March, 2020

The 2019 Artificial Intelligence Index

Irving Wladawsky-Berger

AI has emerged as the defining technology of our era, as transformative over time as the steam engine, electricity, and the Internet.

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Discover2Learn

Jane Hart

Activities and Resources for self-isolation and beyond Be curious – Explore – Discover new things – Have fun – Learn Use your self-isolation time to invest in your future. Reduce boredom and anxiety. Discover2Learn. Modern Workplace Learning

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Cynefin St David’s Day (5 of 5)

Dave Snowden

I don’t know if I displaying a keen anticipatory capability in focusing on Disorder, the all too often ignored fifth domain of Cynefin, in this annual update series; if so it was unconscious.

How To Lead Remote Employees In The Wake Of COVID-19

Dan Pontefract

As of this writing, the World Health Organization (WHO) hasn’t declared COVID-19 (aka: coronavirus) a pandemic, but the likelihood grows by the hour. Whether or not it receives such a … Continue reading "How To Lead Remote Employees In The Wake Of COVID-19".

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Shallow or Deep

Clark Quinn

I wrote about how I was frustrated with the lack of any decent learning expertise in too many vendors. And, lately I’ve been seeing more orgs making learning claims. Unrelated, of course, because it’s too soon. Still, are things improving?

Zoom needs to clean up its privacy act

Doc Searls

As quarantined millions gather virtually on conferencing platforms, the best of those, Zoom , is doing very well. Hats off. But Zoom is also—correctly— taking a lot of heat for its privacy policy , which is creepily chummy with the tracking-based advertising biz (also called adtech ).

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The Coming Era of Decision Machines

