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‘Stealing’ from Artists to Make Innovations Both Novel and Familiar

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AKA Self Plagiarism

Stealing from Artists to Make Innovations Both Novel and Familiar

GUEST POST from Pete Foley


This morning I came across a wonderful piece of music by one of my guitar heroes, Robert Fripp, of King Crimson fame.  It was a duet with Andy Sommers (The Police).  You don’t need to listen to it to connect to the insight it gave me, but if you are interested, you can watch it here. It’s interesting and innovative music

I’m a fan of Fripp, in part because of his technical expertise with the guitar, but mostly because of his innovation and restless creativity.   King Crimson are not a top 40 band, but they’ve enjoyed a long and successful career going back to the late 1960’s.  Their longevity derives, at least in part from their ability to completely reinvent themselves, and challenge their audience on a regular basis.  But they do so while also retaining a loyal following and owning a unique space in music.  They have, over 50 odd years, managed to walk the tightrope between constant change and ongoing familiarity.  

The Novelty-Familiarity Dichotomy:  Stepping back, that tightrope is one of the biggest challenges we all face as innovators.  Hitting the sweet spot between novelty and familiarity is key to both trial and repeat. If we don’t offer something new and interesting, then people have no reason to try us, and are better off staying with their existing habits and behaviors.  But make it too different, and we create a barrier to adoption, because we ask potential users to take a risk by straying from the proven and familiar, and to put effort into trying, using and understanding us. 

This reflects the somewhat schizophrenic, or at least dual personality of our collective human behavior.  We are drawn to familiarity, but have also evolved to crave novelty.  Our desire to experiment and explore is key to why we are the dominant species on the planet, and have expanded our presence to just about every habitat on the planet.  But the lower cognitive demands of the familiar mean much of our life is still dominated by habits, comfortable repetition and familiar activities.  Whether we an artist, a brand, work in an office, or are simply in a romantic relationship, we all have to navigate this dichotomy.  

Self Plagiarizing:  That brings me back to Robert Fripp.  Given his history of continuous change, and much as I enjoyed the track, I was surprised that the core riff sounded very, very similar to a King Crimson song Thela Hut Ginje, released the year before.  They are both Robert Fripp co-compositions, so he was effectively ‘stealing’ his own ideas, or self plagiarizing. 

Initially that seemed odd for someone who has for decades been a formidable change agent.   But I often learn a lot about the innovation process via analogy from music and fine arts.  So I started thinking about self plagiarism, and if it is a tool we could or should use more in innovation in general, as a potential way to maintain familiarity while also driving change  

Transferring our own signatures into multiple new executions ensures familiarity and hence reassures to our ‘loyal’ users.  But in parallel, putting those signatures in new contexts also provides a way to draw in new ‘fans’, or safely break monotony for our ‘regulars’.   Of course, at one level, the reassurance element is exactly what branding does.   But the concept of self plagiarism is potentially a way to achieve this on a more subtle, implicit level.   

Name that Band!  The arts community are masters of this.   It’s amazing to me how often we almost instantly recognize an artist, even if the painting or song itself is not familiar.  Maybe it’s a unique voice, a unique style or sound, or perhaps a signature motif.  Whether it’s David Bowie, Mick Jagger, Pablo Picasso,  Salvador Dali or Taylor Swift, we intuitively and largely unconsciously recognize their ‘style’.   Of course, explicit continuity and consistency is also important.  The wall of color in a supermarket acts as both a signpost, and reinforces important popularity cues.   Even in more dispersed digital environments, more ‘explicit’  cues provide important and cognitively simple cues that tie individual innovations to over-arching brands.  

But self reference, or self plagiarism is an additional tool that I think is worth exploring.  It allows us to leverage (implicit) sensory cues to reinforce brand consistency, and is one potential way to reinforce continuity in the face of evolutionary or even disruptive change. And just as you may intuitively recognize a song by your favorite artist without having to ‘think’ about it, it can operate very quickly, and help an innovation to ‘feel’ right.

Bob Dylan Goes Electric: And having more implicit tools can help with some of the inherent constraints of consistent branding.  Chasing familiarity can be both a blessing and a curse; ask any classic rock band on a greatest hits tour.  Or for any of you who saw the excellent “A Complete Unknown’ movie about Dylan, that culminates in the outrage he created with his core fan base by ‘going electric.  Maintaining familiarity ‘talks’ to a loyal audience, but can also be quite constraining, especially for the most innovative amongst us. And this can be especially challenging if, as in Dylan’s case, the outside world is changing quickly and we need or want to respond.  But there are numerous examples of artists who have done this quite successfully.  For better or for worse, Dylan still sounded distinctly like Dylan after he ‘rebranded’ as electric.  David Bowie, Madonna, or the different ‘periods’ that describe Picasso’s catalog are good examples of dramatic change and reinvention that still maintain some familiarity and consistency.  

What taking this kind of approach looks like for us will of course depend upon the area in which we are innovating.  But sensory cues, shapes, or relative design elements are all cues we can self-plagiarize, that add layers of familiarity, and are often difficult for competition to copy without evoking as, and hence increasing the ‘mind-share’ of their competitor.     

