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I used to tell people we use research to INFORM decisions and not MAKE decisions.

Then.

I told people we use numbers to INFORM decisions and not MAKE decisions.

Then.

I told people we use data to INFORM decisions and not MAKE decisions.

Now.

I tell people we use algorithms to INFORM decisions and not MAKE decisions.

Me

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“An idea of working based on three pillars: science, insight and faith. Science because I’m a social scientist by training. I believe in data, robustness of information, making sure you’re on the right track. Insight because if you’re not able to draw insights from research, you’re not a strategist, just someone observing the data. And faith because you never know what’s going to work, so you always need a bit of faith to get everyone started.”

Laura Chiavone

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I believe great companies have one common infrastructure characteristic: culture. Good companies can be grounded in systems, processes, operations, etc, however, the step up to ‘great’ demands a culture (which is always implemented by people) to elevate the ‘infrastructure aspects. To be clear. “Culture” is not some ‘thing’, or values, or some nebulous feeling, it is an emergent consequence of how people interact with each other within a business. It is not what someone does or doesn’t do, it is what happens when people do things with each other. I thought of this because Mike Walsh has a new book, The Algorithm Leader, which suggests that the most successful companies of the future will support/augment/enhance that culture infrastructure – with algorithms. Now. Before anyone defaults into thinking this translates into “empty soul, technology order taker” company, or even holocracy (ponder how polar opposites could be relevant to the algorithm topic), let me share some thoughts on how I believe the thinking suggests structural value creation lift: for business & humans. To me this will occur through a balance of stability (knowledge infrastructure), uncertainty (quests versus missions) & understanding of Antifragility (selective redundancy maximizing untidy opportunities).

Let me pose some thoughts on the relationship between algorithms and antifragility upfront.

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“It is optionality that makes things work & grow.” AntiFragile

Maybe algorithms shouldn’t provide answers, but options. Maybe, more importantly, we become a little less comfortable with the need for construct and more comfortable with using algorithms as dynamic application of ‘movable construct’ at the right time & place.

“The antifragility of some comes necessarily at the fragility of others. In a system the sacrifice of some units – fragile units or people – are often necessary for the well-being of other units or the whole.” AntiFragile

Maybe algorithms should evaluate tradeoffs, fragility versus antifragility & well-being factors (of units & whole).

“The crux of complex systems , those with interacting parts, is that they convey information to these component parts through stressors.” AntiFragile

Maybe algorithms should not highlight solutions, but rather stressors or what Donella Meadows called ‘leverage points.’.

“There is a category of things that we can call half invented, and taking the half invented into the invented is often the real breakthrough.” AntiFragile

Maybe algorithms shouldn’t seek new innovations but rather ‘half invented’ ideas ripe for innovation maturity.

“Meaningful progress is non-linear.” How To Lead a Quest

Algorithms should enable an organization to identify progress paths to explore and discover rather than simply meet the needs of present identified ‘paths’ of progress or solve present identified issues & vulnerabilities.

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Full disclosure on my business beliefs. Throughout my career I have always felt comfortable by making the less certain decisions just certain enough that someone would go “well, it seems riskier, but, if you own it, go do it.” I say all that because I believe all Future of Work discussion should be grounded on the relationship between certainty & uncertainty – for the business, the people within the business organization and people’s minds/attitudes.

Algorithm leadership.

Most people want certainty therefore they let research make decisions, use numbers to make decisions, show data to make decisions and, increasingly, will suggest algorithms make decisions.

This is just a different type of efficiency couched in efficient operations. It will be called “efficient decision making.” The problem is this efficiency is just an attempt to strip a decision of uncertainty and, well, the best, most effective; decisions always carry along some burden of uncertainty.

What made me think about this? I just finished rereading AntiFragile (Nassim Taleb) and reread Mike Walsh’s first chapter of his new book The Algorithm Leader.

The former is about figuring out how to maximize from disorder or uncertainty while the latter is not becoming too dependent upon seemingly ‘certainty.’

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“The future of companies, regardless of size, will be shaped by algorithms.”

Mike Walsh

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Ultimately, it will be humans who use the shapes created by algorithms to assess options, evaluate antifragile components and navigate asymmetrical uncertainty.

It within this dynamic environment in which we should note business is inherently fragile. HBR once said “business is a quivering mass of vulnerabilities.” I say that because as a pendulum swings one way it will inevitably want to swing the other way. We inherently feel the fragile pendulum swing and start seeking to build ‘un-natural’ antifragile aspects to create a sense of antifragility. Aspects like systems, process, rules, KPIs, data/dashboards and, yes, algorithms. Depending on how fragile we see, or feel, the business to be the more likely we use the created mechanisms to ‘tell us what to do.’ We must fight against those instincts.

Frankly, this is where generations DO become relevant in discussing business. Older workers, 50somethings, can be an impediment by seeing past experience as ‘certainty’ . On the other hand, some 50somethings can actually be a bridge between some certainty-type learnings and younger people who are more comfortable with disorder (but they don’t necessarily have the expertise do discern the best bridges between certainty & uncertainty).

Here is what I do know. Business people inherently abhor risk, business organizations inherently gravitate toward the ‘safest’ and numbers, research, data & algorithms look like life rafts in a risky, safe seeking business world. That said. I also know progress is rarely found without some risk and is often found on ‘not-the-safest’ path. Algorithms create a false sense of ‘right thing to do.’ any leader who leans on algorithms too much isn’t leading. Period.

Uncertainty leadership.

For this I lean in on How to Lead a Quest by Dr. Jason Fox. In times of uncertainty a business does not need business ‘heroes’ but rather people aligned on a quest and leaders who embrace the uncertainty of a complex interconnected multi-dimensional business world.

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“You must learn to be still in the midst of activity and to be vibrantly alive in repose.”

Indira Ghandi

—-

Contrary to popular belief I would suggest a highly successful algorithmic leader is likely a 50something who has navigated research, then data, the ‘dictating’ decisions challenge gauntlet, & who were more likely to see how seemingly unrelated disparate fragments could be coalesced into decisions and futures that the numbers/data didn’t completely support, but also did not completely discount. That was a long winded way to introduce the idea of “data decipherers”. This type of leadership invaluable to an organization more & more steeped in numbers, dashboards, data & algorithms.

Jason Fox calls this “shining a light on the path before us.” Leadership will not use algorithms for ‘squinting into the future but rather to identify the stepping stones in a sea of uncertainty. They will offer people moments of some certainty without promising a certain future nor even promising steady progress organizationally. It will be more about uncovering options, making choices to alleviate stressors, so that teams can breakthrough while others provide the organization with the redundancies to protect an organization from uncertainty vulnerabilities.

Here is what I do know. Psychologically businesses will arc toward a belief algorithms will provide an increased tidiness and symmetry to business. that is a false sense of tidiness. Business will become increasingly untidy, the paths will become increasingly complex, therefore business will become increasingly uncertain with regard to the best, and proper steps, necessary for progress. Pragmatically business will need more, and better, leadership comfortable with uncertainty despite more numbers, data and algorithms.

Antifragile leadership.

Crisis, disaster resolution is rarely about resources available, but rather people* availability.

• * ‘people availability’: this is all of physical energy, skills and mental energy combined.

Here I lean in Taleb’s AntiFragile. We tend to build redundancies incorrectly, don’t assume for disorder well & only enhance fragility in plans. We too often see AntiFragile as a “leadership concept” when in reality it is best absorbed by agile/adaptable teams.

Risk management almost always solely focuses on resources necessary to sustain, and manage, foreseen crisis. As Taleb points out the largest flaw in that is most crisis do not look similar to ones on the past (they will have similarities but still be unique). In addition. Most organizations build in redundancy safety nets as, well, a net.  Because we dislike fragility so much we start building in antifragile everywhere. We tend to think of leadership as “what if” redundancy design. Antifragile leadership should be more ‘aligning resources to meet different scenarios.” Some people would call this ‘agile.’ I would not. I would simply call this pivoting (I am old school) based on the Law of the Situation. Great businesses have always been able to pivot to meet market challenges and opportunities. This is pivoting – no more, no less.

This is where I would view using algorithms a little differently than other people. Algorithms tend to look at opportunities when I believe they could be better used to identify stress points and stressors. Most good leaders are best as problems solvers or maybe better said “removers of obstacles to opportunistic behavior.’ (that doesn’t mean they don’t optimize existing operations/situations just that where good leaders get paid the big bucks is getting moments/situations unstuck). I would also argue identifying stressors permits smarter experimenting and tinkering.

