Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

18 October 2017

Stay Curious

Clark @ 8:09 AM

One of my ongoing recommendations to people grew out of a toss-off line, playing off an advertisement. Someone asked about a strategy for continuing to learn (if memory serves), and I quipped “stay curious, my friends”.  However, as I ponder it, I think more and more that such an approach is key.

I was thinking of this trend the the other day as “intellectual restlessness”. What I’m talking about is being intrigued by things you don’t understand that have persisted or recently crossed your awareness, and pursuing it. It’s not just saying, how interesting, but recognizing connections, and pondering how it could change what you do. Even to the point of actually changing!

It also would include pointing interesting things to other people who would benefit.  This doesn’t always have to happen, but in the spirit of cooperation (in the Jarche sense), we could and should contribute, curate, when we can.  And, ideally, leaving trails of your explorations that others can benefit from. Writings, diagrams, videos, what have you, helps yourself as well as others.

Old Infoworld magazinesI was reminiscing that more than 30 years ago, on top of my job designing educational computer games, I was already curious. I still have copies of the magazines containing reviews I did (one hardware, one software), as well as a journal article based upon undergraduate research I was fortunate to participate in.

And that persistence in curiosity has led to a trail of artefacts. You may have come across the books, book chapters, articles, presentations, etc. And, of course, this blog for the past decade and more. (May it continue!) However, I’m not here to tout my wares, but instead to point to the benefit of being curious.

As things change faster, a continuing interest is what provides an ongoing ability to adapt. All the news about the ongoing changes in jobs and work isn’t likely to lessen.  Staying curious benefits you, your colleagues and friends, and I reckon society in general.  You want to look at many sources of information, track tangential fields, and be open to new ideas.

This isn’t just your choice, of course, ideally your organization is supportive. These lateral inputs are a component of innovation, as is time to allow for serendipity and incubation. Orgs that want to be able to be agile will need this capabilities as well. I suppose organizations need to stay curious as well!

 

11 October 2017

Radical Coherency

Clark @ 8:07 AM

Tied to my last post about insufficient approaches, I was thinking again about the Coherent Organization . Coherency is powerful, but it could be a limiting metaphor.  So I want to explore it a bit further.

First, coherency is powerful.  Lasers, for example, are just light, the same as comes from your lightbulbs. Except that the wavelengths are aligned and focused. When they’re at the same frequency, in the same direction, suddenly you can cut steel!

However, an easy interpretation is that you get this right, and it’s then sufficient. But that’s no longer sufficient in organizations. As things change, you need coherency and agility. How do you get both?

I’m suggesting that coherency has to be on many dimensions.  So you have coherency with the organization’s purpose, but people are coherent with each other, and with the customers, and with best principles.  And that latter is important, as best practices won’t transfer unless they’re abstracted and recontextualized.

So what I’m arguing for is a more radical coherency, a coherency that’s in synchrony in an ecosystem perspective. Where people are communicating and collaborating in ways that apply best principles in an way that integrates them into an aligned whole that’s greater than the sum of the parts.

This is a learning organization, but one that’s integrating many disparate elements. That, I think, is a desirable and achievable goal, but it’s more than one program. It’s a campaign that needs an initial focus, and a plan to successfully integrate it into practice first, and then to scale it to both shift practice and culture. It’s non-trivial, but I think it’s more than worthwhile: it’s necessary. What do you think?

10 October 2017

Simple Insufficiency

Clark @ 8:01 AM

As things get more complex, organizations are looking to get more agile. And they’re looking at a wide variety of approaches in different areas. It can be agile, digital transformation, design thinking, and more. And, by and large, these are all good things. And all of them are quite simply insufficient. Why do I suggest this insufficiency? Because the solution is complex.

Organizations are complex organisms. If you try to address them with simple solutions, you will perturb them, but the results will not be as expected. Whether you believe the 70% failure rate of org change initiatives, the fact is that many or most organizational change initiatives don’t achieve the desired outcomes. As we explore this more, we understand that it requires a ‘ground war, not an air war’ as Sutton & Rao put it in Scaling Up Excellence. And I’ll posit that there’s more.