Of course, this is not to suggest replacing brand (visual) language and brand first design with subtle, implicit cues.   But the journey of a brand is complex, and in today’s world of rapid change, we are likely to increasingly need ways to manage ever greater changes within a ‘familiar’ context.  Thinking about different, potentially complementary ways to do this is never a bad idea. 

Image credits: Pixabay

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Cover versions, Sequels, Taylor Swift and Innovation

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Taylor Swift and Innovation

GUEST POST from Pete Foley

An inherent contradiction in almost any new innovation is that it needs to be both new, but also somewhat familiar.  If it doesn’t offer anything new, there is little motivation for consumers to risk abandoning existing habits or preferences to try it.  But if it is not at least anchored in familiarity, then we ask consumers to put a lot of effort into understanding it, in addition to any opportunity cost from what they give up for trying something new.  Innovation is difficult, and a lot of innovations fail, at least in part because of this fundamental contradiction. 

Transformative Performance:  Of course, innovations can be successful, which means we do navigate this challenge.  But how? One way is to deliver something with such transformative benefits that people are willing to push themselves over the hump of learning something new. Huge benefits also create their own ‘gravity’, often spreading via world of mouth via media, social media, and even old-fashioned human-to-human conversations. This avoids the need for brute force mass marketing spend that can create the illusion of familiarity, but with a hefty price tag that is typically beyond smaller companies

Familiarity: The second option is to leverage what people already know in such a way that the ‘adoption hump’ becomes relatively insignificant, because new users intuitively know what the innovation is and how to use it.

Wow!  The best innovations do both.  CHATgpt Generative AI is a contemporary example, where transformative performance has created an enormous amount of word of mouth, but the interface is so intuitive there is little barrier to adoption, at least superficially. 

Of course, using it skillfully is another thing altogether, but I think there is an insight there too.  It’s OK to have an ongoing learning curve after initial adoption, but initial engagement needs to be relatively simple.  The gaming industry are masters of this.    

Little Wows!  CHATgpt is brilliant innovation.  But realistically, few of us are gong to create something quite that extraordinary.  So how do we manage to create more modest wows that still drive trial, engagement and ultimately repeat business?

Science, Art and Analogy:  As a believer that a lot of interesting things happen at the interface between science and art, and that analogy is a great tool, I think we cam learn a little about solving this by taking insight from the arts.  In this case, music and movies. For example, popular music routinely plunders the familiar, and repackages it as new via cover versions.  I often do the same myself!   Movies do something similar, either with the cycle of remakes of classic movies, or with sequels that often closely follow the narrative structure of the original.  

But this highlights some of the challenges in solving this dichotomy.  It’s rare for a remake, cover version, or sequel to do better than the original.  But a few do, so what is their secret?  What works, and what doesn’t? 

  1. Distance from the original.  Some of the best movie remakes completely reframe the original in ways that maintain a largely implicit familiarity, but do so without inviting direct comparisons of alignable differences to the original. For example, West Side Story is a brilliant retelling of Romeo and Juliet, Bridget Jones Diary reframes Pride and Prejudice, She’s All That is a retelling of George Bernard Shaw’s Pygmalion, while The Lion King retools Hamlet, etc.  I’m not suggesting that nobody sees these connections, but many don’t, and even if they do, the context is sufficiently different to avoid constant comparisons throughout the experience.  And of course, in most of these cases, the originals are not contemporary, so there is temporal as well as conceptual distance between original and remake.   Similarly with cover versions, Hendrix and the Byrds both completely and very successfully reframed Dylan (All Along the Watchtower and Mr. Tambourine Man).  Sinead O’Connor achieved similar success with Prince’s “Nothing Compares 2 U”.  For those of you with less grey in their hairl, last summers cover of Tracy Chapman’s ‘Fast Car’ by Luke Combs shows that covers can still do this. 

2.  Something New.   A different way to fail is to tap familiarity, but without adding anything sufficiently new or interesting.  All too often covers, sequels and remakes are simply weaker copies of the original.  I’m sure that anyone reading this can come up with their own examples of a disappointing remake or sequel.   Footloose, Annie, Psycho, Tom Cruise’s the Mummy or Karate Kid are all candidates for me.  As for sequels, again, I’m sure you can all name a respectable list of your own wasted 2 hours, with Highlander 2 and Jaws the Revenge being my personal cures for insomnia.   And even if we include novelty, it cannot be too predictable either.  It needs to at least be a little surprising.   For example, the gender reversal of the remake of Overboard has a point of difference in comparison to the Goldie Hawn original, but its not exactly staggeringly novel or surprising.  It’s a lot like a joke, if you can see it coming, it’s not going too create a wow.    

3.  Don’t Get De-Selected.  Learning from the two previous approaches can help us to create sufficient separation from past experience to engage and hopefully delight potential consumers.  But it’s important to not get carried away, and become un-tethered from familiarity.  For example, I personally enjoy a lot of jazz, but despite their often extraordinary skill, jazz musicians don’t fill many arenas.  That’s in part because jazz asks the listener to invest a lot of cognitive bandwidth and time to develop an ‘ear’, or musical expertise in order to appreciate it. It often moves a long way from the familiar original, and adds lot of new into the equation.  As a result, it is a somewhat niche musical form.  Pop music generally doesn’t require the same skill or engagement, and successful artists like Taylor Swift understand that.   And when it comes to innovation, most of us want to be mainstream, not niche. This is compounded because consumers today face a bewildering array of options, and a huge amount of information.  One way our brains have evolved to deal with complexity is to quickly ignore or ‘de-select’ things that don’t appear relevant to our goals. A lot of the time, we do this unconsciously.  Faced with more information than we can process, we quickly narrow our choices down to a consideration set that is ‘right-sized’ for us to make a decision.   From an innovation perspective, if our innovations are too ‘jazzy’, they risk being de-selected by a majority on consumers before they can be fully appreciated, or even consciously noticed.     

