apple, IBM, Microsoft, and/or Facebook
  • Some of the vendors that already operate within the higher ed space — such as Salesforce.com, Ellucian, and/or Blackboard
  • Some of the most innovative institutions of higher education — including their faculty members, instructional technologists, instructional designers, members of administration, librarians, A/V specialists, and more
  • The U.S. Federal Government — for additional funding and the development of policies to make this vision a reality

 

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

 

2018 Tech Trends for Journalism & Media Report + the 2017 Tech Trends Annual Report that I missed from the Future Today Institute

 

2018 Tech Trends For Journalism Report — from the Future Today Institute

Key Takeaways

  • 2018 marks the beginning of the end of smartphones in the world’s largest economies. What’s coming next are conversational interfaces with zero-UIs. This will radically change the media landscape, and now is the best time to start thinking through future scenarios.
  • In 2018, a critical mass of emerging technologies will converge finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. News organizations should devote attention to emerging trends in voice interfaces, the decentralization of content, mixed reality, new types of search, and hardware (such as CubeSats and smart cameras).
  • Journalists need to understand what artificial intelligence is, what it is not, and what it means for the future of news. AI research has advanced enough that it is now a core component of our work at FTI. You will see the AI ecosystem represented in many of the trends in this report, and it is vitally important that all decision-makers within news organizations familiarize themselves with the current and emerging AI landscapes. We have included an AI Primer For Journalists in our Trend Report this year to aid in that effort.
  • Decentralization emerged as a key theme for 2018. Among the companies and organizations FTI covers, we discovered a new emphasis on restricted peer-to-peer networks to detect harassment, share resources and connect with sources. There is also a push by some democratic governments around the world to divide internet access and to restrict certain content, effectively creating dozens of “splinternets.”
  • Consolidation is also a key theme for 2018. News brands, broadcast spectrum, and artificial intelligence startups will continue to be merged with and acquired by relatively few corporations. Pending legislation and policy in the U.S., E.U. and in parts of Asia could further concentrate the power among a small cadre of information and technology organizations in the year ahead.
  • To understand the future of news, you must pay attention to the future of many industries and research areas in the coming year. When journalists think about the future, they should broaden the usual scope to consider developments from myriad other fields also participating in the knowledge economy. Technology begets technology. We are witnessing an explosion in slow motion.

Those in the news ecosystem should factor the trends in this report into their strategic thinking for the coming year, and adjust their planning, operations and business models accordingly.

 



 

 

2017 Tech Trends Annual Report — from the Future Today Institute; this is the first I’ve seen this solid report

Excerpts:

This year’s report has 159 trends.
This is mostly due to the fact that 2016 was the year that many areas of science and technology finally started to converge. As a result we’re seeing a sort of slow-motion explosion––we will undoubtedly look back on the last part of this decade as a pivotal moment in our history on this planet.

Our 2017 Trend Report reveals strategic opportunities and challenges for your organization in the coming year. The Future Today Institute’s annual Trend Report prepares leaders and organizations for the year ahead, so that you are better positioned to see emerging technology and adjust your strategy accordingly. Use our report to identify near-future business disruption and competitive threats while simultaneously finding new collaborators and partners. Most importantly, use our report as a jumping off point for deeper strategic planning.

 

 



 

Also see:

Emerging eLearning Tools and Platforms Improve Results — from learningsolutionsmag.com

  • Augmented and virtual reality offer ways to immerse learners in experiences that can aid training in processes and procedures, provide realistic simulations to deepen empathy and build communication skills, or provide in-the-workflow support for skilled technicians performing complex procedures.
  • Badges and other digital credentials provide new ways to assess and validate employees’ skills and mark their eLearning achievements, even if their learning takes place informally or outside of the corporate framework.
  • Chatbots are proving an excellent tool for spaced learning, review of course materials, guiding new hires through onboarding, and supporting new managers with coaching and tips.
  • Content curation enables L&D professionals to provide information and educational materials from trusted sources that can deepen learners’ knowledge and help them build skills.
  • eBooks, a relative newcomer to the eLearning arena, offer rich features for portable on-demand content that learners can explore, review, and revisit as needed.
  • Interactive videos provide branching scenarios, quiz learners on newly introduced concepts and terms, offer prompts for small-group discussions, and do much more to engage learners.
  • Podcasts can turn drive time into productive time, allowing learners to enjoy a story built around eLearning content.
  • Smartphone apps, available wherever learners take their phones or tablets, can be designed to offer product support, info for sales personnel, up-to-date information for repair technicians, and games and drills for teaching and reviewing content; the possibilities are limited only by designers’ imagination.
  • Social platforms like Slack, Yammer, or Instagram facilitate collaboration, sharing of ideas, networking, and social learning. Adopting social learning platforms encourages learners to develop their skills and contribute to their communities of practice, whether inside their companies or more broadly.
  • xAPI turns any experience into a learning experience. Adding xAPI capability to any suitable tool or platform means you can record learner activity and progress in a learning record store (LRS) and track it.

