Tag Archives: language

The Language of Thought

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The Language of Thought

GUEST POST from Geoffrey Moore

Where do thoughts come from? Is there any structure to them before they manifest themselves in language? Is there a universal grammar that underlies every actual grammar?

These questions have been asked many times before. My answers are as follows:

  • They come from below, not above.
  • They do have a readily describable structure.
  • That structure does indeed underly every actual grammar.

The first answer is the most important one. If the language of thought precedes symbolic language, then symbolic language is emergent from it, and the way to study is not through self-examination but rather by observing the behavior of non-language speaking agents. Of these my favorite two are babies and dogs. Both exhibit a myriad of strategic behaviors that imply thought but clearly do not entail language. So, based on observing them, what can we say about the structure of such thinking?

Babies and dogs, I propose, process the following five concepts routinely and effectively:

  1. Agents. They recognize and respond to people and animals that can interact with them, as indicated by their eye contact, their coming and going, and response to commands and gestures.
  2. Objects. They recognize and can discriminate among objects that interest them, both inanimate and animate, including foods, toys, playmates, and parents. They do not distinguish between animate and inanimate objects in any consistent way.
  3. Actions. They initiate and respond to actions in ways that further their interests, be that in feeding, playing, or getting attention. They are inherently attracted to action in any form.
  4. Valence. They discriminate between things they like and things they don’t like, seeking the former and avoiding the latter, as witnessed by their eating and their expressions of mood.
  5. Uncertainty. When uncertain, they hesitate and respond tentatively until they can resolve their uncertainty.

My claim is that these five concepts map directly to the fundamental syntax of every one of the six thousand or so symbolic languages currently in use. Agents and objects both convert to nouns and noun-like entities that serve as subjects and predicate objects in declarative statements. Similarly, actions convert to verbs and verb-like phrases. When we combine nouns with actions, we get predications, or what I like to term claims, which are the fundamental units of symbolic discourse. Valences foreshadow the use of adjectives, adverbs, and other modifiers that add nuances to our claims, and uncertainty is represented by modal verbs expressing possibility, probability, or necessity.

As much ground as all this covers, it is important to understand what the language of thought does not entail. Take the sentence “John is tall.” That thought would never occur to either a baby or a dog. It is inherently symbolic in nature, and until you have a symbolic language, it cannot exist. In The Infinite Staircase, it belongs to the stairstep of analytics, whereas the language of thought can reach no higher than the stairstep of narrative.

It is on the stairstep of narrative that the language of thought passes the baton to symbolic language. We cannot tell stories without symbolic language, but it is clear from the behavior of both toddlers and long-term pets that we want to. The connection that binds the two at this point is a realization of cause and effect. Narrative is how we process cause and effect. The breakthrough of symbolic language is that we can not only be a lot more precise in our communication, increasing its efficacy, but also that we can abstract from one narrative concepts and patterns that can be applied elsewhere. This is the miracle of analytics, and it only comes with symbolic language.

To close, let’s revisit our first question—where exactly do our (symbolic-language-expressed) thoughts originate from? This is not a brain-processing question—that landscape is still under investigation—but rather a question of lived experience. Where does it feel like they come from?

My answer is that they are chemically generated responses that represent fluctuations in our homeostatic balance. Like all organisms, we are compelled to seek this balance all the time. The more we get out of balance, the stronger the chemical signal to respond, the more intense the resultant stream of thoughts will be. This applies to dreams as well as to when we are awake. We are continually processing a stream of thoughts that emerge into consciousness and finding their linguistic expression as they do. We register these thoughts through listening to ourselves and shape them further through talking to ourselves. It is only when we get to the talking that we are fully immersed in symbolic language.

That’s what I think. What do you think?

— Image credit: Pixabay

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Do Your Innovation Words Match Your Actions?

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Do Your Innovation Words Match Your Actions?

GUEST POST from Mike Shipulski

Innovation isn’t a thing in itself. Companies need to meet their growth objectives and innovation is the word experts use to describe the practices and behaviors they think will maximize the likelihood of meeting those growth objectives. Innovation is a catchword phrase that has little to no meaning. Don’t ask about innovation, ask how to meet your business objectives. Don’t ask about best practices, ask how has your company been successful and how to build on that success. Don’t ask how the big companies have done it – you’re not them. And, the behaviors of the successful companies are the same behaviors of the unsuccessful companies. The business books suffer from selection bias. You can’t copy another company’s innovation approach. You’re not them. And your project is different and so is the context.