There’s no precise right or wrong strategy in this context. It’s possible to deliver successful innovations by tapping and balancing these approaches in many different ways.   But there are certainly good and bad executions, and I personally find it helpful to use these kinds of analogy when evaluating an innovation.   Are we too jazzy? Do we have separation from incumbents that is meaningful for consumers, and not just ourselves? And the latter is a real challenge for experts. When we are deeply engaged in a category, it’s all too easy to get lost in the magic of our own creations.  We see differences more clearly than consumers. It’s easy for us to become overly excited by relatively small changes that excite us, but that lack sufficient newness and separation from existing products for consumers who are nowhere near as engaged in our category as we are.  But it’s also easy to create ‘jazz’ for similar reasons, by forgetting that real world consumers are typically far less interested in our products than we are, and so miss the brilliance of our ‘performance’, or perhaps don’t ‘get it’ at all. 

For me, it is useful to simply ask myself whether I’m a Godfather II or a Highlander II, a Taylor Swift or a Dupree Bolton, or even Larry Coryell.  And there’s the rub.  As a musician, I’d rather be Larry, but as a record company exec, I’d far rather have Taylor Swift on my label. 

Image credits: Wikimedia Commons

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How to Use Your Nervous System to Feel Psychologically Safe

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or “Why Mandating a Return to the Office Destroys Safety”

How to Use Your Nervous System to Feel Psychologically Safe

GUEST POST from Robyn Bolton

In last week’s episode, we learned that psychological safety is more neuroscience than psychology and the huge role our nervous system plays in our experience of safety. 

This week, we’re going deeper into our nervous system and how we can use our understanding of it to influence our psychology.

I’m sensing I can’t think my way to safety.  So, can I fix my nervous system to feel safe and smart?

This is where I go beyond Dr. Amy Edmondson’s definition of psychological safety to incorporate neuroscience and how our nervous system works.

Our nervous system has three states:

  1. Immobilization or the freeze response, as you felt, is often accompanied by a sense of overwhelm
  2. Fight-and-flight when you try to either end the conversation or become more aggressive, resistant, and push back on exploring other alternatives.
  3. Rest-and-Digest when you feel safe, social, and connected to the people around you

This third state sets humans and mammals apart from other living things.  Communicating and connecting serve as a survival mechanism and represent a safe state for our nervous system.  When we communicate and connect, our tribe looks out for us and keeps us safe from threats like lions or unfriendly tribes.

So, the answer is to foster more profound connections among human beings, which requires going well beyond our work roles and activities.

Does it require hugging?  I knew it would require hugging.

Don’t worry, hugging isn’t mandatory.

We, as individuals, have a strong desire to connect and communicate, but it doesn’t necessarily require physical proximity. Being physically together doesn’t guarantee anything.

But what about the push to return to the office? There’s even research to support executives’ claims that physical proximity is essential to culture, innovation, and connection.

Not only does physical proximity not guarantee anything, but being forced to return to the office causes more harm than good. 

From a safety perspective, our nervous system doesn’t want to feel trapped. Being forced back to the office activates our flight-or-fight response and erodes safety. Because of how our nervous system perceives choices, the more choices people have, the safer they feel.

Even though I’m tempted to ask questions about building psychological safety at the team or company level, I want to stay on the individual level for a moment. We talked about how I wasn’t consciously unsafe during a phone call. How can I tell when I feel unsafe if I’m not conscious of it?

There’s physical science behind what happens when you feel unsafe. Your heart rate increases, you might hold your breath, and your body may tense up.  Your thoughts might blank out, and your peripheral vision may narrow as your body prepares for fight or flight.  Your body doesn’t differentiate; it treats any threat as a threatening event.

On the other hand, feeling safe doesn’t mean you lack emotions or feel calm. Feeling calm and internally relaxed signifies safety, but it’s more than that.  When your nervous system is regulated, your emotions align with the situation. They’re not an extreme overreaction or underreaction. There’s congruence. If your emotional response matches the situation, your nervous system and brain feel safe.

That makes sense, but it’s not easy.  We’re trained to hide our emotions and always appear calm.  I can’t tell you how many times I’ve heard and said, “Be a duck.  Calm on the surface and paddling like hell below it.”

And that is not congruent.  But congruence doesn’t mean you act out like a toddler, either.

Step one in creating safety is calming your nervous system by verbalizing your feelings. If you say, “This conversation is overwhelming for me. I need a break. Let me get some water,” you’re safe and regulated at that moment. There’s nothing wrong.

But when you can’t verbalize what you’re experiencing and freeze, that’s a sign you’re no longer in a safe state. Your body starts pumping cortisol and adrenaline, preparing for whatever it perceives as a threat.