 



 

DevLearn Attendees Learn How to ‘Think Like a Futurist’ — from learningsolutionsmag.com

Excerpt:

How does all of this relate to eLearning? Again, Webb anticipated the question. Her response gave hope to some—and terrified others. She presented three possible future scenarios:

  • Everyone in the learning arena learns to recognize weak signals; they work with technologists to refine artificial intelligence to instill values. Future machines learn not only to identify correct and incorrect answers; they also learn right and wrong. Webb said that she gives this optimistic scenario a 25 percent chance of occurring.
  • Everyone present is inspired by her talk but they, and the rest of the learning world, do nothing. Artificial intelligence continues to develop as it has in the past, learning to identify correct answers but lacking values. Webb’s prediction is that this pragmatic optimistic scenario has a 50 percent chance of occurring.
  • Learning and artificial intelligence continue to develop on separate tracks. Future artificial intelligence and machine learning projects incorporate real biases that affect what and how people learn and how knowledge is transferred. Webb said that she gives this catastrophic scenario a 25 percent chance of occurring.

In an attempt to end on a strong positive note, Webb said that “the future hasn’t happened yet—we think” and encouraged attendees to take action. “To build the future of learning that you want, listen to weak signals now.”

 



 

 

 

 

 

Artificial Intelligence in Education: Where It’s At, Where It’s Headed — from gettingsmart.com by Cameron Paterson

Excerpt:

Artificial intelligence is predicted to fundamentally alter the nature of society by 2040. Investment in AI start-ups was estimated at $6-$9 billion in 2016, up from US$415 million four years earlier. While futurist Ray Kurzweil argues that AI will help us to address the grand challenges facing humanity, Elon Musk warns us that artificial intelligence will be our “biggest existential threat.” Others argue that artificial intelligence is the future of growth. Everything depends on how we manage the transition to this AI-era.

In 2016 the Obama administration released a national strategic plan for artificial intelligence and, while we do not all suddenly now need a plan for artificial intelligence, we do need to stay up to date on how AI is being implemented. Much of AI’s potential is yet to be realized, but AI is already running our lives, from Siri to Netflix recommendations to automated air traffic control. We all need to become more aware of how we are algorithmically shaped by our tools.

This Australian discussion paper on the implications of AI, automation and 21st-century skills, shows how AI will not just affect blue-collar truck drivers and cleaners, it will also affect white-collar lawyers and doctors. Automated pharmacy systems with robots dispensing medication exist, Domino’s pizza delivery by drone has already occurred, and a fully automated farm is opening in Japan.

 

Education reformers need to plan for our AI-driven future and its implications for education, both in schools and beyond. The never-ending debate about the sorts of skills needed in the future and the role of schools in teaching and assessing them is becoming a whole lot more urgent and intense.

 

 

 

AI Experts Want to End ‘Black Box’ Algorithms in Government — from wired.com by Tom Simonite

Excerpt:

The right to due process was inscribed into the US constitution with a pen. A new report from leading researchers in artificial intelligence cautions it is now being undermined by computer code.

Public agencies responsible for areas such as criminal justice, health, and welfare increasingly use scoring systems and software to steer or make decisions on life-changing events like granting bail, sentencing, enforcement, and prioritizing services. The report from AI Now, a research institute at NYU that studies the social implications of artificial intelligence, says too many of those systems are opaque to the citizens they hold power over.

The AI Now report calls for agencies to refrain from what it calls “black box” systems opaque to outside scrutiny. Kate Crawford, a researcher at Microsoft and cofounder of AI Now, says citizens should be able to know how systems making decisions about them operate and have been tested or validated. Such systems are expected to get more complex as technologies such as machine learning used by tech companies become more widely available.