Here is what I do know. Algorithms, used properly, permit people to stop just optimizing for the present and start attempting to optimizing the future. Yes. It may mean being less efficient in the short term (sometimes), but, done well, will create a more effective long term construct.

Conclusion:

I think the smart businesses of the future will be “directed to act” by algorithms, but not managed by. The latter demands acceptance of algorithm as qualified to make us to do something behaviorally, the former demands we accept algorithms as something that ‘informs’ our doing. Somewhere in between is the decision of how much we, people, are accountable for thinking. Algorithms inherently encourage us to believe business is not best when it is random. Yet. The best businesses resist the urge to suppress randomness and permit people to be more accountable for some untidy decisions with some untidy outcomes.

All businesses will exist, in some form or fashion, grounded in algorithms. I am fairly sure that’s a given. The challenge will be to not get consumed by algorithms.

To realize algorithms do not give answers, but outline options.

To realize algorithms don’t define redundancies, but rather where and when to apply redundancy resources (therefore help to define how to create proper redundancies).

To realize algorithms don’t necessarily create innovation opportunities but rather find opportunities to ‘reinvent’ ideas.

And.

To realize algorithms will not replace people, but rather augment minds and skills OF people. Ponder.

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“Don’t be afraid to write lots of garbage (but also don’t throw any of it away). Have a very large storage system for all that garbage, because it’s only garbage in context. It may turn out to be a treasure in some other context you haven’t discovered yet.”

Courtney Balestier

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“It was the in-between time, before day leaves and night comes, a time I’ve never been partial to because of the sadness that lingers in the space between going and coming.”

The Secret Life of Bees, Sue Monk Kidd

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Thinking has a lot of garbage and a lot of in-between time. Unfortunately, today’s world has little use for what is judged garbage in the present, or even the past, and even less use for “in-between” putting the highest value on “useful now.”

This makes the world really really difficult for most thinkers because, if they are honest, they get a lot wrong initially and most thinking may have seeds of smartness and truth initially, but other than that, well, a lot is garbage. I call it “not quite right” thinking. Taleb called them “half invented ideas.”  The ideas that didn’t get traction immediately and, well, if we are honest, business life and our own spans of attention tend to discard an idea if it doesn’t show immediate possibilities or success. But if you keep the fragments of good ideas around, and twist them around a bit every once in a while, like a kaleidoscope eventually they can come together in a vivid image. Voila, your garbage has turned into non garbage. Your half invented becomes a useful invention.

Which leads me to suggest there is a relationship between useful garbage and speed – as in play, pause, rewind & fast forward.

The truth is that every good self-aware thinker has a panel in their head with a play, pause, rewind and fast forward button. They have the ability to see things in real time, i.e., what has occurred up to that point and, in some way, can envision the ripples of what happens from there. Within that ability they decide to fast forward, or pause, or continue playing at the same speed or even decide to rewind a little. They see reality and decide how to best take advantage of it. I would suggest the best garbage users have this ability.

That said. Some thinkers have one speed. These are ‘the bull in china shop’ asshats who only know forward at some fast speed bludgeoning and blustering their way forward. Then there are others like golf carts steadily chugging along at steady long play. Idea management, i.e., sifting through the garbage, demands a bit of all and each and nuanced use.

Well. Today’s world is structurally hostile to nuance. Subtlety not only doesn’t sell because it invokes that wretched inbetween ‘space’ in which others are more than willing to place something. It is easy to go one speed <or just stop when you get tired>. It takes touch and nuance to pause at the right time, rewind accordingly, fast forward through some difficulties or to take advantage of windows of opportunity or, well, just keep playing <which is sometime tougher than what you would think>.

To be a consistently good thinker is not about maintaining one speed, but rather maintaining a consistent sense for how to adjust pacing accordingly and when, and where, to pick through the garbage.

Which leads me to humility.

In today’s business world we like to have simple formulas and handbook guides. Pacing is more ‘feel’ and awareness and … well … yeah … some humility. I say humility because no matter how good a thinker you are and no matter how good your pacing is there will always be some issues <mostly because you get some things wrong>. Part of the ‘wrong’ portion is you inevitably leave some people behind and some ‘minds’ get a little scattered. And you have to get them back on track and aligned and sometimes you have to step up and show a little humility, admit some things are garbage, maybe even sift through other people’s garbage, and everyone resets when you do that, gives you another chance and get a little reenergized to pick up their bags and hit the road with you again.

In the end, all garbage has value. It may not all turn into a treasure someday, but it all shapes perspective. And perspective is imperative in the in-between time when outlines of some really important things can be a bit vague. Sometimes the garbage is what gets you out of the in-between. And maybe that is the most important point I have shared today. Ponder.

Analog – June 1962 – cover artist – John Schoenherr

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 “The single most important thing that could be done would be to substitute reasonably accurate positive images of the future for the depressing images that now prevail, especially in the Advanced Capitalist nations.”

futurist Herman Kahn in the 1970s

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It is just as deterministic to say “if we build social media, the world will be a more connected place” as it is to say “social media will destroy democracy.”

Danah Boyd

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“We saw Cyndi Lauper convincing a gentleman in a suit to put down his newspaper and dance, I saw a world of possibility, one in which adulthood could be fun, with surprise waiting around every corner.”

Shane O’Neil on the 1980’s & 90’s

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I almost called this ‘refinding technological optimism.’ Okay. Maybe it is more about anti-technological dystopia. I am not suggesting we be utopian, just that I question why we should ditch optimism. I thought about this in a conversation with Faris Yakob as we pondered our possibly naïve optimism about technology in the early 2000’s. Anyway. Two of the books I consistently pluck off my shelf to remind myself that technology dystopia has not always been the norm: The Cluetrain Manifesto and anything by Jaron Lanier. And while I imagine the Cluetrain authors may suggest that they were naively optimistic, I don’t agree with them. In those heady days technology was going to offer us many of the things that would solve, or resolve, many of the societal issues at hand. And technology, for its part, has held up its end of the bargain. Where things go a bit awry is with humans. And if you agree with that, fundamentally, anything humans make can be unmade. Just because some of the Cluetrain and Lanier positive possibilities have not occurred, doesn’t mean they cannot.

But let’s get to the optimistic part.

The roots of technological optimism arise way before the internet and computer technology. Its roots are grounded in technology (a) better utilizing resources against growing demand and (b) easing some of the societal issues through more efficient productivity/use of human time. Technological growth, in the minds of the optimists, meant technological advance where humanity got more output per unit of input – rather than simply more of an old technology. The optimism gained some momentum with the idea of ‘exponential.’ Technology was to provide exponential benefits rather than a more plodding additive or even multiplicative. In other words, today’s limits would look silly in the future because of the accumulation of a seemingly endless amount of breakthroughs. For the most part, this happened. But. We were also offered a blueprint for what could go wrong at this time. Toffler and McLuhan outlined the cognitive issues (human limits) and Anderson outlined the market issues in The Long Tail theory. Fragmentation in the market, profited exponentially, and humans, cognitively, didn’t quite profit as much. The exponentiality was indifferent to symmetry and asymmetry can be a motherfucker to humans and their minds.

But let’s get back to optimism. Distorted market incentives are solvable, businesses and institutions structured to exploit technology can be solved, even societal expectations and objectives can be solved. None of those things have anything to do with technology; they are human issues. That said. Constructive technological advances could enhance human solutions to those things. Technology, in the right hands, could even combat some of the negative features of existing technology.

To be clear, this optimism is not utopian (although I do believe we should do some more utopian thinking). This optimism is rooted in what we know and what we can actually do. To make a point, almost everyone who signed the AI “pause” letter could, if funded well, could develop technological solutions to much of what dystopians lose sleep over. I say that to suggest we should have technological optimism … as long as the right humans are involved in technology’s future. I imagine my grander point on that is technology has not failed us, we have failed technology. And within that we should find some optimism because no matter how bad people can be, good people have a gravitas that bad can never attain.

“In the long run, optimists shape the future.”

Kevin Kelly

Which leads me to shaping.

An optimist almost has to believe, in some form or fashion, that exponential technological growth will expand resources and minds ahead of exponentially increasing issues. This is a tough thought in today’s world because from most people’s perspective technology is an aggravating factor – amplifying all that is bad – rather than an expansive factor – amplifying possibilities and imagination to be mined. But once again, the problem isn’t the technology; its us (humans). The undesirable, aggravating characteristics, consequences of technology are reflections of humanness which many of us simply ignored or submerged under a variety of other things (results, altruism, etc.). Market forces are most typically a reflection of humanness. That is not to say technology doesn’t tweak our worst instincts, just that technology is equally a force for good and bad and only pursues what we want to pursue. The consequences are more us than it is ‘them’ (technology) so if we optimistically shape our technology we can shape a more optimistically good world.

