Author Archives: Greg Satell

About Greg Satell

Greg Satell is a popular speaker and consultant. His latest book, Cascades: How to Create a Movement That Drives Transformational Change, is available now. Follow his blog at Digital Tonto or on Twitter @Digital Tonto.

We Must Stop Fooling Ourselves and Get Our Facts Straight

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GUEST POST from Greg Satell

Mehdi Hasan’s brutal takedown of Matt Taibbi was almost painful to watch. Taibbi, a longtime muckraking journalist of some renown, was invited by Elon Musk to review internal communications that came to be known as the Twitter Files and made big headlines with accusations regarding government censorship of social media.

Yet as Hasan quickly revealed, Taibbi got basic facts wrong, either not understanding what he was looking at, doing sloppy work or just plainly being disingenuous. What Taibbi was reporting as censorship was, in fact, a normal, deliberative process for flagging problematic content, most of which was not taken down.

He looked foolish, but I could feel his pain. In both of my books, I had similarly foolish errors. The difference was that I sent out sections to be fact-checked by experts and people with first-hand knowledge of events before I published. The truth is that it’s not easy to get facts straight. It takes hard work and humility to get things right. We need to be careful.

A Stupid Mistake

Some of the most famous business stories we hear are simply not accurate. Gurus and pundits love to tell you that after inventing digital photography Kodak ignored the market. Nothing could be further from the truth. In fact, its EasyShare line of cameras were top sellers. It also made big investments in quality printing for digital photos. The problem was that it made most of its money on developing film, a business that completely disappeared.

Another popular fable is that Xerox failed to commercialize the technology developed at its Palo Alto Research Center (PARC), when in fact the laser printer developed there saved the company. What also conveniently gets left out is that Steve Jobs was able to get access to the company’s technology to build the Macintosh because Xerox had invested in Apple and then profited handsomely from that investment.

But my favorite mistold myth is that of Blockbuster, which supposedly ignored Netflix until it was too late. As Gina Keating, who covered the story for years at Reuters, explains in her book Netflixed, the video giant moved relatively quickly and came up with a successful strategy, but the CEO, John Antioco, left after a fight with investor Carl Icahn and the strategy was reversed.

Yet that’s not exactly how I told the story. For years I reported that Antioco was fired. I even wrote it up that way in my book Cascades until I contacted the former CEO to fact-check it. He was incredibly generous with his time, corrected me and then gave me additional insights that improved the book.

To this day, I don’t know exactly why I made the mistake. In fact, as soon as he pointed it out I knew I was wrong. Somehow the notion that he was fired got stuck in my head and, with no one to correct me, it just stayed there. We like to think that we remember things as they happened, but unfortunately our brains don’t work that way.

Why We Get Fooled

We tend to imagine that our minds are some sort of machines, recording what we see and hear, then storing those experiences away to be retrieved at a later time, but that’s not how our brains work at all. Humans have a need to build narratives. We like things to fit into neat patterns and fill in the gaps in our knowledge so that everything makes sense.

Psychologists often point to a halo effect, the tendency for an impression created in one area to influence opinion in another. For example, when someone is physically attractive, we tend to infer other good qualities and when a company is successful, we tend to think other good things about it.

The truth is that our thinking is riddled with subtle yet predictable biases. We are apt to be influenced not by the most rigorous information, but what we can most readily access. We make confounding errors that confuse correlation with causality and then look for information that confirms our judgments while discounting evidence to the contrary.

I’m sure that both Matt Taibbi and I fell into a number of these pitfalls. We observed a set of facts, perceived a pattern, built a narrative and then began filling in gaps with things that we thought we knew. As we looked for more evidence, we seized on what bolstered the stories we were telling ourselves, while ignoring contrary facts.

The difference, of course, is that I went and checked with a primary source, who immediately pointed out my error and, as soon as he did, it broke the spell. I immediately remembered reading in Keating’s book that he resigned and agreed to stay on for six months while a new CEO was being hired. Our brains do weird things.

How Our Errors Perpetuate

In addition to our own cognitive biases, there are a number of external factors that conspire to perpetuate our beliefs. The first is that we tend to embed ourselves in networks that have similar experiences and perspectives that we do. Scientific evidence shows that we conform to the views around us and that effect extends out to three degrees of relationships.

Once we find our tribe, we tend to view outsiders suspiciously and are less likely to scrutinize allies. In a study of adults that were randomly assigned to “leopards” and “tigers,” fMRI studies noted hostility to out-group members. Research from MIT suggests that when we are around people we expect to agree with us, we don’t check facts closely and are more likely to share false information.