“We should have equivalent due-process protections for algorithmic decisions as for human decisions,” Crawford says. She says it can be possible to disclose information about systems and their performance without disclosing their code, which is sometimes protected intellectual property.

 

 

UAE appoints first-ever Minister for Artificial Intelligence — from tribune.com.pk

 

“We announce the appointment of a minister for artificial intelligence. The next global wave is artificial intelligence and we want the UAE to be more prepared for it.”

 

 

Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent — from nytimes.com by Cade Metz
Nearly all big tech companies have an artificial intelligence project, and they are willing to pay experts millions of dollars to help get it done.

Excerpt:

Tech’s biggest companies are placing huge bets on artificial intelligence, banking on things ranging from face-scanning smartphones and conversational coffee-table gadgets to computerized health care and autonomous vehicles. As they chase this future, they are doling out salaries that are startling even in an industry that has never been shy about lavishing a fortune on its top talent.

Typical A.I. specialists, including both Ph.D.s fresh out of school and people with less education and just a few years of experience, can be paid from $300,000 to $500,000 a year or more in salary and company stock, according to nine people who work for major tech companies or have entertained job offers from them. All of them requested anonymity because they did not want to damage their professional prospects.

With so few A.I. specialists available, big tech companies are also hiring the best and brightest of academia. In the process, they are limiting the number of professors who can teach the technology.

 

 

 

Where will AI play? By Mike Quindazzi.

 

 

 

 

10 really hard decisions coming our way — from gettingsmart.com by Tom Vander Ark

Excerpt (emphasis DSC):

Things are about to get interesting. You’ve likely heard that Google’s DeepMind recently beat the world’s best Go player. But in far more practical and pervasive ways, artificial intelligence (AI) is creeping into every aspect of life–every screen you view, every search, every purchase, and every customer service contact.

What’s happening? It’s the confluence of several technologies–Moore’s law made storage, computing, and access devices almost free.

This Venn diagram illustrates how deep learning is a subset of AI and how, when combined with big data, can inform enabling technologies in many sectors. For examples, to AI and big data add:

  • Robotics, and you have industry 4.0.
  • Cameras and sensor package, and you have self-driving cars.
  • Sensors and bioinformatic maps, and you have precision medicine.

While there is lots of good news here–diseases will be eradicated and clean energy will be produced–we have a problem: this stuff is moving faster than civic infrastructure can handle. Innovation is outpacing public policy on all fronts. The following are 10 examples of issues coming at us fast that we (in the US in particular) are not ready to deal with.

  1. Unemployment.
  2. Income inequality.
  3. Privacy
  4. Algorithmic bias.
  5. Access.
  6. Machine ethics. 
  7. Weaponization. 
  8. Humanity. 
  9. Genome editing.
  10. Bad AI.

 


From DSC:
Readers of this blog will know that I’m big on pulse-checking the pace of technological change — because it has enormous ramifications for societies throughout the globe, as well as for individuals, workforces, corporations, jobs, education, training, higher education and more. Readers of this blog will again hear me say that the pace of change has changed. We’re now on an exponential pace/trajectory (vs. a slow, steady, linear path).

“Innovation is outpacing public policy on all fronts.”

How true this is. Our society doesn’t know how to deal with this new pace of change. How shall we tackle this thorny issue?

 


 

 

 

 

From DSC:
The article below caused me to reflect on the idea of using Income Share Agreements (ISAs) as a way for students to get through college these days. Although I appreciate that others are trying to help students get through college — an admirable goal for sure and one that I wholeheartedly share — I don’t like the means/method being proposed here. Why? Because I’m concerned that ISAs don’t offer any incentives for colleges and universities to lower their prices in the first place. The burden of debt is just spread out into the future. In fact, one could easily imagine the costs of obtaining a degree to continue to increase, because the immediate impact of the debt isn’t felt right now…it’s spread out over one’s future. The problem becomes invisible again, making it once again easy for those working within higher education to ignore.

So I hope this method doesn’t take off (as I understand it); instead, I hope that we can figure out better ways to reduce the price of obtaining a degree. Technology should be of use here.