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“I don’t think our goal should be to create conscious intelligent machines. Everything that makes a machine useful are generally the things that are not human, why do we need to create an emotional, unpredictable, volatile, machine and put it in charge of something mission critical. The whole point of machines is to do they can do the things we don’t trust humans to do consistently.”

Mike Walsh

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The fact of the matter is, McLuhan was right: “We shape our tools and then our tools shape us.” Technology is not just about things and devices; it is about processes and verbs and attitudes and people. You have to be a little careful about what technologies you adopt, because each technology is, broadly speaking, a way of doing things. Maybe we place optimism on top of these questions L.M. Sacasas suggests:

1. What sort of person will the use of this technology make of me?
2. What habits will the use of this technology instill?
3. How will the use of this technology affect my experience of time?
4. How will the use of this technology affect my experience of place?
5. How will the use of this technology affect how I relate to other people?
6. How will the use of this technology affect how I relate to the world around me?
7. What practices will the use of this technology cultivate?
8. What practices will the use of this technology displace?
9. What will the use of this technology encourage me to notice?
10. What will the use of this technology encourage me to ignore?

Which leads me to suggest technological optimism is about faith and craft.

To be optimistic is to believe in human ingenuity with no foreseeable limit. Technology can be crafted as an unending cascade of advancement. What this means is a belief that each advancement can not only eliminate the present technological issues, but also stretch the limits of what is currently possible. In its constant stretching both good, and bad, can occur but the good is constantly erasing the bad. Yeah. It’s an understanding that technology is both empowering/enabling and oppressive/constraining; often simultaneously. But within optimism is a rejection of a conclusion that the world is ugly and the people are bad. Optimism rejects dystopia as well as the status quo. I believe the status quo never invents the future, and vision, creativity and innovation crafts the future. Yeats is correct, the center cannot hold, so the center may be the status quo and who’s happy with that today? Instead of griping about what’s deplorable, it seems a discussion about the future would be much more interesting. We can wring our hands all we want, but there’s no going back, so what’s ahead?

“Well, that’s the universal law of technology, that it can be used for good or evil.”

Michio Kaku

“Ahead” technology discussions today careen between an anticipation of doom or deliverance. All of today’s technologists, while they craft for utility, power and profit, appear to have as their north star as rationality. Somewhere along the way the technologists lost the distant dreams and aspirations for a better world. Sadly, I believe this is a reflection of business and society in general (it is a tough time for dreamers these days). While tools could have been shaped to shape a better society and world, the tools were shaped – by human hands and minds – to serve financial objectives (which, obviously, is the easiest way to pay for the technology). So. While we should expect far more from our technological innovations then convenience and efficiency, or even cognitive survival, we do not. It gets a bit worse. We also demand deliverance from problems, even the problems that technology creates, from technology. Yeah. Technological growth clearly aggravates real human problems and it is silly to optimistically count on technological advance to solve all of them. Technology is a mixed blessing capable of producing undesirable as well as desirable consequences. The mixed consequences of technological development is an issue that becomes more critical the more technological advance entails risks with catastrophic potential. That said. There is only “ahead” and we should be focused on delivery (and deliverance from dystopia), and not doom.

Which leads me to why dystopia is so much easier than optimism.

Part of the issue is that technology has become a God-like tool for, well, everything to, well, everyone; not just technological optimists.  As Alan Turing said:

“(Turing) predicted in about 50 years time it will be possible to program computers to make them play the imitation game so well that an average interrogator will not have more than a 70% chance of making the right identification after five minutes of questioning. It is at that point we would start deeming a machine’s performance as intelligent.”

The truth is we are at the 70%, if not higher, now. But go on the internet and you can find all the tech nerds and philosophical thinkers adamantly stating all the ways a computer is not human and cannot mimic a human and, in fact, it is not intelligent. Well. The issue is the majority of the world are not tech nerds and philosophical thinkers. To the majority of THAT world the computer is intelligent. In fact (an aside to all the tech nerds and philosophical thinkers), that imitation technology is more easily understood than the tech nerds and philosophical thinkers.

What this puts us at is what complexity theory calls The Edge of Chaos. This refers to the exploration zone of complex systems where interesting things happen. In this zone systems are not so rigid that they cannot change at all, but not so chaotic that they immediately dissolve into useless disorder. The edge of chaos is the fertile ground for possibilities to emerge. It describes where we live in today’s world. It is from this space where optimists thrive and progress towards something better can thrive.

It is time to explore.

I believe there about the same number of neurons in the brain as there are a number of stars in universe. We have used technology to explore space, to explore the brain, to explore the body, to explore the capacity of humans. Technology is the ship which can carry us to the farthest parts of the universe. My real fear and pessimism reside not with technology, but with ourselves – human beings. We have met the enemy and it is us. The truth is technology simply amplifies all the worst things of human beings. I’m not speaking of evil, although it lurks in the depths of the Internet, I’m speaking more about conformity. The internet defines how things should look like and scores of people line up to conform to that likeness. The same thing occurs with ideas and, well, everything. We are imitation machines. More access to all this information and imagery and words just simply encourages us all to become average, i.e., to all become the same. At some point we will all look like each other, speak like each other, and even use all the same words. That is my fear. My optimism resides in the belief that people are not average, they do like to be distinct, and they like progress to something new and better. Yeah. All progress is grounded in some spectacular risk, some spectacular mistake, or some spectacular idea that encourages everybody to zig while everyone else is zagging. And my optimism also encompasses technology because technology mirrors humanness.

Which leads me to end with a thought Pamela McCorduck had: “this thinking machine amplifier would amplify these qualities as other as other as other machines have amplified the other capacities of our body.” The development of AI continues to promise to provide an extension of the human capacities we value most like, well, conversations and exchanges and connections:

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“The first markets were filled with people, not abstractions or statistical aggregates; they were the places where supply met demand with a firm handshake. Buyers and sellers looked each other in the eye, met, and connected. The first markets were places for exchange, where people came to buy what others had to sell — and to talk.

The first markets were filled with talk. Some of it was about goods and products. Some of it was news, opinion, and gossip. Little of it mattered to everyone; all of it engaged someone. There were often conversations about the work of hands: “Feel this knife. See how it fits your palm.” “The cotton in this shirt, where did it come from?” “Taste this apple. We won’t have them next week. If you like it you should take some today.” Some of these conversations ended in a sale, but don’t let that fool you. The sale was merely the exclamation mark at the end of the sentence.”

Cluetrain Manifesto

Of course, there are reasons to be concerned especially when pondering latency – where effects are manifested long after the initiation of their cause – coupled with irreversibility, or a resistance to correction. Or the zero-infinity characteristic which refers to effects that are extraordinarily unlikely to occur, but catastrophic if they do.

Look. I am certainly not suggesting gambling our future on an optimistic point of view, just that optimism can shape the future we want. And I believe optimism is actually the only way to forge our way to a better future. Let’s go explore. Ponder.

A Human Algorithm: Flynn Coleman

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“Their most hopeful vision of the future is centred around compassion not convenience, emotional not artificial intelligence. The path towards this vision seems to require little technical innovation; it demands simply that people care about people – an idea so laughably naïve, yet so radically transformative.”

Kai

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• Preface: apologies to all my technology friends because I am going to mangle some technology concepts to make some points.

With all the talk about ChatGPT (large language models), which seems to bleed into a larger technology angst discussion, I thought it may be important to remind everyone about, well, humans.

The one thing smart machines and humans have in common is choicemaking. From there the paths diverge – fairly significantly.

A major difference between humans and computers is that at any given moment people are not choosing among all possible steps. What this means is when humans think of possibilities or ‘desired futures’ they are not even close to making the optimal choices. Instead, we, people, typically lean in on a deeply nested hierarchy of ‘knowns’ in our minds which we recognize as ‘better’ paths, or stepping stones, toward the future we desire. These nested ‘knowns’ are typically bounded biases (self-sealing beliefs). The self-sealing beliefs issues gets compounded by the fact we tend to pursue short term goals, or more immediate gratification/results, rather than maximizing for the future. We may think we are, and we may even may make valiant attempts to do so, but we are inevitably constrained by those pesky nested beliefs and shorter term gratification.

Which leads me to smart machines.