In David McRraney’s new book, How to Change a Mind, he points out that people who are able to leave cults or reject long-held conspiracy theories first build alternative social networks. Our associations form an important part of our identity, so we are loath to change our opinions that signal inclusion into our tribe. There are deep evolutionary forces that drive us to be stalwart citizens of the communities we join.

Taibbi was, for years, a respected investigative journalist at Rolling Stone magazine. There, he had editors and fact checkers to answer to. Now, as an independent journalist, he has only the networks that he chooses to give him feedback and, being human like all of us, he subtly conforms to a set of dispositions and perspectives.

I probably fell prey to similar influences. As someone who researches innovation, I spend a lot of time with people who regard Netflix as a hero and Blockbuster as something of a bumbler. That probably affected how I perceived Antioco’s departure from the company. We all have blind spots and fall prey to the operational glitches in our brains. No one is immune.

Learning How To Not Fool Ourselves

In one of my favorite essays the physicist Richard Feynman wrote, “The first principle is that you must not fool yourself — and you are the easiest person to fool. So you have to be very careful about that,” He goes on further to say that simply being honest isn’t enough, you also need to “bend over backwards” to provide information so that others may prove you wrong.

So the first step is to be hyper-vigilant and aware that your brain has a tendency to fool you. It will quickly grasp on the most readily available data and detect patterns that may or may not be there. Then it will seek out other evidence that confirms those initial hunches while disregarding contrary evidence.

This is especially true of smart, accomplished people. Those who have been right in the past, who have proved the doubters wrong, are going to be less likely to see the warning signs. In many cases, they will even see opposition to their views as evidence they are on the right track. There’s a sucker born every minute and they’re usually the ones who think that they’re playing it smart.

Checking ourselves isn’t nearly enough, we need to actively seek out other views and perspectives. Some of this can be done with formal processes such as pre-mortems and red teams, but a lot of it is just acknowledging that we have blind spots, building the habit of reaching out to others and improving our listening skills.

Perhaps most of all, we need to have a sense of humility. It’s far too easy to be impressed with ourselves and far too difficult to see how we’re being led astray. There is often a negative correlation between our level of certainty and the likelihood of us being wrong. We all need to make an effort to believe less of what we think.

— Article courtesy of the Digital Tonto blog
— Image credit: 1 of 1,050+ FREE quotes for your meetings & presentations at http://misterinnovation.com

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We Must Hold AI Accountable

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We Must Hold AI Accountable

GUEST POST from Greg Satell

About ten years ago, IBM invited me to talk with some key members on the Watson team, when the triumph of creating a machine that could beat the best human players at the game show Jeopardy! was still fresh. I wrote in Forbes at the time that we were entering a new era of cognitive collaboration between humans, computers and other humans.

One thing that struck me was how similar the moment seemed to how aviation legend Chuck Yeager described the advent of flying-by-wire, four decades earlier, in which pilots no longer would operate aircraft, but interface with a computer that flew the plane. Many of the macho “flyboys” weren’t able to trust the machines and couldn’t adapt.

Now, with the launch of ChatGPT, Bill Gates has announced that the age of AI has begun and, much like those old flyboys, we’re all going to struggle to adapt. Our success will not only rely on our ability to learn new skills and work in new ways, but the extent to which we are able to trust our machine collaborators. To reach its potential, AI will need to become accountable.

Recognizing Data Bias

With humans, we work diligently to construct safe and constructive learning environments. We design curriculums, carefully selecting materials, instructors and students to try and get the right mix of information and social dynamics. We go to all this trouble because we understand that the environment we create greatly influences the learning experience.

Machines also have a learning environment called a “corpus.” If, for example, you want to teach an algorithm to recognize cats, you expose it to thousands of pictures of cats. In time, it figures out how to tell the difference between, say, a cat and a dog. Much like with human beings, it is through learning from these experiences that algorithms become useful.

However, the process can go horribly awry. A famous case is Microsoft’s Tay, a Twitter bot that the company unleashed on the microblogging platform in 2016. In under a day, Tay went from being friendly and casual (“humans are super cool”) to downright scary, (“Hitler was right and I hate Jews”). It was profoundly disturbing.

Bias in the learning corpus is far more common than we often realize. Do an image search for the word “professional haircut” and you will get almost exclusively pictures of white men. Do the same for “unprofessional haircut” and you will see much more racial and gender diversity.

It’s not hard to figure out why this happens. Editors writing articles about haircuts portray white men in one way and other genders and races in another. When we query machines, we inevitably find our own biases baked in.