This isn’t unknown; regardless of label, the folks who are responsible for such initiatives typically argue that that it’s a process. Yet orgs still look for the simple packaged program that will turn things around. And while it’s understandable, it’s decreasingly likely to work. It takes a system approach.

And what I haven’t seen, and I’m willing to hear of one, is a comprehensive program that addresses the full suite of skills and culture together that constitute a coherent organization. And that’s a non-trivial compendium of elements. There are the cultural elements, and skills, and tools, and more. PKM, WoL (SyW), 70:20:10, teaming, collaborating and communicating, etc, are all elements, but they need to be tied together.

My point, I guess, is that there needs to be an entry point, but also a plan to develop the full suite of skills and move the culture. And, like most meta-learning, it needs to be done around something. So you need a concrete focus to start, some problem you’re working on that you’ll do in the new way, and practice the processes and develop the competencies and culture as you go. For the org, it should be a necessary new extension to the organization’s competencies. For L&D, it should be first applied for some L&D project.

In both cases it needs a plan and support for acquisition. And include a realistic time frame for starting, and then spreading. It’s not simple, but it’s necessary. Anything else, I fear, is truly insufficient.

29 September 2017

Mundanities

Clark @ 8:02 AM

This post is late, as my life has been a little less reflective, and a little more filled with some mundane issues.  There’re some changes here around the Quinnstitute, and they take bandwidth.  For a small update on these mundanities with some lessons:

standing deskFirst, I moved office from the side of the house back to the front. My son had occupied it, but he’s settled into an apartment for college, and I prefer the view out to the street (to keep an eye on the neighborhood). Of course, this entailed some changes:

My ergonomic chair stopped working, and it took several days to a) find out someone who’d repair it, b) get it there, wait for it to get fixed, and get it back.  It’s worth it (a lot less than replacing) and ergonomics is important.

Speaking of which, I also now could get a standup desk, or in my case one of those convertible desks that lets you raise and lower your workspace. I’ve been wanting one since the research has come out on the problems with sitting.  We’d previously constructed a custom desktop (with legs from Ikea!), for the odd shaped room, so it was desirable to just put it on top. So far, so good. Strongly recommended.

Also bought a used bookshelf (rather than move the one from the old office).  Real wood, real heavy.  Used those ‘forearm forklift’ straps to get it in. They work!  And, this being earthquake country, had to strap it to the wall. Still to come: filling with books.

At the same time, fed up with all the companies that provide internet and cable television, we decided to change. (We changed mobile providers back in January.)  As I noted previously, companies use policies to their advantage. One of the approaches is that they sell you a two year package, but then there’s no notification that the time’s up and the rate jumps up. And you can’t find just a low rate provider (I don’t even mind if it’s higher than the bonus deal). Everyone uses this practice. Sigh.

As I said, I can’t find anyone better, but just decided to change. That involved conversations, and research, and installation time, and turning off the old systems.  At least we’re getting a) a lower rate, b) nicer DVR, and c) faster internet.  For the time being. While the new provider promised to ping me before the plan runs out, the old provider says they can’t. See what I mean?  Regardless, I’ve got a trigger before it expires to sign up anew. Or change again.  That’s the lesson on this one.

And of course there are some conversations about some upcoming presentations. I was away last week presenting, and have one coming up next month (ATD China Summit, if you’re near Shanghai say hello) and several in November at AECT in Jacksonville.  You’ve seen some of the AI reflections, more likely to come on the new topics.

And there’s been some background work. Reading a couple of books, and working on two projects. Stay tuned for a couple of new things early next year.

The lesson, of course, is trying to find time to reflect while you’re executing on mundanities is more challenging, but still a valuable investment.  I fight to make time, I hope you do too!

26 September 2017

Organizational terms

Clark @ 8:09 AM

Listening to a talk last week led me to ponder the different terms for what it is I lobby for.  The goal is to make organizations accomplish their goals, and to continue to be able to do so.  In the course of my inquiry, I explored and uncovered several different ‘organizational’ terms.  I thought I should lay them out here for my (and your) thoughts.