Even if you feel overwhelmed, if you’re aware of that feeling and can take some breaths or a short break and return to the conversation, you’re in a safe, regulated state.

I can’t imagine admitting to feeling overwhelmed or asking for a break! Plus, I work with so many people who say, “I feel overwhelmed, but I can’t take a moment for myself.  I need to plow through and get this done.”

It takes a tremendous amount of self-awareness. If you want to create safety and emotional intelligence, you must know what you’re feeling and be able to name it. You also need to sense what others are feeling and understand your emotional impact on them.

For example, if you say, “I’m feeling overwhelmed right now,” and I respond calmly and slow my cadence of speech, your nervous system receives the message that everything is okay.  However, if I’m in “fight or flight” mode and you’re overwhelmed, we’ll end up in a chaotic and unproductive cycle.

Self-awareness and understanding are essential to safety. Unfortunately, many organizations I speak with need help with this.

Amen, sister,

Stay tuned for next week’s exciting conclusion, 3 Steps to Building a Psychologically Safe Environment or The No-Cost, No-Hug Secret to Smarter Teams

Image Credit: Pexels

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How to Create Energy with Customers (And Everyone Else)

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How to Create Energy with Customers (And Everyone Else)

GUEST POST from Shep Hyken

The heliotropic effect is the tendency for any living thing to be drawn toward energy. For example, if you put a plant on a windowsill, it will eventually lean toward the window where the sun comes in, soaking up those rays as the nourishment it needs to sustain its life.

Dr. Harry Cohen took this scientific concept and applied it to humans. In his book Be the Sun, Not the Salt, he defines the human version of the heliotropic effect as “being kind, authentic, compassionate, grateful and positive. … When you are being heliotropic, you are a positive energizer that uplifts others.”

In this short book that most people could read in less than an hour, Dr. Cohen shares 30 simple yet powerful principles and tactics that will create the energy that draws people to you. For leaders, you will build a stronger following. For managers, you will create a better work environment. And if you deal with customers, which is the focus of my work, you will get them to like you, trust you and want to do more business with you. And the best part about these thirty (30) ideas is that they don’t cost money, and you can put them into practice immediately.

Here are a few of my favorites that will make you think and, if you practice them, will have a heliotropic effect of attracting others toward you.

    1. Do All the Good You Can — Let’s start with the first one in the book. Just do good. People will be drawn to you, you’ll be more effective in what you do, and you’ll feel good yourself. It’s a fulfilling idea. When you do good, you feel good.
    2. Be Helpful — This seems so simple and obvious, but consider this. In our annual customer experience research, we asked more than 1,000 U.S. consumers, “What customer service experiences are most likely to cause you to come back?” The No. 1 answer was helpful. Such a simple concept!
    3. Show You Care — Insincerity is easy to spot, and nobody likes to do business or be around insincere people. You can’t fake caring—so don’t try. Be authentic about it. Maya Angelou said, “If you find it in your heart to care for somebody else, you will have succeeded.” I also like the Theodore Roosevelt quote Dr. Cohen included in this chapter, “Nobody cares how much you know until they know how much you care.”
    4. Apologize Well — When you find yourself faced with a confrontation, mistake or problem, the first words that come out of your mouth should be an acknowledgment and apology. Saying something as simple as “I’m sorry” can start to turn a negative situation around. A clear, sincere apology at the beginning of a conversation does two things. First, it positively kicks off the process of fixing a problem. Second, it helps restore the customer’s confidence.
    5. Hold the Salt — The opposite of the heliotropic sun, as the book title implies, is salt. To “hold the salt” is about not always saying everything on your mind. It’s sometimes better to bite your tongue and say nothing rather than try to get the last word or emphasize a point that doesn’t really need to be emphasized.
    6. Don’t Be a Complexifier — I’ve always believed that part of my success is simplifying the complicated. I recently wrote an article about how to make your business simple. Simplicity usually makes things better. Complex processes make it hard for customers and employees. Be easy, convenient and simple to do business with!
    7. Speak Fluent Gratitude — This is the perfect one to end on. Expressing appreciation to others is powerful. Dr. Cohen shared research that shows “cultivating gratitude makes you and the people around you feel better.” I love people who have an attitude of gratitude. And this is also an opportunity to express my gratitude to you for taking the time to read and share this article! Thank you!

    .

    This article originally appeared on Forbes.com

    Image Credits: Shep Hyken

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Let Yourself Draw Inspiration from Others

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Let Yourself Draw Inspiration from Others

GUEST POST from Mike Shipulski

When you try something new, check to see who has done something similar. Decompose their design approach. What were they trying to achieve? What outcome were they looking for? Who were their target customers? Do this for at least three existing designs – three real examples that are for sale today.

Here’s a rule to live by: When trying something new, don’t start from scratch.

What you are trying to achieve is unique, but has some commonality with existing solutions. The outcome you are looking for is unique, but it’s similar to outcomes others have tried to achieve. Your target customers are unique, but some of their characteristics are similar to the customers of the solutions you’ll decompose.

Here’s another rule: There are no “clean sheet” sheet designs, so don’t try to make one.