 

Students Get Tuition Aid for a Piece of Their Future — from wsj.com by Jillian Berman
Income share agreements seem poised to take off, as costs and debt loads rise

Excerpt:

To help pay for ever-growing college costs, more students may soon be trying a new approach: selling rights to their future earnings.

Long discussed in college policy and financing circles, income share agreements, or ISAs, are poised to become more mainstream. A handful of backers currently exist that in effect have invested in college students’ futures by advancing them thousands of dollars in tuition money to bridge gaps in financing when student loans don’t quite meet all of their expenses.

Under the terms of a typical ISA, students agree to pay a percentage of their future earnings for a predetermined period in exchange for help up front with their tuition. Now, more students may have the opportunity to enter such deals, as lawmakers in Congress are working on possible ground rules for the agreements.

 

 

 

 

 

“An algorithm designed badly can go on for a long time, silently wreaking havoc.”

— Cathy O’Neil

 

 

 

Cathy O’Neil: The era of blind faith in big data must end | TED Talk | TED.com

Description:
Algorithms decide who gets a loan, who gets a job interview, who gets insurance and much more — but they don’t automatically make things fair. Mathematician and data scientist Cathy O’Neil coined a term for algorithms that are secret, important and harmful: “weapons of math destruction.” Learn more about the hidden agendas behind the formulas.

 

 

 



Addendum:

As AI Gets Smarter, Scholars Raise Ethics Questions — from by by Chris Hayhurst
Interdisciplinary artificial intelligence research fosters philosophical discussions.

Excerpt (emphasis DSC):

David Danks, head of the philosophy department at Carnegie Mellon University, has a message for his colleagues in the CMU robotics department: As they invent and develop the technologies of the future, he encourages them to consider the human dimensions of their work.

His concern? All too often, Danks says, technological innovation ignores the human need for ethical guidelines and moral standards. That’s especially true when it comes to innovations such as artificial intelligence and automation, he says.

“It’s, ‘Look at this cool technology that we’ve got. How can you stand in the way of something like this?’” says Danks. “We should be saying, ‘Wait a second. How is this technology affecting people?’”

As an example, Danks points to AI-powered medical diagnostic systems. Such tools have great potential to parse data for better decision-making, but they lack the social interaction between patient and physician that can be so important to those decisions. It’s one thing to have a technology that can diagnose a patient with strep throat and recommend a certain antibiotic, but what about a patient with cancer who happens to be a professional violinist?

“For most people, you’d just give them the most effective drug,” says Danks. “But what do you do if one of the side effects of that medication is hand tremors? I see a lot of possibilities with AI, but it’s also important to recognize the challenges.”



 

 

From DSC:
I appreciated hearing the perspectives from Bruce Dixon and Will Richardson this morning, as I listed to a webinar that they recently offered. A few key takeaways for me from that webinar — and with a document that they shared — were:

  • The world has fundamentally changed. (Bruce and Will also mentioned the new pace of change; i.e., that it’s much faster.)
  • We need to have more urgency about the need to reimagine school, not to try to improve the existing model.
  • “Because of the advent of the Web and the technologies we use to access it, learning is, in a phrase, leaving the (school) building.”
  • There is a newfound capacity to take full control of one’s own learning; self-determined learning should be at the center of students’ and teachers’ work; co-constructed curriculum
  • And today, at a moment when learners of all ages have never had more agency over their own learning, schools must unlearn centuries old mindsets and practices and relearn them in ways that truly will serve every child living in the modern, connected world.
  • Will and Bruce believe that every educator — and district for that matter — should articulate their own “principles of learning”
  • Beliefs about how kids learn (powerfully and deeply) need to be articulated and consistently communicated and lived out
  • Everything we do as educators, administrators, etc. tells a story. What stories are we telling? (For example, what does the signage around your school building say? Is it about compliance? Is is about a love of learning? Wonder? What does the 20′ jumbo tron say about priorities? Etc.)
  • Bruce and Will covered a “story audit” and how to do one

 

“Learning is, in a phrase, leaving the (school) building.”

Richardson & Dixon

 

 

Also see:

 

 

 

These educators have decades worth of experience. They are pulse-checking their environments. They want to see students thrive both now and into the future. For these reasons, at least for me, their perspectives are highly worth reflecting upon.

 

 

 
© 2024 | Daniel Christian