Irving Wladawsky-Berger

“Artificial intelligence (AI) is the pursuit of machines that are able to act purposefully to make decisions towards the pursuit of goals,” wrote Harvard professor David Parkes in A Responsibility to Judge Carefully in the Era of P rediction Decision Machines , an essay recently published as part of Harvard’s Digital Initiative. “Machines need to be able to predict to decide, but decision making requires much more. Decision making requires bringing together and reconciling multiple points of view. Decision making requires leadership in advocating and explaining a path forward. Decision making requires dialogue.”. In April, 2017 I attended a seminar by University of Toronto professor Avi Goldfarb on the economic value of AI. Goldfarb explained that the best way to assess the impact of a new radical technology is to look at how the technology reduces the cost of a widely used function. For example, computers are essentially powerful calculators whose cost of digital operations have dramatically decreased over the past several decades. Over the years, we’ve learned to define all kinds of tasks in terms of digital operations, e.g., financial transactions, word processing, photography. Similarly, the Internet has drastically reduced the cost of communications and of access to all kinds of information, - including text, pictures, music and videos. Viewed through this lens, the AI revolution can be viewed as reducing the cost of predictions. Prediction means anticipating what is likely to happen in the future. Over the past decade, increasingly powerful and inexpensive computers, advanced machine learning algorithms, and the explosive growth of big data have enabled us to extract insights from all that data and turn them into valuable predictions. Given the widespread role of predictions in business, government and everyday life, AI is already having a major impact on many human activities. As was previously the case with arithmetic, communications and access to information, - we will be able to use predictions in all kinds of new applications. Over time, we’ll discover that lots of tasks can be reframed as prediction problems. But, “[it’s] decisions, not predictions, that have consequences,” notes Parkes. “ If the narrative of the present is one of managers who are valued for showing judgment in decision making… then the narrative of the future will be one in which we are valued for our ability to judge and shape the decision-making capabilities of machines. What will the decision machines of the future be optimizing for, on the basis of what data, and on whose behalf? How should we develop and deploy complex AI systems whose purpose is to make decisions continuously and automatically? What values should be enshrined in our systems? The academic community is starting to pay attention to these very important and difficult questions underlying the shift, from predictions to decisions. L ast year Parkes was co-organizer of a workshop on Algorithmic and Economic Perspectives on Fairness. The workshop brought together researchers with backgrounds in algorithmic decision making, machine learning, and data science with policy makers, legal experts, economists, and business leaders. As explained in the workshop report , algorithmic systems have long been used to help us make consequential decisions. Recidivism predictions date back to the 1920s, and automated credit scoring began in the middle of the 20th century. Not surprisingly, prediction algorithms are now used in an increasing variety of domains, including job applications, criminal justice, lending and insurance, medicine and public services. This prominence of algorithmic methods has led to concerns regarding their overall fairness in the treatment of those whose behavior they’re predicting, such as whether the algorithms systematically discriminate against individuals with a common ethnicity or religion; do they properly treat each person as an individual; and who decides how algorithms are designed and deployed. These concerns have been present whenever we make important decisions. What’s new is the much, much larger scale at which we now rely on algorithms to help us make decisions. Human errors that may have once been idiosyncratic may now become systematic. Another consideration is their widespread use across domains. Prediction algorithms, such as credit scores, may now be used in contexts beyond their original purpose. Accountability is another serious issue. “Who is responsible for an algorithm’s predictions? How might one appeal against an algorithm? How does one ask an algorithm to consider additional information beyond what its designers already fixed upon?”. While fairness is viewed as subjective and difficult to measure, accuracy measurements are generally regarded as objective and unambiguous. “Nothing could be farther from the truth,” says the workshop report. “Decisions based on predictive models suffer from two kinds of errors that frequently move in opposite directions: false positives and false negatives. Further, the probability distribution over the two kinds of errors is not fixed but depends on the modeling choices of the designer. As a consequence, two different algorithms with identical false positive rates and false negative rates can make mistakes on very different sets of individuals with profound welfare consequences.”. Workshop participants were asked to identify and frame what they felt were the most pressing issues to ensure fairness in an increasingly data- and algorithmic-driven world. Let me summarize some of the key issues they came up with as well as questions to be further investigated. Decision Making and Algorithms. It’s not enough to focus on the fairness of algorithms because their output is just one of the inputs to a human decision maker. This raises a number of important questions: h ow do human decision makers interpret and integrate the output of algorithms?; when they deviate from the algorithmic recommendation, is it in a systematic way?; and which aspects of a decision process should be handled by an algorithm and which by a human to achieve fair outcomes? Assessing Outcomes. It’s very difficult to measure the impact of an algorithm on a decision because of indirect effects and feedback loops. Therefore, it’s very important to monitor and evaluate actual outcomes. Can we properly understand the reasons behind an algorithmic recommendation?; how can we design automated systems that will do appropriate exploration in order to provide robust performance in changing environments? Regulation and Monitoring. Poorly designed regulations may be harmful to the individuals they’re intended to protect as well as being costly to implement for firms. It’s thus important to specify the precise way in which compliance will be monitored. How should recommendation systems be designed to provide users with more control?; could the regulation of algorithms lead to firms abandoning algorithms in favor of less inspectable forms of decision-making? Educational and Workforce Implications. The study of fairness considerations as they relate to algorithmic systems is a fairly new area. It’s thus important to understand the effect of different kinds of training on how well people will interact with AI based decisions, as well as the management and governance structure for AI-based decisions. Are managers (or judges) who have some technical training more likely to use machine learning- based recommendations?; w hat should software engineers learn about ethical implications of their technologies?; what’s the relationship between domain and technical expertise in thinking about these issues? Algorithm Research. Algorithm design is a well-established area of research within computer science. At the same time, fairness questions are inherently complex and multifaceted and incredibly important to get right. How can we promote cross-field collaborations between researchers with domain expertise (moral philosophy, economics, sociology, legal scholarship) and those with technical expertise? Artificial Intelligence Complex Systems Data Science and Big Data Economic Issues Education and Talent Innovation Management and Leadership Political Issues Services Innovation Smart Systems Society and Culture Technology and Strategy

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More Trending

Cynefin St David’s Day 2020 (1 of n)

Dave Snowden

On St David’s Day last year, I started a five-part series of posts to update the Cynefin Framework, all illustrated by pictures of the mountains of Eryri, or Snowdonia if you want to use the Saxon which derives from Snow Dun, or snow hill.