Accounting For Algorithmic Bias

A second major source of bias results from how decision-making models are designed. Consider the case of Sarah Wysocki, a fifth grade teacher who — despite being lauded by parents, students, and administrators alike — was fired from the D.C. school district because an algorithm judged her performance to be sub-par. Why? It’s not exactly clear, because the system was too complex to be understood by those who fired her.

Yet it’s not hard to imagine how it could happen. If a teacher’s ability is evaluated based on test scores, then other aspects of performance, such as taking on children with learning differences or emotional problems, would fail to register, or even unfairly penalize them. Good human managers recognize outliers, algorithms generally aren’t designed that way.

In other cases, models are constructed according to what data is easiest to acquire or the model is overfit to a specific set of cases and is then applied too broadly. In 2013, Google Flu Trends predicted almost double as many cases there actually were. What appears to have happened is that increased media coverage about Google Flu Trends led to more searches by people who weren’t sick. The algorithm was never designed to take itself into account.

The simple fact is that an algorithm must be designed in one way or another. Every possible contingency cannot be pursued. Choices have to be made and bias will inevitably creep in. Mistakes happen. The key is not to eliminate error, but to make our systems accountable through, explainability, auditability and transparency.

To Build An Era Of Cognitive Collaboration We First Need To Build Trust

In 2020, Ofqual, the authority that administers A-Level college entrance exams in the UK, found itself mired in scandal. Unable to hold live exams because of Covid-19, it designed and employed an algorithm that based scores partly on the historical performance of the schools students attended with the unintended consequence that already disadvantaged students found themselves further penalized by artificially deflated scores.

The outcry was immediate, but in a sense the Ofqual case is a happy story. Because the agency was transparent about how the algorithm was constructed, the source of the bias was quickly revealed, corrective action was taken in a timely manner, and much of the damage was likely mitigated. As Linus’s Law advises, “given enough eyeballs, all bugs are shallow.”

The age of artificial intelligence requires us to collaborate with machines, leveraging their capabilities to better serve other humans. To make that collaboration successful, however, it needs to take place in an atmosphere of trust. Machines, just like humans, need to be held accountable, their decisions and insights can’t be a “black box.” We need to be able to understand where their judgments come from and how they’re decisions are being made.

Senator Schumer worked on legislation to promote more transparency in 2024, but that is only a start and the new administration has pushed the pause button on AI regulation. The real change has to come from within ourselves and how we see our relationships with the machines we create. Marshall McLuhan wrote that media are extensions of man and the same can be said for technology. Our machines inherit our human weaknesses and frailties. We need to make allowances for that.

— Article courtesy of the Digital Tonto blog
— Image credit: Flickr

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The Keys to Changing Someone’s Mind

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The Keys to Changing Someone's Mind

GUEST POST from Greg Satell

When is the last time you changed your mind about anything substantial? Was it another person that convinced you or an unexpected experience that changed your perspective? What led you to stop seeing something one way and start seeing it in another? I will bet it does not happen often. We rarely change our minds.

Now think about how much time we spend trying to change other people’s minds. From sales pitches and political discussions, to what we are going to have for dinner and when the kids should go to bed, we put a lot of time and effort into shaping the opinions of others. Most of that is probably wasted.

The truth is that we cannot really change anyone’s mind. Only they can do that. Yet as David McRaney explains in his new book, How Minds Change, there are new techniques that can help us be more persuasive, but they don’t require brilliant sophistry or snappy rhetoric. They involve more listening than speaking, and understanding the context in which beliefs arise.

Why We Fail To Adapt

We don’t experience the world as it is, but through the context of earlier experiences. What we think of as knowledge is really connections in our brains called synapses which develop over time. These pathways strengthen as we use them and degrade when we do not. Or, as scientists who study these things like to put it, the neurons that fire together, wire together.

It’s not just our own experiences that shape us either. In fact, a series of famous experiments done at Swarthmore College in the 1950’s showed that we will conform to the opinions of those around us even if they are obviously wrong. More recent research suggests that this effect extends out to three degrees of influence, so it’s not just people we know personally, but the friends of our friends’ friends that shape how we see things.

Finally, there are often switching costs to changing our minds. Our opinions are rarely isolated thoughts, but form a basis for decisions. Once we change our minds, we need to change our actions and that can have consequences. We may need to change how we do our jobs, what we choose to buy, how we act towards others and, sometimes, who we choose to associate ourselves with.

In The Righteous Mind, social psychologist Jonathan Haidt makes the point that our beliefs become closely intertwined with our identity. They signal our inclusion in a particular “team.” That’s why contrary views can often feel like an attack. Rather than taking in new information we often feel the urge to lash out and silence the opposing voice.