For one, it seemed to be about organizational effectiveness. That is, the goal is to make organizations not just efficient, but capable of optimal levels of performance.  When you look at the Wikipedia definition, you find that they’re about “achieving the outcomes the organization intends to produce”.  They do this through alignment, increasing tradeoffs, and facilitating capacity building.  The definition also discusses improvements in decision making, learning, group work, and tapping into the strictures of self-organizing and adaptive systems, all of which sound right.

Interesting, most of the discussion seems to focus on not-for-profit organizations. While I agree on their importance, and have done considerable work with such organizations, I guess I’d like to see a broader focus. Also, and this is purely my subjective opinion, the newer thoughts seem grafted on, and the core still seems to be about producing good numbers. Any time you use the phrase ‘human capital’, I am leery.

Organizational engineering is a phrase that popped to mind (similar to learning engineering). Here, Wikipedia defines it as an offshoot of org development, with a focus on information processing. And, coming from cognitive psychology, that sounds good, with a caveat.  The reality is, we’re flawed as ideal thinkers. And in the definition it also talks about ‘styles’, which are a problem all on their own. Overall, this appears to be more a proprietary suite of approaches under a label. While it uses nice sounding terms, the reality (again, my inferences here) is that it may be designed for an audience that doesn’t exist.

The final candidate is organizational development. Here the definition touts “implementing effective change”. The field is defined as interdisciplinary and drawing on psych, sociology, and more.  In addition to systems thinking and and decision-making, there’s an emphasis on organizational learning and on coaching, so it appears more human-focused. The core values also talk about human beings being valued for themselves, not as resources, and looking at the complex picture.  Overall this approach resonates with me more, not just philosophically, but pragmatically.

As I look at what’s emerging from the scientific study of people and organizations, as summed up in a variety of books I’ve touted here, there are some very clear  lessons. For, one, people respond when you treat the as meaningful parts of a worthwhile endeavor. When you value people’s input and trust them to apply their talents to the goals, things get done. Caring enough to develop them in ways that are supportive, not punitive, and not just your goals but theirs’ too, retains their interest and commitment. And when you provide them with an environment to succeed and improve, you get the best organizational outcomes.

There’s more about how to get started.  Small steps, such as working in a small group (*cough* L&D? *cough* ;), and developing the practices and the infrastructure, then spreading, has been shown to be better than a top-down initiative. Experimenting and reviewing the outcomes, and continually tweaking likewise.  Ensuring that it’s coaching, not ‘managing’ (managers are the primary reason people leave companies).  Etc.

All this shouldn’t be a surprise, but it’s not trivial to do but takes persistence. And, it flies in the face of much of management and HR practices.  I don’t really care what we label it, I just want to find a way to talk about things that makes it easy for people to know what I’m talking about.  There are goals to achieve, so my main question is how do we get there?  Anyone want to get started?

20 September 2017

Transparency

Clark @ 8:09 AM

I believe that transparency is a good thing. It builds trust, as it makes it hard to hide things.  And trust is important. So, in the spirit of transparency, it occurred to me to share a little bit about me and this blog. Here I lay out who I am, why I write it, and what I write about.

You can find out more via the ‘about Clark Quinn’ link in the right column, but in brief, I saw the connection between computing and learning as an undergraduate, and it’s been my career ever since. It’s not just my vocation, but it’s my avocation: I enjoy exploring cognition and technology. And while I’ve done the science and track it, what I revel in (and have demonstrable capability for), is applying cognitive and learning science to create new approaches and fine-tune existing ones.  Learning engineering, if you will.

And, for a variety of reasons, I do this as a consultant. I make my living providing strategic guidance for clients.  I speak at events, and write books, but my main income is from consulting. Which means you should hire me.  I assist organizations to improve their processes and products, both tactically and strategically. My clients have been happy, and find it’s good value. What you get are unique ideas that are practical and yet effective. Ideas you aren’t likely to have come up with, but are valuable. I really do Quinnovate! Check out the Quinnovation site for more.  Of course, I do have to live in the real world, and so I need to find ways to do this that are mutually beneficial.