An Open Letter To The CEOs Of High Tech And Telecom Regarding COVID-19

Dan Pontefract

To the CEOs of companies such as Apple, Amazon, Google, Microsoft, Intel, IBM, Oracle, AT&T, Verizon, TELUS, Rogers, Bell, BT and Telstra, I have a request. Gather your c-suite. Ask … Continue reading "An Open Letter To The CEOs Of High Tech And Telecom Regarding COVID-19".

Is intrinsic motivation a myth?

Clark Quinn

I was asked to comment on intrinsic motivation, and was pointed to an article claiming that it’s a myth(!). Given that I’m a staunch advocate of intrinsic motivation, I felt this was something that I should comprehend. Is intrinsic motivation a myth?

working smarter with PKM

Harold Jarche

Working Smarter with Personal Knowledge Mastery is a field guide for the networked knowledge worker. It is meant to complement the PKM Workshops and help practitioners.

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The Current State of Open Innovation

Irving Wladawsky-Berger

In January, UC Berkeley professor Henry Chesbrough published Open Innovation Results : Going Beyond the Hype and Getting Down to Business, his fourth book on innovation in the last two decades.

More on Zoom and privacy

Doc Searls

Zoom needs to clean up its privacy act , which I posted yesterday, hit a nerve. While this blog normally gets about 50 reads a day, by the end of yesterday it got 15000. So far this morning (11:15am Pacific), it has close to 8000 new reads.

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Consulting in the Time of Corona (virus)

Dave Snowden

In the past 2 weeks, I have been called into a few urgent conference calls with partners and clients. As a response to the Corona virus, and it’s spread, many of them (and ourselves) included have had their projects impacted. .

Announcing My Free (or chip in!) Basics On Working From Home Toolkit

Dan Pontefract

You may recall that I launched a REMOTE LEADERSHIP TOOLKIT on March 16. There have been over 3,000 downloads thus far. Glad I could help somehow in this the age … Continue reading "Announcing My Free (or chip in!) Basics On Working From Home Toolkit". The post Announcing My Free (or chip in!)

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Interesting times

Clark Quinn

It was when I was living in Australia that I first heard the apocryphal Chinese curse “may you live in interesting times.” ” And, I have to say, the going’s gotten weird. A few reflections on the situation, all of course related to COVID-19.

the future is here

Harold Jarche

Work is learning, and learning is the work. This has been my tag line for the past decade.