There was an old game show called Name That Tune, where contestants would try to guess the name of a song by hearing just a few notes. The player wins when they can name the tune with the *fewest* notes. And it’s the same with new designs – you want to provide a novel customer experience using the fewest new notes.

A rule: Reuse what you can, until you can’t.

Because the customer is the one who decides if your new offering offers them new value, the novel elements of your design don’t have to look drastically different in a side-by-side comparison way. But the novel elements of your offering do have to make a significant difference in the customer’s life. With that said, however, it can be helpful if the design element responsible for the novel goodness is visually different from the existing alternatives. But if that’s not the case, you can add a non-functional element to the novelty-generating element to make it visible to the customer. For example, you could add color, or some type of fingerprint, to the novel element of the design so that customers can see what creates the novelty for them. Then, of course, you market the heck out of the new color or fingerprint.

A rule: It’s better to make a difference in a customer’s life than, well, anything else.

Don’t be shy about learning from what other companies have done well. That’s not to say you should violate their patents, but it’s a compliment when you adopt some of their best stuff. Learn from them and twist it. Understand what they did and abstract it. See the best in two designs and combine them. See the goodness in one domain and bring it to another.

Doing something for the first time is difficult, why not get inspiration from others and make it easier?

Image credit: Unsplash

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When Innovation Becomes Magic

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When Innovation Becomes Magic

GUEST POST from Pete Foley

Arthur C Clarke’s 3rd Law famously stated:

“Any sufficiently advanced technology is indistinguishable from magic”

In other words, if the technology of an advanced civilization is so far beyond comprehension, it appears magical to a less advanced one. This could take the form of a human encounter with a highly advanced extraterrestrial civilization, how current technology might be viewed by historical figures, or encounters between human cultures with different levels of scientific and technological knowledge.

Clarke’s law implicitly assumed that knowledge within a society is sufficiently democratized that we never view technology within a civilization as ‘magic’.  But a combination of specialization, rapid advancements in technology, and a highly stratified society means this is changing.  Generative AI, Blockchain and various forms of automation are all ‘everyday magic’ that we increasingly use, but mostly with little more than an illusion of understanding around how they work.  More technological leaps are on the horizon, and as innovation accelerates exponentially, we are all going to have to navigate a world that looks and feels increasingly magical.   Knowing how to do this effectively is going to become an increasingly important skill for us all.  

The Magic Behind the Curtain:  So what’s the problem? Why do we need to understand the ‘magic’ behind the curtain, as long as we can operate the interface, and reap the benefits?  After all, most of us use phones, computers, cars, or take medicines without really understanding how they work.  We rely on experts to guide us, and use interfaces that help us navigate complex technology without a need for deep understanding of what goes on behind the curtain.

It’s a nuanced question.  Take a car as an analogy.  We certainly don’t need to know how to build one in order to use one.  But we do need to know how to operate it and understand what it’s performance limitations are.  It also helps to have at least some basic knowledge of how it works; enough to change a tire on a remote road, or to have some concept of basic mechanics to minimize the potential of being ripped off by a rogue mechanic.  In a nutshell, the more we understand it, the more efficiently, safely and economically we leverage it.  It’s a similar situation with medicine.  It is certainly possible to defer all of our healthcare decisions to a physician.  But people who partner with their doctors, and become advocates for their own health generally have superior outcomes, are less likely to die from unintended contraindications, and typically pay less for healthcare.  And this is not trivial.  The third leading cause of death in Europe behind cancer and heart disease are issues associated with prescription medications.  We don’t need to know everything to use a tool, but in most cases, the more we know the better

The Speed/Knowledge Trade-Off:  With new, increasingly complex technologies coming at us in waves, it’s becoming increasing challenging to make sense of what’s ‘behind the curtain’. This has the potential for costly mistakes.  But delaying embracing technology until we fully understand it can come with serious opportunity costs.  Adopt too early, and we risk getting it wrong, too late and we ‘miss the bus’.  How many people who invested in crypto currency or NFT’s really understood what they were doing?  And how many of those have lost on those deals, often to the benefit of those with deeper knowledge?  That isn’t to in anyway suggest that those who are knowledgeable in those fields deliberately exploit those who aren’t, but markets tend to reward those who know, and punish those who don’t.    

The AI Oracle:  The recent rise of Generative AI has many people treating it essentially as an oracle.  We ask it a question, and it ‘magically’ spits out an answer in a very convincing and sharable format.  Few of us understand the basics of how it does this, let alone the details or limitations. We may not call it magic, but we often treat it as such.  We really have little choice; as we lack sufficient understanding to apply quality critical thinking to what we are told, so have to take answers on trust.  That would be brilliant if AI was foolproof.  But while it is certainly right a lot of the time, it does make mistakes, often quite embarrassing ones. . For example, Google’s BARD incorrectly claimed the James Webb Space Telescope had taken the first photo of a planet outside our solar system, which led to panic selling of parent company Alphabet’s stock.  Generative AI is a superb innovation, but its current iterations are far from perfect.  They are limited by the data bases they are fed on, are extremely poor at spotting their own mistakes, can be manipulated by the choice of data sets they are trained on, and they lack the underlying framework of understanding that is essential for critical thinking or for making analogical connections.  I’m sure that we’ll eventually solve these issues, either with iterations of current tech, or via integration of new technology platforms.  But until we do, we have a brilliant, but still flawed tool.  It’s mostly right, is perfect for quickly answering a lot of questions, but its biggest vulnerability is that most users have pretty limited capability to understand when it’s wrong.