With innovation, the biggest waste of emotional energy is quest for (and arguments around) best practices. Because innovation is done in domains of high ambiguity, there can be no best practices. Your project has no similarity with your previous projects or the tightest case studies in the literature. There may be good practice or emergent practice, but there can be no best practice. When there is no uncertainty and no ambiguity, a project can use best practices. But, that’s not innovation. If best practices are a strong tenant of your innovation program, run away.

The front end of the innovation process is all about choosing projects. If you want to be more innovative, choose to work on different projects. It’s that simple. But, make no mistake, the principle may be simple the practice is not. Though there’s no acid test for innovation, here are three rules to get you started. (And if you pass these three tests, you’re on your way.)

  1. If you’ve done it before, it’s not innovation.
  2. If you know how it will turn out, it’s not innovation.
  3. If it doesn’t scare the hell out of you, it’s not innovation.

Once a project is selected, the next cataclysmic waste of time is the construction of a detailed project plan. With a well-defined project, a well-defined project plan is a reasonable request. But, for an innovation project with a high degree of ambiguity, a well-defined project plan is impossible. If your innovation leader demands a detailed project plan, it’s usually because they are used running to well-defined continuous improvement projects. If for your innovation projects you’re asked for a detailed project plan, run away.

With innovation projects, you can define step 1. And step 2? It depends. If step 1 works, modify step 2 based on the learning and try step 2. And if step 1 doesn’t work, reformulate step 1 and try again. Repeat this process until the project is complete. One step at a time until you’re done.

Innovation projects are unpredictable. If your innovation projects require hard completion dates, run away.

Innovation projects are all about learning and they are best defined and managed using Learning Objectives (LOs). Instead of step 1 and step 2, think LO1 and LO2. Though there’s little written about LOs, there’s not much to them. Here’s the taxonomy of a LO: We want to learn if [enter what you want to learn]. Innovation projects are nothing more than a series of interconnected LOs. LO2 may require the completion of LO1 or L1 and LO2 could be done in parallel, but that’s your call. Your project plan can be nothing more than a precedence diagram of the Learning Objectives. There’s no need for a detailed Gantt chart. If you’re asked for a detailed Gantt chart, you guessed it – run away.

The Learning Objective defines what you learn, how you want to learn, who will do the learning and when they want to do it. The best way to track LOs is with an Excel spreadsheet with one tab for each LO. For each LO tab, there’s a table that defines the actions, who will do them, what they’ll measure and when they plan to get the actions done. Since the tasks are tightly defined, it’s possible to define reasonable dates. But, since there can be a precedence to the LOs (LO2 depends on the successful completion of LO1), LO2 can be thought of a sequence of events that start when LO1 is completed. In that way, an innovation project can be defined with a single LO spreadsheet that defines the LOs, the tasks to achieve the LOs, who will do the tasks, how success will be determined and when the work will be done. If you want to learn how to do innovation, learn how to use Learning Objectives.

There are more element of innovation to discuss, for example how to define customer segments, how to identify the most important problems, how to create creative solutions, how to estimate financial value of a project and how to go to market. But, those are for another post.

Until then, why not choose a project that scares you, define a small set of Learning Objectives and get going?

Image credits: Pixabay

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Are Humans Just a Fleshy Generative AI Machine?

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Are Humans Just a Fleshy Generative AI Machine?

GUEST POST from Geoffrey A. Moore

By now you have heard that GenAI’s natural language conversational abilities are anchored in what one wag has termed “auto-correct on steroids.” That is, by ingesting as much text as it can possibly hoover up, and by calculating the probability that any given sequence of words will be followed by a specific next word, it mimics human speech in a truly remarkable way. But, do you know why that is so?

The answer is, because that is exactly what we humans do as well.

Think about how you converse. Where do your words come from? Oh, when you are being deliberate, you can indeed choose your words, but most of the time that is not what you are doing. Instead, you are riding a conversational impulse and just going with the flow. If you had to inspect every word before you said it, you could not possibly converse. Indeed, you spout entire paragraphs that are largely pre-constructed, something like the shticks that comedians perform.

Of course, sometimes you really are being more deliberate, especially when you are working out an idea and choosing your words carefully. But have you ever wondered where those candidate words you are choosing come from? They come from your very own LLM (Large Language Model) even though, compared to ChatGPT’s, it probably should be called a TWLM (Teeny Weeny Language Model).

The point is, for most of our conversational time, we are in the realm of rhetoric, not logic. We are using words to express our feelings and to influence our listeners. We’re not arguing before the Supreme Court (although even there we would be drawing on many of the same skills). Rhetoric is more like an athletic performance than a logical analysis would be. You stay in the moment, read and react, and rely heavily on instinct—there just isn’t time for anything else.