The Long-Term Future of Work and Education: Three Potential Scenarios

Irving Wladawsky-Berger

“Experts differ widely in their predictions about how technological innovation will change the labor market, but they all see a need for changes in education,” write British professors Ewart Keep and Phillip Brown in a recently published article, Rethinking the Race Between Education and Technology. While experts don’t generally agree on much, they’re pretty much of one mind when it comes to the growing importance of skills and education in our 21st century digital economy. Every past technological transformation ultimately led to more jobs, higher living standards and economic growth. But, as a number of recent studies concluded, to ensure that this will indeed be the case, our emerging knowledge economy should be accompanied by the expansion of educational opportunities for everyone. While noting that this is the most likely scenario for the next 10 - 15 years, Keep and Brown also consider two potential longer-term scenarios. Perhaps AI will lead to even more pervasive and fundamental transformations in the nature of work, making it difficult for even those with a college or higher education to find a good job. Beyond that , some have suggested that in the more distant future we might see an even more radical, science-fiction-like transformation: the end of work as we’ve long known it. The authors argue that considering such a spectrum of possibilities will help us better prepare for what’s essentially an unpredictable future. In that spirit, their paper discusses three different labor market scenarios: labor scarcity, job scarcity, and the end of work. Labor scarcity. “Supporters of this scenario expect that as in the past, new positions and professions will emerge and create new jobs to replace any eliminated by new technology. Although there may be a challenging period of transition, especially for those displaced by automation, technological innovation will require new skills and create employment opportunities.”. Investments in the skills required to meet these technology and workforce challenges are the key source of individual opportunity, social mobility, and economic welfare. This is especially important for workers without a four-year college degree who’ve disproportionately borne the brunt of automation. Post-secondary education and training venues, - e.g., community colleges, apprenticeships, online education, industry-specific training programs, - are likely to be most relevant and accessible to these workers. However, existing education and training programs won’t be enough given the demands for life-long adult learning. “What makes these arguments consistent is the idea of a race between technology and education to develop more advanced skills if people are to remain employable in tomorrow’s labor market. The fundamental challenge remains the reform of education systems to prepare the future workforce to take advantage of new opportunities emerging within a technologically advanced economy… People will need to adapt continuously and learn new skills and approaches within a variety of contexts.”. In addition, new skills will be required to keep up with the increased digitalization of the economy. The article references the Essential Digital Skills Framework , a tool developed by the UK Government that defines the skills needed to benefit from, participate in, and contribute to the digital world. The framework includes five categories of skills: communicating, collaborating and sharing online; handling information and content securely; buying, selling and managing transactions; finding solutions to problems using digital tools; and being safe and legal online. Job Scarcity. Automation fears have understandably accelerated in recent years, as our increasingly smart machines are now being applied to activities requiring intelligence and cognitive capabilities that not long ago were viewed as the exclusive domain of humans. P revious technological innovation always delivered more long-run employment, but things can change. As a 2014 Economist article noted, while the majority of economists wave such worries away, some now fear that a new era of automation enabled by ever more powerful and capable computers could work out differently. “The job scarcity view recognizes that new technologies may enhance the skills of a relatively small proportion of the workforce, but the general direction of technological innovation is toward the redesign of existing jobs, where much of the knowledge content is captured in software that permits a high level of standardization and potential to deskill or automate a wide range of occupations, including technical, professional, and managerial roles.”. This scenario reminds me of Software is Eating the World , a 2011 essay by Marc Andreessen which predicted that software was poised to take over large swathes of the economy. Entrepreneurial companies all over the world are disrupting established industries with innovative AI-driven software solutions. An increasing number of businesses and industries are being run on software and delivered as online services. “Job scarcity points to a significant mismatch between an expanding supply of educated and skilled workers and a scarcity of high-quality job opportunities, primarily resulting from the routinization and segmentation of job roles rather than technological unemployment.” A relatively small number of highly skilled, educated professionals and managers will develop the necessary algorithms, digital systems and business models, while a much larger number of less skilled workers will be needed to implement the procedures and managerial tasks which have been captured in algorithms and software. The End of Work. In a 1930 essay , English economist John Maynard Keynes wrote about the onset of “a new disease” which he named technological unemployment , that is, “unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” Keynes predicted that the standard of living in advanced economies would be so much higher by 2030 that “for the first time since his creation man will be faced with his real, his permanent problem - how to use his freedom from pressing economic cares, how to occupy the leisure,” and most people would be working a 15-hour week or so, which would satisfy their need to work in order to feel useful and contended. Such an end-of-work scenario assumes that decades from now, most economic activity will be handled by super-smart machines developed and supervised by small groups of highly skilled professional and technical workers. “It would represent a profound dislocation for the education and training system… where for the past three decades or more the focus has been on the role of education in equipping individuals to perform effectively in a changing labor market.” Instead, the aim of education “would be to help people gain the skills to live fulfilling lives, with the judgment and knowledge to be capable of addressing the complex problems that humanity will face.”. “All three theories acknowledge rapid technological change, even if there is disagreement about its impact on labor demand and job quality,” write the authors in conclusion. “They all acknowledge the need for digital skills and an even greater focus on social skills. These skills are seen to be more important because people will need to be flexible and adaptable within rapidly changing labor markets and work contexts. Moreover, although the technical and knowledge requirements of what people do for a living may change, the social context in which people interact, network, and produce will remain, and social skills are more difficult for smart machines to develop.” Finally, “ all three theories see a need for educational reform and a greater focus on lifelong learning.”. Artificial Intelligence Complex Systems Economic Issues Education and Talent Future of Work Management and Leadership Political Issues Services Innovation Smart Systems Society and Culture Technology and Strategy

Zoom’s new privacy policy

Doc Searls

Yesterday (March 29), Zoom put up a major rewrite to its privacy policy. The new language is far more clear than what it replaced, and which had caused the concerns I detailed in my previous three posts: Zoom needs to clean up its privacy act , More on Zoom and privacy , and. Helping Zoom.