Given enough data a smart machine can recognize your self-sealed beliefs (even the ones you may have submerged fairly deeply). From there it can manipulate your nested beliefs which inevitably changes your view of future possibilities. We all have these nested beliefs, often called heuristic thinking, and they do help us navigate shit. That said. Because they are so embedded it’s difficult for us to see let alone reshape ourselves, but a computer can – sometimes incrementally over time and sometimes in one fell swoop. As you can imagine, this can be very good, and it can be very bad. And that is where this whole thing gets tricky. While we all have personal preferences, computers simply have data and the knowledge to see your preferences – but not understand them or the reasoning behind them – and smart machines are built with the purpose to modify human preferences because, well, smart machines modify human experiences. Preference modification is a slippery slope. It can modify good and modify bad and, well, machines are machines and without some intuition they may mathematically steer a preference away from a more optimal path – specifically to you – simply because the machine has assessed it to be so. This gets compounded by, quoting Brian Christian, “when a computer guesses, it is alarmingly confident.” Look. Machines will most likely make preference modification more statistically optimal (even weighing a 51% probability in a binary way), but the truth is some of the best preference driven choices people make are the less obvious ones. So maybe what I am suggesting is that ‘always optimal’ leads to a less-than-optimal destination. Yeah. Imagine that if everyone did what the computer said the entire world inches a bit closer to the mean (average) and runs the risk of eliminating the soaring heights attained in the improbable. And, if humans are anything, they are improbable machines.

Which leads me to how smart machines are both smart and dumb.

Machines do have an ability to learn at a variety of levels. At one level is repetitive task automation where the machine has been taught how to perform a specific task reliably, but its knowledge cannot grow any further based on its experience or in response to changing conditions. This is a closed loop system and typically very affordable. At another level the computer is able to observe the effects of its performance or results of its analysis and make adjustments to what it “knows”, usually by experimenting with other possibilities that might perform better. This sounds good and it is good, however, it can’t question anything because it doesn’t really have the ability to assess context awareness and learning. It cannot really question anything beyond any of the inputs it has been told to consider in its optimization. This is also a closed loop system just broader than the first that I outlined – a little less affordable.

This closed loop is important because far too many people talk about AI as being some omniscient thing, i.e., an open loop all-knowledge-encompassing process. It can be, but mostly it can’t because of cost. I cannot tell you how many times I have talked with a software developer about an AI/algorithm-based idea and they have responded “that is a great idea, but I don’t know anyone who would have the budget to build it.” What this means is ‘closed loop’ is also ‘budget-manageable.’

Anyway. A smart machine will end up being good at pattern recognition (assuming it has a large enough data base) and will be bad at intuitive sense. For example, machines “see” items as a patchwork of lines and dots and ones and zeros from which they identify things that match what they have in their database. But they cannot easily identify the essence of what item is. And even if a machine is able to successfully match an object to an image in its database, a slight change in perspective can baffle the shit out of a smart machine.

Our brains, however, are quite capable of taking different perspectives and variations into account. Our brains are subconsciously performing trillions of calculations. Basically, artificial intelligence is trapped in a closed loop. That loop can very large like large language models, but however vast they appear, alas, they are a closed loop. Brains, on the other hand, are an open system with nested loops inside. And this is maybe where common sense is not so common gets explained. Individual’s brains love residing in a nested loop. That nested loop of thinking is experience-based ‘data’ where the identification of what needs to be solved pops up as common sense. That said. The issue would be the same as a smart machine in that this heuristic thinking is a closed loop system which ignores additional information flowing in. That being said the brain is an open loop system and has the ability to be to be able to feed consistent additional information into any one of the closed nested loops within our brain, if we elect to permit it in.

“The fact that digital computers are able to outperform humans and performing some mental tasks should come as no surprise they were designed to do just that.”

University professor Phil Auerswald

Which leads me to the fact good decisionmaking is not always the optimal decision.

Good decision making has always been in the purview of humans. While we all bitch and moan about the lack of good decision making by certain people, the truth is the majority of us make good decisions most of the time. Or, maybe said, we make the best decision that we possibly can in the moment with the information that we have at hand. Which leads me to say people have learned to make the really hard decisions by first making a lot of easy ones. People gain skills and confidence from simple situation decisionmaking where it can be determined afterwards whether a decision was made well or not. So. If we were to allow smart machines to take over these ‘starter decisions’ and leave only the highly ambiguous situations for humans, there is a risk that effective decision making would be a less-than-optimal choice for humans to make. Yeah. They would just suck at decisionmaking. Yeah. If fewer people understand how to diagnose a decision because they’ve never had to run the gauntlet of all the easy ones, how would we be able to even assess whether a good decision has been made on the hard ones later on? I sometimes worry that we will find ourselves under a smart machine decision making autocracy by default in which less educated, or less concerned, decision makers automatically follow the decisions of smart machines. I’m not suggesting this will always be a bad thing. In fact it raises the possibility that a lot of good things happen faster. But it will only be a good thing until it’s not. Sometimes it will be a very very bad thing. And I worry we humans won’t know which is which. But then again, if we absolve ourselves of responsibility for all the easy decisions, aren’t we by default divesting humans from the hard decisions?

Here is what I know.

A smart machine will always make optimal choices. The best future is rarely, if not ever, found by making optimal choices. In fact, it’s the less-than-optimal choices that tend to foster the spectacularly-more-than-optimal results. And I tend to think humans are the best spectacular error and spectacular success machines in the world. Ponder.

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“No, I’m not interested in developing a powerful brain. What I’m after is just a mediocre brain, something like the president of the American Telephone and Telegraph company.”

Alan Turing

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“The most important human endeavor is the striving for morality in our actions. Our inner balance and even our very existence depend on it. Only morality in our actions can give beauty and dignity to life.”

–

Albert Einstein

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“We need timeless principles to steer by in running our organizations and building our personal careers. We need high standards — the ethics of excellence.”

 –

Price Pritchett

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Ethics are our morals in action. Ethical behavior is the system we develop framed within our moral code. Our moral code, or our morals, are a system of beliefs emergent from our values. Values are the foundation of our ‘right/wrong judgement’ which create some belief system. This is personal, an individual decision, not universally accepted.

“values are our measures of importance, whereas ethics represent our judgments about right and wrong”

(Shockley-Zalabak 1999, p. 438)

It may seem like I am parsing thought here, however, in the business world all the words get tossed around flippantly (interchangeably) – particularly when it comes to culture. It is important because culture is emergent, not dictated. Culture is a collection of individuals, with individual values, who act in a coherent behavioral fashion, within an organization (where the systems enable or suffocate the individual behavior). I say this because this is when “principles” comes into play. Principles encourage a specific coherence not by dictating but rather by establishing some common agreement. In other words, despite each person having their own value prioritization, the organization establishes its value prioritization (establishing not what to do, but what not to do).

Look. Here is a truth.

We don’t really like to admit it but Life, in general, more resembles a constant teetering on the edge of a slippery slope than anything else (especially with regard to ethics, i.e., “doing the right thing.”). Life, and business, constantly, relentlessly forces you to make, well, ethical choices. Now. They may not look like ethical choices, but if you look real closely you will see the face of ‘right or wrong’ staring at you wagging its finger. We don’t look that closely because it would force us to admit:

• Right & wrong is often contextual
• Right & wrong is often not a clear black or white
• Right & wrong is often measured, ultimately, in consequences not actions, yet, we are demanded to choose right or wrong and act now

You will most associate this constant teetering (also a recognition of being on the slippery slope of fading ethics) as “just this once” behavior. We don’t really like to admit it because ‘just this once’ tends to be used to explain away some of our more dubious behavior and decisions.

This ‘dubiousness’ gets couched in a variety of ways. Safety. Utility. Benefits (functional and ‘to me’). We find a lot of ways to justify our behavior, decisions and attitudes before we ladder up to ethics. As my friend Faris Yakob (see image) suggests it is almost a Maslow-ian decision model. Its not that we ignore ethics or even not care about ethics its just we prioritize a number of things before we get to ethics. This suggests ethics is not a foundation from which decisions emerge, but rather are a final, fairly wide, box in which a decision has to be checked against.

source: Faris Yakob

If that is true, then ethical fading is commonplace, yet, justified by ‘pragmatism’ criteria. I bring up pragmatism because, whether we admit it or not, unless you actually think about ethics, morals and values (in a non-meta philosophical way) then it becomes a little more difficult to understand how principles can play a fairly important pragmatic guardrail role. The truth is that ethics are constantly challenged, in context, by safety and utility. For example, would we steal to feed our children or lie to keep us safe.

Sound moral judgment is rooted in strong values and acted upon by our ethics. An organizational judgement, a collection of these individuals, is herded in common principles.

Principles, yes, before you despair, principles guard against ethical fading. Principles are the cornerstones of your ethical building. Without principles you have no solid ground to stand on in a world constantly trying to tip you over into a variety of holes, slippery slopes and dead-end tunnels.