So, if all this is the case, then how are we not like GenAI? The answer here is pretty straightforward as well. We use concepts. It doesn’t.

Concepts are a, well, a pretty abstract concept, so what are we really talking about here? Concepts start with nouns. Every noun we use represents a body of forces that in some way is relevant to life in this world. Water makes us wet. It helps us clean things. It relieves thirst. It will drown a mammal but keep a fish alive. We know a lot about water. Same thing with rock, paper, and scissors. Same thing with cars, clothes, and cash. Same thing with love, languor, and loneliness.

All of our knowledge of the world aggregates around nouns and noun-like phrases. To these, we attach verbs and verb-like phrases that show how these forces act out in the world and what changes they create. And we add modifiers to tease out the nuances and differences among similar forces acting in similar ways. Altogether, we are creating ideas—concepts—which we can link up in increasingly complex structures through the fourth and final word type, conjunctions.

Now, from the time you were an infant, your brain has been working out all the permutations you could imagine that arise from combining two or more forces. It might have begun with you discovering what happens when you put your finger in your eye, or when you burp, or when your mother smiles at you. Anyway, over the years you have developed a remarkable inventory of what is usually called common sense, as in be careful not to touch a hot stove, or chew with your mouth closed, or don’t accept rides from strangers.

The point is you have the ability to take any two nouns at random and imagine how they might interact with one another, and from that effort, you can draw practical conclusions about experiences you have never actually undergone. You can imagine exception conditions—you can touch a hot stove if you are wearing an oven mitt, you can chew bubble gum at a baseball game with your mouth open, and you can use Uber.

You may not think this is amazing, but I assure you that every AI scientist does. That’s because none of them have come close (as yet) to duplicating what you do automatically. GenAI doesn’t even try. Indeed, its crowning success is due directly to the fact that it doesn’t even try. By contrast, all the work that has gone into GOFAI (Good Old-Fashioned AI) has been devoted precisely to the task of conceptualizing, typically as a prelude to planning and then acting, and to date, it has come up painfully short.

So, yes GenAI is amazing. But so are you.

That’s what I think. What do you think?

Image Credit: Google Gemini

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Why Words Matter

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Why Words Matter

GUEST POST from Mike Shipulski

We all want to make progress. We all want to to do the right thing. And we all have the best intentions. But often we don’t pay enough attention to the words we use.

There are pure words that convey a message in a kind soothing way and there are snarl words that convey a message in a sharp, biting way. It’s relatively easy, if you’re paying attention, to recognize the snarl and purr. But it’s much more difficult to take skillful action when you hear them used unskillfully.

A pure word is skillful when it conveys honest appreciation, and it’s unskillful when it manipulates under the banner of false praise. But how do you tell the difference? That’s where the listening comes in. And that’s where effective probing can help.

If you sense unskillful use, ask a question of the user to get at the intent behind the language. Why do you think the idea is so good? What about the concept do you find so interesting? Why do you like it so much? Then, use your judgment to decide if the use was unskillful or not. If unskillful, assign less value to the purr language and the one purring it.

But it’s different with snark words. I don’t know of a situation where the use of snarl words is skillful. Blatant use of snarl words is easy to see and interpret. And it looks like plain, old-fashioned anger. And the response is straightforward. Call the snarler on their snarl and let them know it’s not okay. That usually puts an end to future snarling.

The most dangerous use of snarl words is passive-aggressive snarling. Here, the snarler wants all the manipulative benefit without being recognized as a manipulator. The pros snarl lightly to start to see if they get away with it. And if they do, they snarl harder and more often. And they won’t stop until they’re called on their behavior. And when they are called on their behavior, they’ll deny the snarling altogether.

Passive-aggressive snarling can block new thinking, prevent consensus and stall hard-won momentum. It’s nothing short of divisive. And it’s difficult to see and requires courage to confront and eviscerate.

If you see something, say something. And it’s the same with passive-aggressive snarling. If you think it is happening, ask questions to get at the underlying intent of the words. If it turns out that it’s simply a poor choice of words, suggest better ones and move on. But if the intent is manipulation, it must be stopped in its tracks. It must be called by name, its negative implications must be be linked to the behavior and new behavioral norms must be set.

Words are the tools we use to make progress. The wrong words block progress and the right ones accelerate it.

Why not choose the right words?