Technology Blind Spots: That of course is the Achilles Heel, or blind spot and a dilemma. If an answer is wrong, and we act on it without realizing, it’s potentially trouble. But if we know the answer, we didn’t really need to ask the AI. Of course, it’s more nuanced than that.  Just getting the right answer is not always enough, as the causal understanding that we pick up by solving a problem ourselves can also be important.  It helps us to spot obvious errors, but also helps to generate memory, experience, problem solving skills, buy-in, and belief in an idea.  Procedural and associative memory is encoded differently to answers, and mechanistic understanding helps us to reapply insights and make analogies. 

Need for Causal Understanding.  Belief and buy-in can be particularly important. Different people respond to a lack of ‘internal’ understanding in different ways.  Some shy away from the unknown and avoid or oppose what they don’t understand. Others embrace it, and trust the experts.  There’s really no right or wrong in this.  Science is a mixture of both approaches it stands on the shoulders of giants, but advances based on challenging existing theories.  Good scientists are both data driven and skeptical.  But in some cases skepticism based on lack of causal understanding can be a huge barrier to adoption. It has contributed to many of the debates we see today around technology adoption, including genetically engineered foods, efficacy of certain pharmaceuticals, environmental contaminants, nutrition, vaccinations, and during Covid, RNA vaccines and even masks.  Even extremely smart people can make poor decisions because of a lack of causal understanding.  In 2003, Steve Jobs was advised by his physicians to undergo immediately surgery for a rare form of pancreatic cancer.  Instead he delayed the procedure for nine months and attempted to treat himself with alternative medicine, a decision that very likely cut his life tragically short.

What Should We Do?  We need to embrace new tools and opportunities, but we need to do so with our eyes open.   Loss aversion, and the fear of losing out is a very powerful motivator of human behavior, and so an important driver in the adoption of new technology.  But it can be costly. A lot of people lost out with crypto and NFT’s because they had a fairly concrete idea of what they could miss out on if they didn’t engage, but a much less defined idea of the risk, because they didn’t deeply understand the system. Ironically, in this case, our loss aversion bias caused a significant number of people to lose out!

Similarly with AI, a lot of people are embracing it enthusiastically, in part because they are afraid of being left behind.  That is probably right, but it’s important to balance this enthusiasm with an understanding of its potential limitations.  We may not need to know how to build a car, but it really helps to know how to steer and when to apply the brakes .   Knowing how to ask an AI questions, and when to double check answers are both going to be critical skills.  For big decisions, ‘second opinions’ are going to become extremely important.   And the human ability to interpret answers through a filter of nuance, critical thinking, different perspectives, analogy and appropriate skepticism is going to be a critical element in fully leveraging AI technology, at least for now. 

Today AI is still a tool, not an oracle. It augments our intelligence, but for complex, important or nuanced decisions or information retrieval, I’d be wary of sitting back and letting it replace us.  Its ability to process data in quantity is certainly superior to any human, but we still need humans to interpret, challenge and integrate information.  The winners of this iteration of AI technology will be those who become highly skilled at walking that line, and who are good at managing the trade off between speed and accuracy using AI as a tool.  The good news is that we are naturally good at this, it’s a critical function of the human brain, embodied in the way it balances Kahneman’s System 1 and System 2 thinking. Future iterations may not need us, but for now AI is a powerful partner and tool, but not a replacement

Image credit: Pixabay

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Top 10 Human-Centered Change & Innovation Articles of March 2023

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Top 10 Human-Centered Change & Innovation Articles of March 2023Drum 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 March’s ten most popular innovation posts:

  1. Taking Care of Yourself is Not Impossible — by Mike Shipulski

  2. Rise of the Prompt Engineer — by Art Inteligencia

  3. A Guide to Effective Brainstorming — by Diana Porumboiu

  4. What Disruptive Innovation Really Is — by Geoffrey A. Moore

  5. The 6 Building Blocks of Great Teams — by David Burkus

  6. Take Charge of Your Mind to Reclaim Your Potential — by Janet Sernack

  7. Ten Reasons You Must Deliver Amazing Customer Experiences — by Shep Hyken

  8. Deciding You Have Enough Opens Up New Frontiers — by Mike Shipulski

  9. The AI Apocalypse is Here – 3 Reasons You Should Celebrate! — by Robyn Bolton

  10. Artificial Intelligence is Forcing Us to Answer Some Very Human Questions — by Greg Satell

BONUS – Here are five more strong articles published in February 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!

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 three years:

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Top 10 Human-Centered Change & Innovation Articles of January 2023

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Top 10 Human-Centered Change & Innovation Articles of January 2023Drum 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 January’s ten most popular innovation posts:

  1. Top 40 Innovation Bloggers of 2022 — Curated by Braden Kelley

  2. Back to Basics: The Innovation Alphabet — by Robyn Bolton

  3. 99.7% of Innovation Processes Miss These 3 Essential Steps — by Robyn Bolton

  4. Top 100 Innovation and Transformation Articles of 2022 — Curated by Braden Kelley

  5. Ten Ways to Make Time for Innovation — by Nick Jain

  6. Agility is the 2023 Success Factor — by Soren Kaplan

  7. Five Questions All Leaders Should Always Be Asking — by David Burkus

  8. 23 Ways in 2023 to Create Amazing Experiences — by Shep Hyken

  9. Startups Must Be Where Their Customers Are — by Steve Blank

  10. Will CHATgpt make us more or less innovative? — by Pete Foley

BONUS – Here are five more strong articles published in December 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!