Yet generating business isn’t why I write this blog.  I started writing this blog as an experiment and originally tried to write 5 days a week (but was happy if that ended up being 2-3 times a week).  My commitment now is 2 per week (which rarely yields 1 or 3).  And I haven’t monetized it: there’s no advertising, and while I occasionally talk about where I’m speaking or the like, I haven’t used this as a way to sell things. Hopefully that can continue.

So, the reason I write is to think ‘out loud’.  It’s largely for me: it makes me think. I’m just always curious! I’ve previously recounted the story about how I was on a panel answering questions from the audience, and one of my fellow panelists commented that I had an answer for everything. And the reason is in the ongoing attempt to populate the blog, I’ve looked at lots of things. As my client engagements have been in many different areas, I also have wide-ranging experience to draw upon.  And I just naturally reflect, but getting concrete: diagramming and/or writing, provides additional benefits.

Thus, the process of continually writing (for over 10 years now) means I’m looking at lots of things, reflecting on them, and sharing my thoughts. I also make a point to look at related fields, and look for connections. I also look at what’s happening with technology. In general, I look with a critical eye, as I was trained as a scientist.  I think that’s valuable as well, because there still is a lot of nonsense trotted out, and there’s always some new buzzword that’s being loosely tossed about. Blogging’s given me cause to continue to tune my thinking, and at least some folks have commented that they’ve found it useful.

Mostly I write about things related to technology, learning, and individual and organizational implications. It includes diversions to innovation, design, wisdom, performance support, and the like, because they’ve implications for practice. In many ways I see approaches that aren’t well aligned with how we think, work, and learn, and that strikes me as both a shame, and an opportunity to improve. And that’s what I enjoy, finding ways to improve what we do.

So that’s it: I blog to facilitate my understanding, because cognitive science and technology is my passion. It isn’t a direct business move.  I do need to make a living, and prefer to do it in the area of my passion, and fortunately have been successful so far.  (Which isn’t to say you shouldn’t find a reason to use me, there are never enough opportunities to assist in improvement, and I’m not a sales person ;).  And yes, this life is a learning experience all in itself!  I hope this is clear, but in the interests of transparency I welcome your inquiries and comments. Stay curious, my friends.

 

15 September 2017

AI Reflections

Clark @ 8:07 AM

Last night I attended a session on “Our Relationship with AI” sponsored by the Computer History Museum and the Partnership on AI. In a panel format, noted journalist John Markoff moderated Apple’s Tom Gruber, AAAI President Subbarao Kambhampati, and IBM Distinguished Research Scientist Francesca Rossi. The overarching theme was: how are technologists, engineers, and organizations designing AI tools that enable people and devices to understand and work with each other?

It was an interesting session, with the conversation ranging from what AI is, to what it could and should be used for, and how to develop it in appropriate ways. Addresses were concerns about AI’s capability, roles, and potential misuses.  Here I’m presenting just a couple of thoughts triggered, as I’ve previously riffed on IA (Intelligence Augmentation) and Ethics.

One of the questions that arose was whether AI is engineering or science. The answer, of course, is both. There’s ongoing research on how to get AI to do meaningful things, which is the science part. Here we might see AI that can learn to play video games.  Applying what’s currently known to solve problems is the engineering part, like making chatbots that can answer customer service questions.

On a related note was what can AI do.  Put very simply, the proposal was that AI could do what you can make a judgment on in a second. So, whether what you see is a face, or whether a claim is likely to be fraudulent.  If you can provide a good (large) training set that says ‘here’s the input, and this is what the output should be’, you can train a system to do it.  Or, in a well-defined domain, you can say ‘here are the logical rules for how to proceed’, and build that system.

The ability to do these tasks, was another point, is what leads to fear. “Wow, they can be better than me at this task, how soon will they be better than me on many tasks?”  The important point made is that these systems can’t generalize beyond their data or rules.  They can’t say: ‘oh I played this video driving game so now I can drive a car’.

Which means that the goal of artificial general intelligence, that is, a system that can learn and reason about the real world, is still an unknown distance away.  It would either have to have a full set of  knowledge about the world, or you’d have to have both the capacity and the experience that a human learns from (starting as a baby).  Neither approach has demonstrated any approach of being close.