Cynefin St David’s Day (4 of 5)

Dave Snowden

In this penultimate post in the current series, I want to look at what you can manage in the complex domain of Cynefin and return to the which domain is X in debate.

Since 2008 I’ve Worked From Home. Here Are 5 Helpful Tips.

Dan Pontefract

I spent ten years at TELUS as a team member, leader and executive. I was a mobile worker the entire time. I worked from the road, a TELUS office, hotels, the … Continue reading "Since 2008 I’ve Worked From Home. Here Are 5 Helpful Tips.". The post Since 2008 I’ve Worked From Home.

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Modern Workplace Learning 2020 now available as a paperback

Jane Hart

Modern Workplace Learning 2020 is now ALSO available as a paperback (as an alternative to the online/PDF version). 10% discount until the end of March. Modern Workplace Learning

observation > narration > curation

Harold Jarche

“In a crisis, you should always deploy an innovation team alongside the business recovery teams … to capture the novel practices … put naive observers in alongside the incident team to capture the key learning points” — Dave Snowden. Are you responsible for learning in your organization?

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The Evolution of the Social Contract in the 21st Century

Irving Wladawsky-Berger

“Life has changed substantially for individuals in advanced economies in the first two decades of the 21st century,” notes The social contract in the 21st century , a new report by the McKinsey Global Institute (MGI). “In many ways, changes for individuals have been for the better, including new opportunities and overall economic growth… Yet, the relatively positive perspective on the state of the economy, based on GDP and job growth indicators, needs to be complemented with a fuller assessment of the economic outcomes for individuals as workers, consumers, and savers.”. The report takes an in-depth look at the changing economic outcomes for individuals between 2000 and 2018 in 22 advanced countries, - 16 European ones, Japan and South Korea, Australia and New Zealand, and Canada and the US. In aggregate, these countries constitute 57% of global GDP. . The report closely examines the evolution of the social contract , that is, “the arrangements and expectations, often implicit, that govern the exchanges between individuals and institutions.” Its overriding finding is that the social contract has changed considerably in the 21st century, with individuals having to assume greater responsibility for their economic outcomes. Opportunities for work and employment rates have risen significantly, but outcomes vary considerably across socioeconomic groups and geographies. While many have benefited from this evolution, those in the bottom 60% of the income distribution are facing significant economic challenges, leading to an uncertain future and a general loss of trust in institutions. The report analyzes the evolution of the social contract by looking at the changing outcomes for individuals as workers, as consumers, and as savers. Let me summarize the findings in each of these three categories. Employment has risen amid growing labor market polarization and wage stagnation. Employment has risen to record levels in the 22 countries studied. The employment rate for working age populations (15-64 years) rose from 68% in 2000 to 71% in 2018, with the number of working-age people increasing by 45 million, - 31 million women and 14 million men. The rising employment rate has been primarily driven by the rise in part-time employment, - including alternative forms of work, i.e, the so-called gig economy. Part-time employment increased by 4.1% between 2000 and 2018, while full-time employment fell by 1.4%, - a net employment increase of 2.7%. However, even though the employment rate has been at record levels in the US, the working-age employment rate fell from 74% in 2000 to 71% in 2018 due to the rising share of discouraged workers. In the US, p art-time employment increased by 3.4% while full-time employment declined by 6.8%. The increased digitalization of their economies has been a major factor in the polarization of employment and wage distributions over the past two decades. Across the 22 countries, j ob opportunities have expanded for both high- and low-skill occupations while contracting for middle-skill jobs. Between 2000 and 2018, 7 million middle-skill jobs were lost in the US and the 16 European countries for which data are available. Wage stagnation has been a serious challenge for many workers. Between 2000 and 2018, average yearly wage growth was just 0.7% in all the 22 countries. Over the same time period, the share of total income of the bottom 40% of workers decreased by 1.2%, was approximately flat for the middle 40%, and went up by 1.2% for the top 20% of workers in the US and the 16 European countries for which data are available. In the US, the median wage for high skill workers grew