Meeting The Mind Changing Threshold

As closely as we cling to our beliefs, sometimes we do change our minds. In one study that analyzed voting behavior, it was found that when up to 20% of the information that people were exposed to contradicted their beliefs, they dug in their heels and grew more certain. Beyond that, however, their resolve tended to weaken. The informational environment can deeply influence what people believe.

Their relationship to the subject matter is also important. The elaboration likelihood model (ELM) and the heuristic-systematic model (HSM) developed in the 1980s both suggest that we treat different topics in different ways. Some topics, such as those that are important to us professionally, we’re willing to invest time in exploring systematically. Others are more marginal to us and we will tend to look for shortcuts.

For example, if we are researching a business investment, we’ll want to gather facts from a variety of different sources and study them closely. On the other hand, if we’re trying to decide which craft beer to select from a large selection at a bar, we’ll rely on subtle cues such as packaging, how the beer is described or what we see others drinking.

If we want to change someone’s mind about something we need to understand their relationship to the subject matter. If they are heavily invested in it, they are unlikely to be swayed by superficial arguments. In fact, weak or purely emotive arguments may suggest to them that the opposite is true. At the same time, if someone is not very knowledgeable or motivated to learn about a topic, bogging them down with a lot of facts is likely to bore them.

Two Strategies For Persuasion

If you want to change somebody’s mind, you can follow two different kinds of approaches. The first, which can be called “topic denial”, argues the facts. The second, called “technique denial,” exposes flaws in reasoning. For example, if you want to convince a vaccine skeptic you can either cite scientific evidence or refute the form of the argument, such as pointing out that while there may be a minimal risk to taking a vaccine, the same could be said of aspirin.

While research shows that both approaches can be effective, we need to keep context in mind. If you are in a trustful environment, such as a professional or scientific setting, a fact-based topic rebuttal can often be effective. However, if you’re trying to talk your crazy uncle out of a conspiracy theory at Thanksgiving dinner, you may want to try a technique rebuttal.

In recent years a variety of methods, such as Deep Canvassing, Street Epistemology and the Change Conversation Pyramid have emerged as effective technique rebuttal methods. Interestingly, they don’t rely on any elaborate rhetorical flourishes, but rather listening empathetically, restating the opposing position in a way that shows we understand it, identifying common ground and exploring how they came to their conclusion.

The truth is that we can never truly change somebody’s mind. Only they can do that. All too often, we treat opinions as if they were artillery in a battle. Yet attacking someone’s beliefs is more likely to raise their defenses than to convince them that they are in error. Before we can convince anyone of anything, we need to first build an environment of safety and trust.

Let Empathy Be You Secret Weapon

When we want to change somebody’s minds, our first instinct is to confront their beliefs. We want to be warriors and fight for our position. Yet because people’s opinions are often a result of their experiences and social networks, countering their beliefs won’t feel to them like merely offering a different perspective, but as an attack on their identity and dignity.

That’s why we’re much better off listening and building rapport. That’s not always easy to do, because staying silent while somebody is voicing an opinion we don’t agree with can feel like a surrender. But it doesn’t have to be. In fact, if we can identify a shared value and a shared language in an opposing viewpoint, we have a powerful tool to argue our position.

The truth is that empathy isn’t absolution. In fact, it can be our secret weapon. We don’t have to agree with someone’s belief to internalize it. We all have a need to be recognized and when we take the time to hear someone out, we honor their dignity. That makes them much more willing to hear us out. Lasting change is always built on common ground.

At some point, we all need to decide if we want to make a point or make a difference. If we really care about change, we need to hold ourselves accountable to be effective messengers and express ourselves in terms that others are willing to accept. That doesn’t in any way mean we have to compromise. It simply means that we need to advocate effectively.

To do that, we need to care more about building shared purpose than we do about winning points.

— Article courtesy of the Digital Tonto blog
— Image credit: Flickr

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Making Empathy Your Secret Weapon

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GUEST POST from Greg Satell

When I first moved to Kyiv about 20 years ago, I met my friend Pavlo, who is from Belarus. Eventually our talk turned to that country’s leader, Alexander Lukashenko, and an incident in which he turned off the utilities at the US Ambassador’s residence, as well as those of other diplomats. It seemed totally outlandish and crazy to me.

“But he won,” Pavlo countered. I was incredulous, until he explained. “Lukashenko knows he’s a bastard and that the world will never accept him. In that situation all you can win is your freedom and that’s what he won.” It was a mode of thinking so outrageous and foreign to me that I could scarcely believe it.