‘Principle’ is defined in Nuttall’s Concise Standard Dictionary of the English Language as, “n. the source or origin of anything; a general truth or law comprehending many subordinate ones; tenet or doctrine; a settled law or rule of action; to impress with any tenet; to establish firmly in the mind.”

Principles protect, in a very fragile way, against ethical fading.

They do so in a number of ways

1. They establish a foundation, or a moral filter, for ethical behavior. Maybe call them the ground rules of how you assess what is right versus wrong
2. Unfortunately, the foundation is a framework not a “how to do” manual. Therefore upfront they help define exceptions to the ground rules and, yes, we will always find some exceptions. Some ‘blurring’ of the guardrails as it were.
3. Unfortunately (part 2), this blurring, while not always creating ‘just this once’ behavior, it CAN create just this once behavior which is, well, the slippery slope of ethical fading. In this situation principles can actually be the solid lily pads of ‘no more’ certainty from which one can stop the slide down the slippery slope of ethical fading.
4. Unfortunately (part 3), principles, while resilient, are not immortal. Facing the onslaught of ethical fading they can, well, fade and once they have made their last stand you are screwed. You are on the slope and the only question left to answer is how far down the slope you end up.

So, despite their fragility, let me talk about principles.

“The most important ingredient we put into any relationship is not what we say or what we do, but what we are. And if our words and our actions come from superficial human relations techniques (the Personality Ethic) rather than from our own inner core (the Character Ethic), others will sense that duplicity. We simply won’t be able to create and sustain the foundation necessary for effective interdependence.”

Stephen R. Covey

To me principles revolve around a discussion of soul (selling your soul ). Some people may disagree with me but, to me, soul represents the intersection of I & We. It gives us life energy (call it our subconscious passion). It what joins us together with an external shared common vision – kind of our common value proposition for Life. It creates a connective tissue for, well, acting in a humane fashion with other humans. It is within this intersection in which we seek the common ground between morals, ethics and value and arrive at a coherent principled behavior as a community or business organization.

Let me suggest 4 cornerstone principles (not ranked, just foundational):

• Inviting culture premised on affection for humanity. Lives are to be lived for others (therein lies where we gain meaning), not just for our own success and advancement. We must model lives that matter if we want to nurture into living lives that matter. We believe that we are not islands unto ourselves but social beings who need community to flourish and become our best selves. Believing you are in, and of, community.
• Commitment to character demands involving oneself into multiple traditions and frameworks for what makes up a good life (contextually expanding your view). This means accepting a responsibility to pose questions which introduce one to a variety of cultures and contextual questioning.

Believing that character takes involvement & commitment & work.

• Do good. I imagine I am suggesting that if you do good you will contribute in a meaningful way (some call this a purposeful life). We must simply follow Aristotle’s advice, or Emerson, that “the purpose of our examination is not to know what virtue is, but to become good.” The point is not merely to study the good, in a detached and academic way, but to invite oneself to develop as a person of character.

Believing that a virtuous life is not found in attitude, but behavior & actions.

• Be curious about everyone and everything. Keep your head in a swivel as context changes. Exhibit a dedication, imagination and commitment to context as the fertile ground for intellectual growth, knowledge and ethical resilience. Ethical resilience is NOT rigid ethics, but rather strongly held principles which can accommodate the nuances of cultural context (reflective of cultures surrounding the person and decision). This principle, in particular, does not dictate character, but is intended to provide a compass to help each person find their own path and to grow in their awareness of self (and others).

Believing principles are not steadfast and unmoving but rather depending on adapting to new learning.

I will note that all the Principles are solid in belief but adaptable to time, knowledge and context. This is a recognition that we, humans, are not of self but rather of something bigger – society, community, connectivity.

Yes. This suggests Principles are not simple, but complex.

This leads me to leadership.

Leadership can be of one’s own life or it can be in combination with other people. Regardless, someone must develop some skills for successful leadership – for self or for group.

The first is the mindset that leaders see leadership as a skill that needs to be continually developed and improved (active listening, giving feedback, talking to people).

The second is a recognition that certain things happen under the surface and have a significant impact on the performance of the team, such as interpersonal dynamics, the way individuals work, disputes and tension between people (typically originating from the past). Leaders have to have the skills to bring these things to the surface and resolve them.

** note: this is also true of self and inner conflict

The third is power and inclusion. Power dynamics effect any social structure (you are misguided if you don’t believe this). You have to recognize, and acknowledge, power dynamics in order to be inclusive, empathetic and create complete connections. If you elect to ignore the relationship between power and ethical behavior, i.e., how power stresses individual values prioritization and behavior toward goals, you will ignore the truth that the more power you need, the more likely ethical fading is to occur.

That said. In old structures (hierarchy) power can be directed, but in future organizations power emerges (networks evolve) and leadership is expanding potential from emergent power dynamics. This will demand a different type of character. This type of character navigates the I, we, larger We dynamics of an interconnected life, business & society.

“Character, like oxygen, is most noticeable when it is missing.”

Richard Reeves

The new powerful leadership will not lead with power, but rather principled driven energy and instead of just accumulating wealth/profits/achievements, seek to accumulate outcomes to be proud of.

Look.

These are very strange times. I would not say it’s the worst of times, but it seems to be a world that demands binary, black & white stances despite the fact navigating ambiguity and uncertainty is the path to not only success, but progress. What I can say is that holding onto something in a black and white way in a world of swirling colors, and grays, creates an ongoing sense of uncomfortableness. Maybe worse is attempting to hold onto binaries you will slide down the slippery slope of ethical fading without even noticing until its too late.

And maybe that is where I will end. You would think ethical fading would be associated with gray and the graying of morals and choices, but its not. Ethical fading occurs one black & white step at a time.

In the end.

We often speak of “principled leadership” or desiring leaders to have principles. I would argue each of us, to be successful, need to grapple with our own relationship between values, ethics and principles. Because, in the end, while we may be grounded in our values and measured by our ethical behavior what will matter will be the principles which make all of these decisions coherent to our Life – what we will, or will not, do. Yes. Refusal of “ethical fading” suggests “we are what we refuse to do” or, as Paul Chippendale stated, “we are what we refuse to adapt to.”

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“The rules cannot be understood apart from the virtues at which they aim”

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Telos is the Greek word for a human’s ultimate aim. Its kind of the smart version of today’s dumbed down “individual purpose. It represents his ultimate purpose and function — an essential nature that can only be realized by throwing off the inertia of default desires and actively striving after it. Its kind of like attaining “what you could be”, your potential best, if you could clear the decks and do it. to be clear, this isn’t excellence, it is more about flourishing as a human being.

Which leads me to virtuous.

Here is what I mean by virtuous:

• Do good. I imagine I am suggesting that if you do good you will contribute in a meaningful way (some call this a purposeful life). We must simply follow Aristotle’s advice, or Emerson, that “the purpose of our examination is not to know what virtue is, but to become good.” The point is not merely to study the good, in a detached and academic way, but to invite oneself to develop as a person of character.

Believing that a virtuous life is not found in attitude, but behavior & actions.

I believe it was Aristotle who suggested being a good human was both functional and objective which means that being virtuous is not just lived within what you do (so asking to be judged by your actions may mean well but you are likely to be doomed within judgement of) but also within intent (your aspirations to be better). That said. I imagine the conflict of self, in life, mainly resides in the liminal space between who we are and who we could be at our best.

Which leads me to coherence.

Far, far, too often people suggest consistency is the key to attaining your purpose or even a life better lived. They would be wrong. It is coherence. Life, business, shit, everything, is driven by connections with others and other thoughts. And within each of those connections you have conversations – with others, their ideas and even in your own head. At some point, if you want to make any progress, this lends you some coherence within all the scattered ideologies and feelings and attitudes and opinions so you can shape some perspective. It shapes both imagination and reality all of which shapes identity.

I would argue they shape your telos as well as create the platforms for a better life, business, and society. And while these three things may never be completely in sync, I would argue that the constant coherence around seeking the sync is where things get better – everything.

That coherence establishes some parameters and ultimately people, not just an individual, get mobilized within those parameters to do better things, think better things, and become better.

I imagine this is an argument for each individual doing the right thing, and if they get close to individual telos, the greater good, the greater community and society, is positively impacted.

Which leads me to end with rules do not help.