by 7.3%, by 1.1% for mid skill workers, and by 5.3% for low skill workers. In addition, recent studies have found a growing economic polarization across a country’s geographic regions. Urban areas are seeing faster employment and wage growth while smaller towns and rural areas are falling behind. In the US, net job growth through 2030 will be concentrated in urban areas, while much of the rest of the country may see little employment growth or even lose jobs. Discretionary goods and services are cheaper, but the cost of housing and other basics has risen. Costs have fallen for most discretionary goods and services, such as clothing, communications, recreation and furnishings, which account for roughly 25% of consumer spending in advanced economies. In addition, the Internet, smartphones and other technologies have given rise to new discretionary consumption, some of which is available to consumers as free services, e.g., access to information, e-mail and social media. However, the costs of housing, healthcare and education have risen faster than general prices, absorbing much of the income gains for many mid- and low-wage workers. Average housing costs have increased by almost 40% in the US and European countries between 2002 and 2018. Since housing accounts for roughly 25% of consumption, rising housing costs have led to a decline in the purchasing power of many workers. Healthcare represents 4% of spending in European countries and in Japan. In the US healthcare accounts for 9% of spending, and, at 17%, it’s the second most significant driver of consumer prices. H ealthcare has significantly improved over the past two decades: life expectancy at 65 increased from 18 to 20 years, mortality from cancer decreased by an average of 15%, and diabetes mortality declined by 20%. “Technology promises to drive further improvements, with innovations such as predictive diagnosis algorithms, health monitor implants, and synthetic biology.”. Education costs went up in all countries except Japan, especially in the US and the UK. Education accounts for 3% of spending in the US, 2% in Japan and 1% in European countries. Access to education has also improved. In particular, tertiary attainment rates, - including trade schools, college and universities, - increased from 28% to 42% of the 25- to 64-year-old population. In addition, online courses are democratizing access to education and skills. Individual and institutional savings have declined at a time of increasing longevity and aging populations. Since people are living longer, the expected number of years spent in retirement has increased from 16 in 1980 to 20 in 2018. But, guaranteed pension levels have declined by an average of 11% since 2000, as governments and private-sector institutions have shifted a larger responsibility to individuals for their own retirement savings. Many pension systems have changed from defined?benefit plans , for which institutions guarantee a minimum return and thus bear the market risk, to defined?contribution plans , for which individuals bear the market risk. “Yet household saving rates fell in 11 of the 22 countries; in 2017, more than half of individuals did not save for old age.” The net pension replacement rate, - which measures how effectively a pension system provides a retirement income to replace pre-retirement earnings, - has decreased by 11% for the average person across the 22 countries in the study. While much has improved for individuals in the first two decades of the 21st century, many challenges remain. To help achieve better and more inclusive outcomes in the decades ahead, concerted action is needed on two fronts: “first to make sure that the gains of the 21st century so far are sustained and scaled, and the potential for even more opportunities and economic prosperity is fully realized. Second, to make sure that the outcomes for individuals in the next 20 or more years of the 21st century are better and more inclusive than in the first 20 and increase broad prosperity.”. Economic Issues Healthcare Systems Management and Leadership Political Issues Society and Culture

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How I work

Clark Quinn

So, I work from home. A lot. And lots of folks are providing advice for those who have to make the shift in these interesting times. Rather than talk about what you should do, however, I thought I’d share what I do. So this is how I work. This is my workspace. That’s a convertible desk, so I can be standing or sitting. That varies depending on what I’m working on, how I feel, etc. I’ve an ergonomic chair for sitting, and a foam pad I slide out when I’m standing.

Aporetic Meditations

Dave Snowden

These have been trying times. Yesterday, I watched our National Development Minister tear up at a national address as he thanked frontline workers who are doing their part against COVID-19. Singapore released its second stimulus package yesterday, drawing a landmark $48bn from its reserves.