Image credit: Unsplash

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Top 10 Human-Centered Change & Innovation Articles of May 2025

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Top 10 Human-Centered Change & Innovation Articles of May 2025Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are May’s ten most popular innovation posts:

  1. What Innovation is Really About — by Stefan Lindegaard
  2. ‘Stealing’ from Artists to Make Innovations Both Novel and Familiar — by Pete Foley
  3. Benchmarking Innovation Performance — by Noel Sobelman
  4. Transform Your Innovation Approach with One Word — by Robyn Bolton
  5. Building Innovation Momentum Without the Struggle — Five Questions for Tendayi Viki
  6. Change Behavior to Change Culture — by Mike Shipulski
  7. The Real Reason Your Team Isn’t Speaking to You — by David Burkus
  8. The Enemy of Customer Service is … — by Shep Hyken
  9. Three Real Business Threats (and How to Solve Them) — by Robyn Bolton
  10. Better Customer Experiences Without Customer Feedback — by Shep Hyken

BONUS – Here are five more strong articles published in April that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Build a Common Language of Innovation on your team

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last four years:

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Top 10 Human-Centered Change & Innovation Articles of February 2025

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Top 10 Human-Centered Change & Innovation Articles of February 2025Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are February’s ten most popular innovation posts:

  1. Innovation is Dead. Now What? — by Robyn Bolton
  2. When Best Practices Become Old Practices — by Mike Shipulski
  3. 3 Keys to Improving Leadership Skills — by David Burkus
  4. Audacious – How Humans Win in an AI Marketing World — Exclusive Interview with Mark Schaefer
  5. Which Go to Market Playbook Should You Choose? — by Geoffrey A. Moore
  6. Turns Out the Tin Foil Hat People Were Right — by Braden Kelley
  7. Are You a Leader? — by Mike Shipulski
  8. Time to Stop These Ten Bad Customer Experience Habits — by Shep Hyken
  9. Beyond the AI Customer Experience Hype — by Shep Hyken
  10. A Tumultuous Decade of Generational Strife — by Greg Satell

BONUS – Here are five more strong articles published in January that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

SPECIAL BONUS: While supplies last, you can get the hardcover version of my first bestselling book Stoking Your Innovation Bonfire for 44% OFF until Amazon runs out of stock or changes the price. This deal won’t last long, so grab your copy while it lasts!

Build a Common Language of Innovation on your team

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last four years:

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Does Saying Innovation Make You Sound Stupid?

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Does Saying Innovation Make You Sound Stupid?

GUEST POST from Robyn Bolton

“You sound stupid when you use the word ‘_____________’ because you’re trying to sound smart.”Mark Cuban

What goes in the blank?

For Mark Cuban, it’s “cohort” because “there’s no reason to ever use the word ‘cohort’ when you could use the word ‘group.’  A cohort is a group of people.  Say ‘group.’ Always use the simpler word.”

For one of my former bosses, it was “breakthrough.”  He would throw you out of the room if you used that word.  Not physically throw you out, but he was a big guy and could if you didn’t exit on your own.

For me, it’s “disrupt” (and all its forms) because applies (as originally intended by Clayton Christensen) in only about 0.1% of the instances in which it’s used.

There are other candidates.

Lots of other candidates.

In fact, I would go so far as to propose the biggest buzzword of them all: INNOVATION.

“Innovation” does not make you sound smart.

Here is a very short list of the most commonly heard statements about innovation.

  • Innovation is a priority.
  • Innovation is key to our growth.
  • We need to be more innovative.
  • We want to build/are committed to building a culture of innovation
  • Let’s innovate!

What do these statements even mean?

  • It’s great that innovation is a priority and key to our growth.  Hasn’t that always been the case?  What is changing? How is that translating into action? What do you expect from me?
  • Agree we should be more innovative.  How? What does “more innovative” look like?
  • Definitely want to be part of a culture of innovation.  What does that mean?  How is that different than our current culture?  What changes? How do we make sure the changes stick?
  • Sigh. Eye roll.

Saying what you mean makes you sound smart.

Always use the simpler word, and, in the case of innovation, there is always a simpler word or phrase.  Consider:

  • Grow revenue from our existing businesses
  • Create new revenue streams
  • Grow profit in our existing businesses
  • Grow profit by launching new high-profit businesses
  • Stay ahead of the competition
  • Create a new category
  • Launch a new product
  • Better serve our current customers
  • Serve new customers
  • Update/extend our current products
  • Increase the effectiveness of our marketing spend
  • Revise our business model to reflect changing consumer and customer expectations
  • Launch a low-cost and good-enough offering that appeals to non-consumers

You sound smart when you use the word(s) that most clearly, concisely, and unambiguously communicate your idea or intention.  “Innovation” does not do that.