While I don’t want to confuse, or conflate, morals and virtue, I will use philosopher Alasdair McIntyre, “when a moral culture lacks a teleological element, rules become the primary concept of the moral life” to make a point. Rules do not define behavior nor do they define virtue. Rules are a default mechanism for people too weak to decide what is right and what is wrong, what is virtuous and what is not.  Simplistically, a societal system, or even a business culture, which lacks a coherent understanding of its telos, there can only exist negative proscriptions for appropriate behavior, i.e., rules shape behavior. The reality is rules are not meant to move people toward meaning or purpose or mattering, they are simply reductive, and restrictive parameters, to basic behavior. If you want to be better, as a person, as a business, as a society, rules will not get you there. I am not suggesting rules should be abolished, but I am suggesting the closer we get to a true telos mindset, the less we will ever have to use rules. Ponder.

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“There are countless ways of achieving greatness, but any road to achieving one’s maximum potential must be built on a bedrock of respect for the individual, a commitment to excellence, and a rejection of mediocrity.”

Buck Rodgers

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While I have always been a Tom Peters fan, especially his book Thriving on Chaos, I have always chafed at The Search for Excellence. Ok. Let me be more specific.

First.

In Search of Excellence was the first book I faced in my career that became a ‘formula’ for business people I worked with. Normally sane thoughtful independent thinking business people (mostly men) would pull out the book or point to it on some shelf and would say “we need to do this.” Without question it became the first business bible, of many business bibles to come, of what everyone needs to do to be excellent. And while I could debate some aspects of the book itself suffice it to say, its good, has some great ideas, but is not a bible.

Second.

Excellence. While excellence seems like an innocuous helpful objective, when placed into a typical maniacal business environment (business pursuit of profits) excellence as an objective can become quite unhealthy. Its almost like perfection. Seeking excellence, and even perfection, can often make things better, but when they become objectives everyone gets measured in an “absence of” way <both are actually unattainable so when measured everyone will appear lacking>. When I was younger it was impossible trying to convince people excellence was a dubious objective at best. Later in my career as I got better at pointing out how good ideas can be misinterpreted and misused and become misguided objectives, I took this battle on more often (more on that later).

Then I found this snippet from a research paper (source lost):

In the eighties and nineties, N. Aubert and V. de Gaulejac (2007) argued, that the “ethics of excellence” in people management created the moral foundation of a system striving to control the totality of a person. In convincing employees that, by working for the firm, they were working for themselves, a complete blurring was made of professional and personal ambitions, and companies emerged as institutions capable of mediating individual destinies, supporting self-development, objects of true love, and in the end the only instrument able to fulfill the need for immortality of the self.

This work ethic creates particular interactions between people, interactions marked by the constant necessity to become visible. This quest for visibility takes the form of a new social game in which everyone is striving to capture the attention of others. In a sort of Goffmanian ‘parade’, self-branding and “newsing” oneself are ways to occupy the mental space of others and to stay on top of the competition. For businesses, being always present on personal communication channels, on webplatforms, etc., is a way to colonize the minds of their managers and to reduce their capacity to imagine another world.

The point here is that searching for excellence, when wielded as a management tool, became not only a power play, but as it became a standardized tool it became an imagination/innovation diminisher. As with most things business does, they decided to make the search for excellence more a ‘paint by numbers’ concept rather than a malleable concept to be applied differently in different contexts. What the idea lost was what Mary Parker Follett called “the law of the situation.” In other words, the situation, the context, dictates the application of an idea or concept – even excellence.

Third.

Excellence aside, there are a number of good well intended ideas that have driven many a good business person off the beaten path to success. Copying and standardization are the worst things that can ever be done to a good concept. I have known that for many many years and have therefore been a pain in the ass for many many years.

I have been a pain in the ass for years.

In mid 90’s I published the highly unpopular “customer is not king/queen” arguing that all it would do is create an entire industry of businesses chasing customer’s whims & wants consistently undermining expectations. My agency was not delighted. But it did.

In 2005 I published the ‘inside/out manifesto’ arguing to achieve highest order of value is thru organization knowing who it is, unequivocally accepting that, with a product as an extension of who they are (successfully addressing a need) matched with customers who want that combo. Branding people were grumpy.

In 2000’s when my agency introduced The Big Idea brief I skewered it as encouraging people to believe the only ideas of value were Big and encouraging clients to only be happy with so-called Big ideas & it would create a false culture in which we made ‘small’ shit, even small shitty ideas, look Big. Agency not happy. But it did.

In 2008 I skewered The Experience Economy (although I think it is one of most important business books/ideas of this generation) arguing it would spawn an industry of vapid ideas & meaningless products wrapped in experiences all the while espousing premium value. It has.

In 2010 I began harpooning customer centric arguing it only leads to unmet promises, false expectations & hollow value (internally & externally) within hierarchies. It demands distributed organizational autonomy or it creates no value. It has & it still does.

In Search of Excellence, Good to Great, Tipping Point … pick a book with a viable idea and it has been abused. The biggest abuse resides in taking one’s eye off the single most important thing – successfully implementing any of these good ideas to the highest order of value are contingent upon a consistently good product consistently delivered. My biggest issue is how all this stuff diverts people from the hard work of developing a meaningful product & creating value in it.

Let me end by circling back to a thought that may have not been highlighted enough. The Law of the Situation (Mary Parker Follett). I love ideas from smart people, I love books and I love learning new things. But. Everything is contextual. Everything. The law of every idea is overruled by the law of the situation. No idea’s maximum value can survive the context without some adaptation. In other words. Each situation has its own order and own concept. I imagine my point is that you can study excellence,  accountability methods, leadership principles, but, inevitably, all that matters is the Law of the Situation. Ponder.

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“a series of steps, each building on the last, but without a predetermined plan. We did what was necessary and as we made progress or ran into problems it became obvious what needed doing next. It wasn’t a straight line. We made mistakes and not everything worked. But we realized we were learning by doing.”

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“The devil isn’t just in the details. He’s in the definitions. And, most of all, he’s in the analytical distinctions: in the ability to tell one thing from another. To not mix things up.”

Hanzi Freinacht

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Where does all our crappy behavior and crappy perceptions of the world come from?

Like most things, it’s mainly the product of learned behavior. That may sound horrible, but we humans are imitation machines. Our subconscious minds constantly take in signals from the environment and integrate them into our mindsets, attitudes and, yeah, even behaviors, all of which end up guiding our perceptions and our actions. And while we want to blame social media, and media in general, the most influential part of any environment is the people in it.

Which leads me to a Toffler, Future Shock, thought.

….. impact of Warehouse of Images (before Instagram existed) …..

Pre-internet we were exposed to a fairly finite, and fairly rigid, sample of the human population to ‘imitate’ or judge our perceptions and behaviors. The people in our neighborhood. In our schools and libraries and community gathering places. At the grocery store. In our office. On the street. On the bus. We lived in smaller community echo chambers, where signals were fewer, and meanings/cues were clearer or, at least, more well defined. The internet exponentially expanded our universes wherein the number of signals we receive has increased exponentially and meanings/cues became scrambled into a moshpit of signals. Our common, well, any commonality, and agreed upon sensemaking lost clarity and gained some fairly vague outlines. In other words, social coherence lost accepted boundaries. Our imitation muscles were overworked as we attempted to learn behavior from a seemingly limitless onslaught of cues of which it became almost impossible to discern the majority from the minority.

Which leads me to the danger and opportunity.

We simultaneously see more crappy behavior than ever before, which creates a perception that everyone is crappy, and, yet, we see more kind and moral behavior than ever before (maybe just not from what we would have easily accepted as an established traditional local influencer in the past) which creates a perception that not everyone is crappy. Generally speaking, it is confusing. Are people good or bad? What that means is because we see more information about other people than ever before we need to be very, very, careful what we normalize because while we may not exactly imitate – we may simply begin accepting some version of crappy behavior. We see videos of crappy behavior of kids in schools, crappy crazy drivers, crappy acting adults arguing in grocery stores, let alone the insane amount of insane self made crappy video rants. All of these things we already knew happened occasionally, but virality implies it isn’t confined to the occasional.  And, well, what a culture sees, is what a culture becomes. The more a person sees something, especially another person’s actions, the more they will either gravitate toward it or simply accept it as “how we are” as people (whether we like it or not). It creates the message that “this is how society is.” Even if it is really not.

Which leads me to what we see (and what we become).

In the wayback machine, we had more control over what we would see. Plus. A smaller community controlled what we saw (in some form or fashion). Simplistically, we had to work harder to see the less-than-normal shit. The problem in today’s world is what we are ‘shown’ doesn’t care about proportionality so the ‘less-than-normal shit’ takes on an oversized shitstorm feeling of everywhere all the time. All this to say we get caught in the wretched inbetween of knowing that access to all this information makes us smarter, can make us safer, and actually can create a more equitable (accountable) society AND knowing that a consistent onslaught, or drip-by-drip, of exposure to crappy behavior, well, suggests we begin imitating some of that behavior in order to be ‘competitive’ in today’s crappy society/world. It’s kind of like the tragedy of commons just with behavior. This all breeds a sense of what is called ‘learned helplessness’. This is where we become conditioned to believe that a bad situation is unchangeable, resulting in an unrealistically negative view of the world and a sense of permanent crisis. Ultimately this eliminates hope, or diminishes it (through crappy perceptions), and we either disengage or assume some crappy behavior aspects.