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 three years:

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.






Will CHATgpt make us more or less innovative?

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Will CHATgpt make us more or less innovative?

GUEST POST from Pete Foley

The rapid emergence of increasingly sophisticated ‘AI ‘ programs such as CHATgpt will profoundly impact our world in many ways. That will inevitably include Innovation, especially the front end. But will it ultimately help or hurt us? Better access to information should be a huge benefit, and my intuition was to dive in and take full advantage. I still think it has enormous upside, but I also think it needs to be treated with care. At this point at least, it’s still a tool, not an oracle. It’s an excellent source for tapping existing information, but it’s (not yet) a source of new ideas. As with any tool, those who understand deeply how it works, its benefits and its limitations, will get the most from it. And those who use it wrongly could end up doing more harm than good. So below I’ve mapped out a few pros and cons that I see. It’s new, and like everybody else, I’m on a learning curve, so would welcome any and all thoughts on these pros and cons:

What is Innovation?

First a bit of a sidebar. To understand how to use a tool, I at least need to have a reasonably clear of what goals I want it to help me achieve. Obviously ‘what is innovation’ is a somewhat debatable topic, but my working model is that the front end of innovation typically involves taking existing knowledge or technology, and combining it in new, useful ways, or in new contexts, to create something that is new, useful and ideally understandable and accessible. This requires deep knowledge, curiosity and the ability to reframe problems to find new uses of existing assets. A recent illustrative example is Oculus Rift, an innovation that helped to make virtual reality accessible by combining fairly mundane components including a mobile phone screen and a tracking sensor and ski glasses into something new. But innovation comes in many forms, and can also involve serendipity and keen observation, as in Alexander Fleming’s original discovery of penicillin. But even this requires deep domain knowledge to spot the opportunity and reframing undesirable mold into a (very) useful pharmaceutical. So, my start-point is which parts of this can CHATgpt help with?

Another sidebar is that innovation is of course far more than simply discovery or a Eureka moment. Turning an idea into a viable product or service usually requires considerable work, with the development of penicillin being a case in point. I’ve no doubt that CHATgpt and its inevitable ‘progeny’ will be of considerable help in that part of the process too.   But for starters I’ve focused on what it brings to the discovery phase, and the generation of big, game changing ideas.

First the Pros:

1. Staying Current: We all have to strike a balance between keeping up with developments in our own fields, and trying to come up with new ideas. The sheer volume of new information, especially in developing fields, means that keeping pace with even our own area of expertise has become challenging. But spend too much time just keeping up, and we become followers, not innovators, so we have to carve out time to also stretch existing knowledge. But if we don’t get the balance right, and fail to stay current, we risk get leapfrogged by those who more diligently track the latest discoveries. Simultaneous invention has been pervasive at least since the development of calculus, as one discovery often signposts and lays the path for the next. So fail to stay on top of our field, and we potentially miss a relatively easy step to the next big idea. CHATgpt can become an extremely efficient tool for tracking advances without getting buried in them.

2. Pushing Outside of our Comfort Zone: Breakthrough innovation almost by definition requires us to step beyond the boundaries of our existing knowledge. Whether we are Dyson stealing filtration technology from a sawmill for his unique ‘filterless’ vacuum cleaner, physicians combining stem cell innovation with tech to create rejection resistant artificial organs, or the Oculus tech mentioned above, innovation almost always requires tapping resources from outside of the established field. If we don’t do this, then we not only tend towards incremental ideas, but also tend to stay in lock step with other experts in our field. This becomes increasingly the case as an area matures, low hanging fruit is exhausted, and domain knowledge becomes somewhat commoditized. CHATgpt simply allows us to explore beyond our field far more efficiently than we’ve ever been able to before. And as it or related tech evolves, it will inevitably enable ever more sophisticated search. From my experience it already enables some degree of analogous search if you are thoughtful about how to frame questions, thus allowing us to more effectively expand searches for existing solutions to problems that lie beyond the obvious. That is potentially really exciting.

Some Possible Cons:

1. Going Down the Rabbit Hole: CHATgpt is crack cocaine for the curious. Mea culpa, this has probably been the most time consuming blog I’ve ever written. Answers inevitably lead to more questions, and it’s almost impossible to resist playing well beyond the specific goals I initially have. It’s fascinating, it’s fun, you learn a lot of stuff you didn’t know, but I at least struggle with discipline and focus when using it. Hopefully that will wear off, and I will find a balance that uses it efficiently.