Saying “innovation” AND what you mean makes you sound wicked smaht

“Innovation” on its own is lazy.  Simpler words and phrases aren’t nearly as sexy (I can’t imagine Fast Company coming out with “The World’s Best Companies at Creating New Revenue Streams” list).

But when you put them together – smart and sexy:

  • Innovation is a priority.  As a result, we are committing a minimum of $50M a year for the next five years to…
  • Innovation is key to growth.  As a result, we are doubling our investment in…
  • We need to be more innovative.  To achieve this, we are changing how we measure and incentivize executive performance to encourage long-term investments.
  • We want to build a culture of innovation.  As a first step in this process, we are making Kickbox available to any interested employee.
  • Let’s Innovate (Nope, don’t say this.  It’s too cheesy)

Say what you mean. 

If you don’t, people will think you don’t mean what you say.

What other words would you add to this rant?

Image credit: unsplash

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Innovation vs. Invention vs. Creativity

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Innovation vs. Invention vs. Creativity

by Braden Kelley

There is so much talk about innovation these days, it’s hard to sometimes distinguish the signal from the noise.

In fact, the word innovation gets thrown around so much that it leaves people wondering:

What’s really innovative?

Well, most of the time that people talk about something being innovative, what they describe isn’t innovative, but instead inventive or creative. These three are all very different. Here is how I like to distinguish the differences between creativity, invention and innovation:

  1. Creativity – creates something interesting
  2. Invention – creates something useful
  3. Innovation – creates something so valuable that it is widely adopted, replacing the existing solution in a majority of appropriate use cases

Very few creative sparks result in an invention and very few inventions become innovations.

And the painful truth is that many great inventions take 20-30 years to be realized. Timing your investment is the key to whether you waste a big wad of cash, or still have it to spend when the optimal time to invest in a potential innovation comes.

If you look at most technology-based innovations, whether it’s the mp3 or the VCR, they were invented 20-30 years before they reached wide adoption in the marketplace, and for Gorilla Glass we’re talking more like 50 years.

To further emphasize the importance of timing…

Look at Webvan vs. Amazon Fresh

Look at Pets.com vs. Chewy.com (acquired by Petsmart)

Now these aren’t innovations, but you get my point. You have to know where you are on the commercialization timeline…

And most importantly, sometimes you have to look BACKWARDS before you look forwards, so you know where on the commercialization timeline you are.

If you’re working on a potential innovation now, are you sure it’s a potential innovation?

Are you sure now is the time to go big?

Read more about Premature Innovation

You might also enjoy Are You Innovating for the Past or the Future?

Image credit: Pexels

Innovation Audit from Braden Kelley

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Let’s Chat About the Language of Innovation

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Let’s Chat About the Language of Innovation

It was bound to happen sooner or later…

What is it you might ask?

Well, it is the recognition that the language we use (and more importantly, having a common language) when it comes to innovation, to change, or to pretty much any other aspect of business is just as important as it is in our personal lives.

Who does the recognition come from?

Well, none other than the innocats, a cool group of people who host a twitter chat at #innochat every Thursday at 5PM GMT (that’s 9AM for those of you on the west coast of the USA, Noon on the east coast, and well, 5PM for those of you in the UK).

Personally I tend to use Tweetchat.com to participate in twitter chats like this because it makes it easy to follow along real-time. If you go to the Tweetchat.com web site, just enter the hashtag #innochat as the room you’d like to enter.

So, come join me tomorrow (October 9, 2014) for an #innochat on the language of innovation. You can find the introductory post for the session here:

Sorry, link expired

UPDATE: Sorry, link to transcript expired

On that page you’ll also find links to my latest article on the topic and my latest white paper (commissioned by Planview).

If you’d like to commission a white paper, webinar, or keynote speech on innovation, social business, inbound/digital/content marketing or some other topic you think I can help people make sense of, contact me.

Otherwise, come join me for a lively Twitter discussion of the importance of a common language of innovation.

Oh, and if you’re curious what my current definition of innovation is, here you go:

“Innovation transforms the useful seeds of invention into widely adopted solutions valued above every existing alternative.” – Braden Kelley

Keep innovating!

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Innovation Goes to the Dogs?

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Innovation Going to the Dogs?

In case you missed it, a team from Scandinavia thinks that they’ve nearly cracked no, not the human-computer interface, but the dog-computer interface, so that some day soon we might in fact be able to understand man’s best friend.

What does the dog say?

Well, this question begs another question, do we really care? Or do we really want to hear it all of the time?

They’ve launched an IndieGoGo campaign and have already exceeded their campaign funding goal, so I guess they’ll be moving their research and product development on to the next stage.

So, what do you think, if they push the product to the finish line, will it be an invention or an innovation?


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