Which leads me to creating a culture which we want people to see so it can become a better culture.

I have written far too often about how algorithms shape what we see and, therefore, shape culture (at least by my measure). But humans are smarter than algorithms, humans create algorithms, and algorithms do not have culture, do not understand culture nor do they even care about culture – algorithms feed people what they ‘say’ they want. Period. So, we can choose to spread the good stories and starve the bad ones of attention. Period. End of story. The stories we tell and we share, becomes what a culture sees and, ultimately, what it becomes.

By assuming this responsibility, hopefully, we learn something new, good; and we change course.

In the end.

Everyone should think about this a bit because the basic premise I offer is the thought if we continuously see crappy behavior, we will start doing some crappy behavior. A lot of people will balk at that. They will believe they can recognize crappy behavior as unacceptable and will never do it. Uhm. I am not so sure about that. I think it becomes just a bit easier to do some crappy things, on occasion, if you have a crappy perception of the context and think everyone else is going to be crappy. Shit. Think about how business culture works (and doesn’t). That said. Ponder. It feels important.

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… discovered a more complex problem. Most customers weren’t fed up with any one phone call, field visit, or other individual service interaction—in fact, most customers didn’t much care about those singular touchpoint events.  What was driving them out the door was something the company wasn’t examining or managing—the customers’ cumulative experience across multiple touchpoints, multiple channels, and over time.

Take new-customer onboarding, for example, a journey that spanned about three months and involved an average of nine phone calls, a home visit from a technician, and numerous web and mail interactions. At each touchpoint, the interaction had at least a 90 percent chance of going well. But average customer satisfaction fell almost 40 percent over the course of the entire journey. The touchpoints weren’t broken—but the onboarding process as a whole was.”

McKinsey: Touchpoints to Journey

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“Of course, disinformation,” Quinn said. “I can do that. I’ll leave out critical events, then I’ll put in false information and twist everything that has happened around into a vague, shadowy history that obscures what really took place.”

Terry Goodkind

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So. I pick up McKinsey white papers on occasion because, while bloated diatribes, they are typically frickin’ smart. My opening quote on the ‘touchpoint journey’ is from McKinsey.

Now. In the marketing & communications world touchpoint marketing has been around for decades by one name or another.  But recently I had to discuss it and ended up talking about it in a slightly different way than I have in the past. I had scribbled down “tactical connection engineers.”

What made me sit back on this a little was this applies to a communications professional as well as everyday schmucks like you & I <who take in communications & messages>.

Communications professionals as tactical connection engineers.

Communications people have had a logistical organizational problem with an effective touchpoint connection plan for years. We hire specialists and then ask them to drill down in their specialty to insure ‘the most effective plan of action within that touchpoint silo.’ This translates into a couple of things, assuming they do their job well,

<a> it will focus so much on the target, the consumer, in its intent to herd and persuade & ‘connect’ that it can very easily slip away from the business selling the shit, and

<b> while today’s business world vociferously balks at ‘purchase funnels’ the truth is that if you have a specialist within some touchpoint segment they may show you some hurricane like visual to show that in the swirl of a connection they herd someone into a ‘meaningful relationship’ stage … uhm … that’s a funnel.

In addition. I would suggest that with companies going to specialized partners and silos what could be construed as a ‘customer focus’ may actually exacerbate the problem as everyone goes running toward their own view of customers and journeys and, maybe worse, prioritizing shit on the journey based on their own budgetary limitations. These silos aren’t really customer focused people nor are they ‘strategic thinkers’, they are actually more likely to be tactical connection engineers.

Everyday schmucks as tactical connection engineers.

Let me explain this one a little because I think it would behoove communications professionals to think about us everyday schmucks like this more often. We tactically engineer our input. We do his to engineer the productivity in our life. Sometimes it may be fr pleasure but the majority of the time we are engineering on Life efficacy <efficient & effective>. I say this because while communications talk ad nausea about a non stop ever changing world they tend t view us everyday schmucks in some stagnant way. They don’t view us as “tactical connection engineers’ but rather simply prey for their own tactical connection engineering. Stupid.  We are tactically engineering our own connectivity on a daily basis dependent upon the context of the day, hour, moment.

Ponder that a second all you “highest order of personalization” advocates. Your head will explode if you ponder too long.

All that said.

While I am not a huge specialized fan, in a specialized world I would argue that holding the center is the most important thing — holding the center on functional offering, brand/company character lens and vision <let’s call that the company distinctness>. Holding the center on the grander strategy & the greater good <brand value> beyond the simple transactional connection objective. It insures whoever is doing whatever will at least be aligned on what really matters – what you are selling and who is selling it. It also insures the intense focus on connection doesn’t inherently strip away the substantive shit that makes up the greater value in the brand.

I cannot tell you how many times I have pulled the following lines from “The Second Coming” by Yeats:

Turning and turning in the widening gyre

The falcon cannot hear the falconer;

Things fall apart; the centre cannot hold;

Mere anarchy is loosed upon the world,

Siloes, or multiple partners, are the falcons. You need to make sure you have a falconer who can be heard <assuming you have a hierarchy type organization>. That means your tactical connection engineers need a head engineer <for ALL tactical engineers regardless of department or expertise>.

I have been asked a zillion times by my business owner friends I always tell them the same thing … do not hire multiple partners unless:

<a> you choose one as the one to hold the centre for you, or,

<b> you are strong enough to hold the centre yourself – and on b. I am honest enough to tell them that most companies/clients don’t really have that expertise to do that because it is far too easy to follow the next shiny object.

That is my #1 argument for finding one partner and using them well.

Now. Back to the risk in tactical connection management. Of course, it’s necessary to provide customers with what they say is important.  However, research consistently shows that it’s much more valuable to align customer experience investments to those elements shown to drive emotional connection, thus maximizing ROI while minimizing risk. For example, one research study showed customer-experience strategies that maximized emotional connection resulted in customers who are six times more likely to consolidate assets with the firm than customers who are highly satisfied, but not emotionally connected.

In the search for profitable organic growth, more and more companies are investing in the technological aspects of optimizing the end-to-end customer experience <each aspect of how customers interact with the company’s brand, products, promotions, and service offerings, on and offline>. They seek to optimize each touchpoint assuming by doing so they will optimize the entire ‘journey.’ They are wrong, in addition, most of these same companies lack a strategic objective for all the pieces & parts in the whole. This matters because without the strategy you gain efficiency (theoretically), but you lose the opportunity to increase customer value. This matters because without the strategy the tactical connection engineers just become the most efficient tactical engineers, not necessarily the most effective for the company.

Look.

I do think tactical connection engineers will also need to be better data interpreters <decoders>. Why? Well. data people are finally realizing to maximize customer value it isn’t about just customer satisfaction but also an emotional tier in which you appeal to some fundamental motivations and emotional motivators  <desire to feel a sense of belonging, to succeed in life, or to feel secure for details>. HBR has a nice article on this: “The New Science of Customer Emotions”).

In the end.

Touchpoint architecture is a good basic principled way of viewing things. Some people may argue against that, but it’s a framework, not a formula. I will say the larger issue is not the system itself but rather how the system is used, hence, my suggestion to have “tactical connection engineers.” Ponder.

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Gathering:

 accumulate, amass, assemble, bulk (up), collect, concentrate, congregate, constellate, corral, garner, group, lump, pick up, round up, ball, batch, bunch, cluster, huddle, heap, pile, stack, flock, herd, hive, pack, press, swarm, throng, combine, connect, join, link, merge, pool, unite

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Several years ago, in a piece called “thinking, decision making and leadership” I wrote this:

• Which leads me to declustering. Leaders like to cluster decisions and business like to cluster things. All are typically done because everyone believes it is more efficient and, possibly, more effective. Clustering is the unspoken organizational corrosive barnacle on the progress ship. It is true business, and clusters, arc toward replication. If a leader spots a ‘decisionmaker’ inevitably they will guide more decisions to that person simply. Decisions then cluster thereby making the overall – most clusters – desire to be involved in decisions to decluster. Yeah. For every action there is an equal and opposite reaction. By default, you’ve once again parsed out responsibility, not collaborative sensemaking, and created a different type of hierarchy. I am not suggesting some clusters aren’t better at making decisions than others. What I am suggesting is leaders’ natural instinct is NOT to spread sensemaking and thinking, but isolate so when convinced to distribute and spread, no matter how effective overall it may be, inevitably they will redistribute to a few – that’s the arc. Just ponder.