2. The Illusion of Understanding: This is a bit more subtle, but a topic inevitably enhances our understanding of it. The act of asking questions is as much a part of learning as reading answers, and often requires deep mechanistic understanding. CHATgpa helps us probe faster, and its explanations may help us to understand concepts more quickly. But it also risks the illusion of understanding. When the heavy loading of searching is shifted away from us, we get quick answers, but may also miss out on the deeper mechanistic understanding we’d have gleaned if we’d been forced to work a bit harder. And that deeper understanding can be critical when we are trying to integrate superficially different domains as part of the innovation process. For example, knowing that we can use a patient’s stem cells to minimize rejection of an artificial organ is quite different from understanding how the immune system differentiates between its own and other stem cells. The risk is that sophisticated search engines will do more heavy lifting, allow us to move faster, but also result in a more superficial understanding, which reduces our ability to spot roadblocks early, or solve problems as we move to the back end of innovation, and reduce an idea to practice.

3. Eureka Moment: That’s the ‘conscious’ watch out, but there is also an unconscious one. It’s no secret that quite often our biggest ideas come when we are not actually trying. Archimedes had his Eureka moment in the bath, and many of my better ideas come when I least expect them, perhaps in the shower, when I first wake up, or am out having dinner. The neuroscience of creativity helps explain this, in that the restructuring of problems that leads to new insight and the integration of ideas works mostly unconsciously, and when we are not consciously focused on a problem. It’s analogous to the ‘tip of the tongue’ effect, where the harder we try to remember something, the harder it gets, but then comes to us later when we are not trying. But the key for the Eureka moment is that we need sufficiently deep knowledge for those integrations to occur. If CHATgpt increases the illusion of understanding, we could see less of those Eureka moments, and the ‘obvious in hindsight ideas’ they create.

Conclusion

I think that ultimately innovation will be accelerated by CHATgpt and what follows, perhaps quite dramatically. But I also think that we as innovators need to try and peel back the layers and understand as much as we can about these tools, as there is potential for us to trip up. We need to constantly reinvent the way we interact with them, leverage them as sophisticated innovation tools, but avoid them becoming oracles. We also need to ensure that we, and future generations use them to extend our thinking skill set, but not become a proxy for it. The calculator has in some ways made us all mathematical geniuses, but in other ways has reduced large swathes of the population’s ability to do basic math. We need to be careful that CHATgpt doesn’t do the same for our need for cognition, and deep mechanistic and/or critical thinking.

Image credit: Pixabay

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Psychology of Brand Loyalty and Its Implications for Innovation

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Psychology of Brand Loyalty and Its Implications for Innovation

GUEST POST from Art Inteligencia

In today’s competitive business landscape, building and maintaining brand loyalty is more crucial than ever before. For organizations, understanding the psychology behind why consumers remain loyal to certain brands can provide valuable insights for driving innovation and staying ahead of the curve. This article explores the psychology of brand loyalty, shedding light on its deeper aspects and showcasing two compelling case studies that highlight the implications for innovation.

1. The Emotional Connection:

One crucial factor that drives brand loyalty is the emotional connection consumers develop with a brand. People often choose and remain loyal to brands that align with their values, beliefs, and personal identity. Companies that successfully tap into this psychological aspect connect with their customers on a deeper level.

Case Study 1: Apple Inc.

Apple’s success can be largely attributed to the emotional connection it has forged with its user base. By creating a brand identity centered around innovation, creativity, and a user-friendly experience, Apple has cultivated a tribe of dedicated followers known as “Apple enthusiasts.” These individuals exhibit strong brand loyalty, continuously investing in Apple’s products, and actively advocating for the brand.

Implication for Innovation:

Understanding the emotional connection customers seek, Apple continues to innovate by continually pushing the boundaries of design, aesthetics, and technology. Whether it’s the introduction of new product lines or enhancing the user experience, Apple’s unwavering commitment to maintaining its brand loyalty has driven its innovation strategies.

2. Creating a Sense of Community:

Brand loyalty can also stem from consumers’ innate desire for social connection. When individuals connect with a brand that fosters a strong sense of community, their loyalty intensifies. Such communities can create a shared identity, fostering a space where consumers feel understood, valued, and engaged.

Case Study 2: Peloton Interactive Inc.

Peloton’s rise in popularity showcases the power of creating a community-driven brand. Through its connected fitness platform, Peloton has brought people together, providing an interactive fitness experience from the comfort of their homes. Users engage in real-time classes, share achievements and milestones, and develop connections with instructors and fellow riders.

Implication for Innovation:

Recognizing the importance of a community-centric approach, Peloton constantly innovates to enhance the sense of connection among its users. By introducing features like group rides, leaderboards, and social challenges, Peloton drives brand loyalty through virtual camaraderie and shared goals.

The Synergy of Brand Loyalty and Innovation:

Brand loyalty and innovation are mutually reinforcing. Innovation contributes to brand loyalty by delivering superior products, services, and experiences that exceed customer expectations. In turn, brand loyalty provides organizations with the platform and customer base necessary to take risks and innovate further.

Conclusion

Understanding the psychology behind brand loyalty allows organizations to forge meaningful connections, create a strong sense of community, and drive innovation. By delving into emotional connections and fostering communities, brands can cultivate loyal customer bases that not only stay committed but also provide valuable feedback and act as brand advocates. As human-centered design professionals, comprehending the psychology of brand loyalty equips us to fuel innovation and stay ahead in a dynamic and competitive marketplace.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: misterinnovation.com

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