A side issue was that of the datasets.  It turns out that datasets can have or learn implicit biases. A case study was mentioned how Asian faces triggered ‘blinking’ warnings, owing to the typical eye shape. And this was from an Asian company!  Similarly, word recognition ended up biasing woman towards associations with kitchens and homes, compared to men.  This raises a big issue when it comes to making decisions: could loan-offerings, fraud-detection, or other applications of machine learning inherit bias from datasets?  And if so, how do we address it?

Similarly, one issue was that of trust. When do we trust an AI algorithm?  One suggestions was that it would come through experience (repeatedly seeing benevolent decisions or support).  Which wouldn’t be that unusual. We might also employ techniques that work with humans: authority of the providers, credentials, testimonials, etc. One of my concerns then was could that be misleading: we trust one algorithm, and then transfer that trust (inappropriately) to another?  That wouldn’t be  unknown in human behavior either.  Do we need a whole new set of behaviors around NPCs? (Non Player Characters, a reference to game agents that are programmed, not people.)

One analogy that was raised was to the industrial age. We started replacing people with machines. Did that mean a whole bunch of people were suddenly out of work?  Or did that mean new jobs emerged to be filled?  Or, since we’re now doing human-type tasks, will there be less tasks overall? And if so, what do we do about it?  It clearly should be a conscious decision.

It’s clear that there are business benefits to AI. The real question, and this isn’t unique to AI but happens with all technologies, is how we decide to incorporate the opportunities into our systems. So, what do you think are the issues?

 

7 September 2017

Developing L&D

Clark @ 8:05 AM

One of the conversations I’ve been having is how to shift organizations into modern workplace learning. These discussions have not been with L&D, but instead targeted directly at organizational strategy. The idea is to address a particular tactical goal as part of a strategic plan, and to do so in ways that both embody and develop learning and a collaboration culture. The topic was then raised about how you’d approach an L&D unit under this picture. And I wondered whether you’d use the same approach to developing L&D as part of L&D operations. The answer isn’t obvious.

So what I’m talking about here would be to take an L&D initiative, and do it in this new way, with coaching and scaffolding. The overall model involves a series of challenges with support.  You’re developing some new organizational capability, and you’d scaffold the process initially with some made up or pre-existing challenges.  Then you gradually move to real challenges. So, does this model change for L&D?

My thought was that you’d take an L&D initiative, and something out of the ordinary, an experiment.  Depending on the particular organization’s context, it might be performance support, or social media, or mobile, or…  Then you define an experiment, and start working on it. To develop the skills to execute, you give a team (or teams) some initial challenges: e.g. critique a design. Then more complex ones, so: design a solution to a problem someone else has solved. Finally, you give them the real task, and let them go (with support).

This isn’t slow; it’s done in sprints, and still fits in between other work. It can be done in a matter of weeks.  In doing so, you’re having the team collaborate with digital tools (even if/while working F2F, but ideally you have a distributed team). Ultimately, you are developing both their skills on the process itself and on working together in collaborative ways.

In talking this through, I think this makes sense for L&D as well, as long as it’s a new capability that’s being developed.  This is an approach that can rapidly develop new tactical skills and change to a culture oriented towards innovation: experimentation and iterative moves. This is the future, and yet it’s unlike most of the way L&D operates now.

Most importantly, I think, is that this opportunity is on the table now for a brief period. L&D can internally develop their understanding and ability of the new ways of working as a step towards being an organization-wide champion. The same approach taken within L&D then can be taken and used elsewhere. But it takes experience with this approach before you can scale it.  Are you ready to make the shift?

5 September 2017

Metaphors for L&D

Clark @ 8:02 AM

What do you see the role of L&D being in the organization?  Metaphors are important, as they form a basis for inferences of what fits. We frame our conversations by the metaphors we use, and these frames guide what’s allowed conversation and what’s not.  To put it another way, metaphors are the basis for mental models that explain and predict what happens.  But metaphors and models simplify things, making certain things ‘invisible’.  Thus, our metaphors can keep us from seeing things that might be relevant.