Several years ago I also wrote: “the natural arc of every business is to mediocrity.”

The two are related.

Yeah. I am saying clustering leads to mediocrity. That said, oddly, business tends to like clustering, or, they do not discourage clustering. Let me be clear. Given an opportunity to be excellent, a business will always choose the path to mediocrity. Yes. Always. What I mean by that is in every situation – customer service, capital investment, ideation, innovation, creativity, planning, strategy, implementation – given an opportunity to choose a Spinal Tap 11 choice, a business will always choose a 9 or below choice. And from there on out that ‘plus number’ begins diminishing bit by bit. And while I imagine I could point to a variety of reasons, let me focus on clustering as the culprit.

As soon as an “11” opportunity is identified, business will circle the wagons around some consensus data, group view, collective wisdom, whatever, which never raises the 11 to a 12, it only brings it down (usually significantly).

That’s clustering.

To be clear. Mediocrity is fairly equal opportunity employer. Data pools, cliques, opinions, specialists, likeminded clusters, all circle the wagons and transactional thinking actually (a) makes teams exclusive and (b) makes value finite and, yet, encourages a belief in exceptionalism (but a reality of mediocrity). From the ‘rational business’ perspective businesses like ‘clusters’ because they appear to be patterns (or some version of mass coherency) which they immediately associate efficiency and scale to. They don’t really care if the cluster benefits lose degrees of efficiency from that point on – they’ll flog the cluster until it is dead of anything good (or true value creating). Maybe worse is that over time clusters become ‘self-sealing belief’ parts within an entire system basically creating limits to tapping into the larger potential of the entire organization. That doesn’t mean they don’t offer value, its just that the value has limits and tends to stratify which makes them a bit more difficult to mesh with other components of the system. Clusters DO produce good things, but while those things seem good at scaling, it is not clear that they are necessarily good at innovation or anything ‘new’. Or another way to put it: clusters may might be good at exploiting (that is repeating a known winning pattern), but are less good at exploring (that is figuring out what needs to be done).

The corollary to that last sentence is clustering limits potential.

Business loves to cluster skills, but clusters tend to be herded into small clusters of micro skills in their macro skill puzzle. In this excellent video with Alain de Botton he points out that clusters are fragmentary in skills and interests and, yet, we are told what we are not good at, what we should focus on and then wealth is rewarded to that focus. In other words, we are told to cluster around a specific thing we may like or be good at and ignore (or relegate as a ‘hobby’) other skills and interests.

This has consequences beyond skills. The ways clusters interpret things do not translate neatly into larger decision trees. In addition. Decisions are not discrete, they are connected. A cluster may get parts of ‘now’ right, but the other parts may gather momentum or strength in the fact they were chosen as inconsequential in that ‘now’. In a cluster’s confidence lies its biggest risk. The truth is that, particularly in business, human expertise is usually tied to knowing what to look for – the nuances within hard data/information. Clusters become increasingly certain and blind to ‘new nuance.’ The repercussions to this is then a cluster is more likely elect to choose solutions or actions inconsistent with the problem/situation at hand but consistent with their view. That inconsistency can be in nuance or it can avoid some significant aspects, regardless, the consequences are often the same as the future unfolds from what was perceived as effective framing, but less-than-effective choice making. You have to decluster things. consciously. consistently, to optimize decisionmaking.

Which leads me to point out growth tends to polarize itself.

Cluster-driven growth is often spectacularly unprofitable. Business chases success/growth. Its inherent reaction to success is to milk that success until it is dry (albeit many businesses refuse to let go of even dry growth paths). Business uses math, numbers, relentlessly to pursue this objective. Reminder. It was Bernoulli who stated “mathematics alone does not capture a situation.” This is also true of a graph/dashboard. They simply inform or become a guide to a grander discussion of what exists and how to make sense of something, yet, business people cluster around dashboards and cluster energy/focus based on them.

“In a world glutted with information, the capacity to ignore selectively becomes ever more valuable … a system that is to control its environment successfully must adapt by constructing models that allow it to decide what information to get and how to act on it.”

Seth Lloyd, MIT

Business loves numbers. Which leads me to remind everyone one of businesses/s biggest lies is “the numbers never lie.” Numbers lie all the time. Even beyond how people torture numbers until they say what is wanted, numbers create clusters. Yeah. As soon as you find a number you like it becomes a magnet for other numbers, resources, energy, focus, etc. What this means is business relentlessly clusters resources against a diminishing growth opportunity. Invariably ROI can never really improve, in a meaningful way, but intrepid business people will always find ways to suggest things are good and getting better. Once again, it never hits 11 and is only getting closer and closer to 1. The only way to get off that slippery slope of lessening growth is, well, declustering.

Which leads me to power.

The issue occurs with, well, power. Those in power like evenness and replication and they view the only way to keep balance is to enforce it. They believe that no one else understands how to balance or maybe can even see the value of balance. They see themselves as being in the middle doing what’s best – for their sake – and they use ‘clusters’ as hammers. They cloak their hammers in ‘safety’, i.e., we keep clusters safe and the business safe. This gets tricky because most people clusters have an unhealthy trust in in larger systems with regard to what is beneficial TO the cluster which makes them less likely to realize when they (the cluster) has made a mistake AND less likely to realize when the larger system truly has something to offer that is beneficial to the progress/development of the cluster. All that said. Power clusters. Even though an individual in power is either (a) obliviously overconfident or (2) constantly paranoid, most individuals in power recognize they need other power players to dominate others. So whether it be by salary/$, titles, perceived meritocracy, education, or even psychotic authoritarianism, people will cluster for power – in implementing as well as in holding onto. Obviously, businesses should actively decluster power as much as possible to attain full potential.

“It’s a game of nanoseconds. Judgement calls have to slide through impossibly narrow doorways.”

Carolyn Barclay

Which leads me to data, technology and humans.

I have written a number of times about how technology can be used to decluster. In my unpublished book I even dedicate a chapter to how algorithms and technology can be used in a business infrastructure to nudge declustering to the benefit of sensemaking and gaining knowledge. That said. Technology amplifies everything – strengths & vulnerabilities – all of which stress the boundaries of any system. The corollary to this is the more you depend on technology the more likely a catastrophic even will occur (resolves little problems hiding the lurking catastrophe inside) because technology attacks/addresses things systematically while systems shape themselves organically (creating dissonance at some point). What that last mumbo jumbo sentence really means is that technology clusters shit by amplifying what people like and or are interested in. Sure. Machines and technology will often suggest potential actions and we may calibrate different paths with probabilities of success. The problem is that everyone will have the same input and if everyone does exactly what the input suggests everyone will, well, cluster.

Data and technology are inputs, but it is experience, wisdom, patience, and emotional fortitude that are the key ingredients when added to the inputs that result in differing results. And this is where clustering gets, well, fucked. Yeah. I just said clusterfuck. If people are clustered, they apply the same experience, wisdom, emotion against the same clustered data and technology, hence, the clusterfuck.

Experts always suggest the key to an algorithmic future is to be sure you understand what an algorithm is optimized for. I believe this is too simplistic.

“We know from biology that relentlessly preventing small problems can increase the risk of future big problems.”

Seth Blumsack

 

Not only are algorithms typically built to head off problems immediately (eliminate small problems), but how they get advice, information, determines how they behave. This has some very practical consequences in that, generally speaking, is more likely to present only catastrophic complex problems to the attention of clusters. Basically it ignores small problems/issues. Well. Anyone remember: “its never the elephants that kill you, it’s always the ants”? We design our systems, process and even encourage clusters, to focus on building elephants. We even build algorithms with that in mind. Clusters are elephants.

Which leads me to end with cluster narratives.

I don’t really know if clusters of people, or data, create narratives or if narratives encourage clusters. What I do know is a good story told well gets repeated over and over again creating a myth – and people cluster around myths. Generally speaking, myths aren’t very good for business. Myths get in the way of reality and are stubbornly resilient against alternative narratives (learning). So, yeah, I am suggesting declustering narratives (which is actually deconstructing narratives). This is a semi-important point as I circle back to an opening point: the arc of business is toward mediocrity. I cannot remember one business narrative myth that extols mediocrity, yet, by following most business narratives you are simply following the lure of mediocrity. Quite the paradox. It kind of feels like the only way out of that paradox is, well, declustering. Ponder.