Announcing Speak Aid 2020

Dan Pontefract

In this time of uncertainty, angst and working from home, patterns have changed and new norms are quickly being crafted. One of the norms to have seemingly vanished overnight was … Continue reading "Announcing Speak Aid 2020". The post Announcing Speak Aid 2020 appeared first on Dan Pontefract.

An analysis of the value of the ways of learning at work: PART TWO

Jane Hart

In PART TWO of my analysis I take a look at each of the 12 ways of learning and compare the results of each of the different profiles (discussed in Part One) against the overall profile, and discuss some further implications for modern workplace learning.

learning from the external world

Harold Jarche

What are the most valued ways of learning work? Jane Hart has been asking this question since 2010. Over 7,500 people have responded to date.

Remembering Freddy Herrick

Doc Searls

The picture of Freddy Herrick I carry everywhere is in my wallet, on the back of my membership card for a retail store. It got there after I loaned my extra card to Freddy so he could use it every once in awhile.

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Coronavirus: Effective strategies and tools for remote work during a pandemic

Dion Hinchcliffe

Whether or not coronavirus becomes a full outbreak, the trend of working from afar is currently experiencing a major boost as businesses shift to digital channels and more people avoid physical gatherings. Here are key approaches and tools to get the most from remote work

Cynefin St David’s Day 2020 (2 of n)

Dave Snowden

In my first post in this series, I talked about the renaming of the disorder domain into A/C (for short) standing for Aporetic or Confused for what used to be called authentic or inauthentic disorder.

Announcing My Free (or by donation) Remote Leadership Toolkit

Dan Pontefract

Since 2002 I’ve led teams and people located across the globe. Since 2008 I’ve been a mobile worker, which means I work half the time from the comforts of my … Continue reading "Announcing My Free (or by donation) Remote Leadership Toolkit".

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My 25 Years of Ed Tech

Stephen Downes: Half an Hour

Martin Weller has released his book 25 Years of Ed Tech today. It's a nice read; you are encouraged to check it out. But I have to confess, on having looked at the table of contents, I thought that it captured my career pretty well. Of course, that was not Weller's objective.

new societal infrastructures

Harold Jarche

In 2004 Bill Draves and Julie Coates wrote Nineshift : Work, life and education in the 21st Centur y. That was the same year I started blogging here.

We haven’t seen this movie before

Doc Searls

Three weekends ago, we drove from New York to Baltimore to visit with family. We had planned this for awhile, but there was added urgency: knowing the world was about to change in a big way. Or in many big ways. The hints were clear, from China and elsewhere: major steps would need to be taken—by people, businesses and governments—to slow the spread of a new virus against which there was yet no defense other than, mainly, hiding out.

Interactive Coptic-English translation of (the gospel of) Thomas

Martijn Linssen

The goals behind this translation are twofold: this is the most pure translation that can exist, and it is fully traceable: each and every word is accounted for and can be verified with one single click by everyone, as long as there is access to the Internet: that is where the full and complete online Coptic Dictionary of KELLIA is at. If no access, click on any word and quickly verify it against the index where an excerpt of the thesaurus is presented This translation will let you breathe the atmosphere of over two thousand years ago. Anyone can verify every word of this translation, anyone can deep-dive into the original Coptic text of Thomas. And the translation is fully normalised: every Coptic word has its own English word, and vice versa. Doubts about a translated word? Click on the English translation and quickly verify it against the index where an excerpt of the thesaurus is presented. Still not satisfied? Click again on the Coptic word itself that leads you to the full dictionary; compare it to similar words, their shared root(s) and origin(s), and make up your mind The translation is available on Amazon in most countries: try Amazon UK , Amazon NL or Amazon US , for instance. Don't have 3 bucks or euros to spend? Pity, the Kindle has a fine search function although the orange underlines are hideous, unfortunately inherent to the Print Replica format. But you can try your luck at academia.edu where my other publications are: the translation is here and can be read online, or you can register and dowload it Enjoy. And may your house be forever destroyed

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