LEARNING & development

Thus, we should examine the metaphors we’re using in L&D.  We can start, of course, even with the term L&D: Learning & Development.  Typically, it’s the ‘learning’ part that dominates: we’re talking about helping people learn. And this metaphor implies: courses. Yet, we know that formal learning is only part of the picture of full development of capability. So the ‘development’ part should play a role, including coaching and the choice of assignments. Perhaps also meta-learning.  Though I’d suggest that these latter bits aren’t prominent, because learning can be a mechanism for development, and therefore the following steps lag. Which is why movements like 70:20:10 can be helpful in awakening a broader emphasis.

However, there’s more. In Revolutionize Learning & Development, I argued that we should switch the term to P&D, Performance & Development. Here I was trying to recognize that our learning has a goal: the ability to perform. Also, there are other paths to performance, including performance support.  I still wanted development, including formal learning, but we also want to develop the ability for the organization to continue to learn: innovation.  And I’m not claiming that this can break the problem with learning, as P&D might end up only emphasizing on performance, as L&D ends up only emphasizing learning.

The point being is that we need to have a perspective that doesn’t limit our vision. It’s the case that L&D could be just about courses, but I want to suggest that’s not optimal.  A ‘course’ perspective allows the focus to be on the delivery, not on the outcome. With more ability for individuals to learn on their own, traditional courses are likely to wither.  I think it’s a path to irrelevance.

I’ll suggest that we want to be thinking about all the ways that an organization can facilitate doing, and increasing the ability to do. Then we should figure out what parts we can contribute to. If, as I suggest, we want to be professional about understanding learning, then we have a basis to be the best people to guide all of it.

So I don’t know the best metaphor.  What I do believe is that ‘course’, and even ‘learning’ can be limiting. (I’ve also thought that ‘talent development’ is not sufficient.) I’ve suggested P&D, but perhaps it’s organic and about organizational growth. Or perhaps it’s about performance and increasing. So, now, it’s over to you: what do you think would be a helpful way to look at it. Do we need a rebranding, and if so, to what?

31 August 2017

Evidence-based L&D

Clark @ 8:08 AM

Conducting ScienceEarlier this year, I wrote that L&D was a ‘Field of Dreamsindustry, running on a belief that “if you build it, it is good”.  There’s strong evidence that we’re not delivering on the needs of the organization. So what is a good basis for finding ways to support people in the moment and develop them over time?  We want to look to what research and theory tell us .  In short, I think L&D should be evidence-based.

What does the evidence say?  There are a number of places where we can look, but first we have to figure out what we can (and should) be doing.  I suggest that L&D isn’t doing near what it could and should, and what it is doing, it is doing badly.  So let’s start with that latter.

One thing L&D should be doing is making learning experiences that have organizational impact.  There’s evidence that organizations that measure impact, do better. There’s also evidence that there are principles on which to design learning that leads to better outcomes.  Yet, despite signups for the eLearning Manifesto, there’s still evidence that organizations aren’t following those principles, if extant elearning is any indication. Similarly, the number of L&D units actually measuring their impact on organizational metrics seems to be lagging those that, for instance, just use ‘smile sheets‘. And even those are done badly.

There’s also an argument that L&D could and should be considering performance support as well. There are certainly instances where, as I’ve heard it said (and I’m paraphrasing, I can’t find the original quote): “inside every course there’s a lean job aid waiting to get out”. Certainly, performance can improve with a job aid instead of training (c.f. Atul Gawande’s Checklist Manifesto).

Further actions by L&D include facilitating communication and collaboration. Again, organizations that become learning organizations succeed better than those that don’t. The elements of a learning organization include the skills around working together and a culture where doing so can flourish.  We know what makes brainstorming work, and more.

In short, there’s a vast body of evidence about how to do things right. It’s time to become professionals, and pay attention. In that sense, we’re organizational learning engineers. While there may be a lack of evidence about the linkage between individual learning and organizational learning, we do know a lot about facilitating each.  And we should.  Are you ready?

 

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