Yet it opened my eyes and made me a more effective operator. We tend to think of empathy as an act of generosity, but it’s far more than that. Learning how to internalize diverse viewpoints is a skill we should learn not only because it helps make others more comfortable, but because it empowers us to successfully navigate an often complex and difficult world.

Identifying Shared Values

We all have ideas we feel passionately about and, naturally, we want others to adopt them. The ideas we believe in make up an important facet of our identity, dignity and sense of self. For me, as an American living in post-communist countries, the ideas embedded in democratic institutions were important and it was difficult for me to see things another way.

My conversation with Pavlo opened my eyes. Where I saw America and “the west” as a more just society, people in other parts of the world saw it as a dominant force that restricted their freedom. My big insight was that I didn’t need to agree with a perspective to understand, internalize, and leverage it as a shared value.

For example, once I was able to understand that some people saw Americans as powerful—something akin to an invading force—I was able to shed the feelings of vulnerability that arose from being in a strange and foreign land and focus on the shared value of safety in my dealings with others.

A great strategy for identifying shared values is to listen closely to what your opposition is saying. People say and do things because they believe they will be effective. Once I was able to stop dismissing Lukashenko as a corrupt thug, I was able to identify the issues surrounding safety and dominance that could be useful to me.

Building Shared Purpose

Using empathy to identify shared values is a crucial first step, but doesn’t achieve anything by itself. To move things forward, we need to build a shared purpose. Consider a famous study called the Robbers Cave Experiment, which involved 22 boys of similar religious, racial and economic backgrounds invited to spend a few weeks at a summer camp.

In the first phase, they were separated into two groups of “Rattlers” and “Eagles” that had little contact with each other. As each group formed its own identity, they began to display hostility on the rare occasions when they were together. During the second phase, the two groups were given competitive tasks and tensions boiled over, with each group name calling, sabotaging each other’s efforts and violently attacking one another.

In the third phase, the researchers attempted to reduce tensions. At first, they merely brought them into friendly contact, with little effect. The boys just sneered at each other. However, when they were tricked into challenging tasks where they were forced to work together in order to be successful, the tenor changed quickly. By the end of the camp the two groups had fallen into a friendly camaraderie.

As Francis Fukuyama writes in his recent book, “Identity can be used to divide, but it can also be used to integrate,” which is exactly what I found in my years working is foreign cultures. Once I was able to leverage shared values to create a shared purpose and began engaging in shared actions, that purpose and those actions became part of a shared identity. Yes, I was still an American, with American values and perspectives, but I became their American.

Overcoming Conflict By Designing A Dilemma

Unfortunately, building a shared purpose isn’t always possible. A simple truth is that humans build attachments to people, ideas and things. When those attachments are threatened, they will lash out. That’s why whenever we set out to make a significant impact, there will always be those who will work to undermine what we are trying to achieve in ways that are dishonest, underhanded and deceptive.

When that happens—and it always does eventually—we can get sucked into a conflict, which will likely take us off course and discredit what we’re trying to achieve. Yet, here too, developing empathy skills to identify shared values can be extremely helpful once we learn how to design a dilemma action, which puts the opponents into an impossible position.

Dilemma actions have been used for at least a century—famous examples include Gandhi’s Salt March, King’s Birmingham Campaign and Alice Paul’s Silent Sentinels—but more recently codified by the global activist, Srdja Popović. They are just as effective in an organizational context, using an opponent’s resistance against them.

One of the great things about dilemma actions is that you approach them exactly the same way you approach building allies—by identifying a shared purpose. Once you do that, you can design a constructive act rooted in that shared purpose that advances your agenda. Your opponent then has a choice: they can disrupt the act and violate the shared value or they can let it go forward and let change progress.

For example, I was once running a transformation project that was being impeded by a Sales Director hogging accounts. Although it was agreed that she would distribute her clients, she never got around to it, so I set up a meeting with a key account and one of our salespeople. When she tried to disrupt the meeting, she violated the shared value we had established, was dismissed from her position and everything fell into place after that.

Empathy Is Not Absolution

Empathy, as powerful as it can potentially be, is widely misunderstood. It is often paired with compassion in the context of creating a more beneficial workplace. That is, of course, a reasonable and worthy objective, but the one-dimensional use of the term is misleading and limits its value.

When seen only through the lens of making others more comfortable, empathy can seem like a “nice to have,” trait rather than a valuable competency and an important source of competitive advantage. It’s much easier to see the advantage of imposing your will, rather than internalizing the perspectives of others.

One thing I learned over many years living in foreign cultures is that it’s important to understand how people around you think, especially if you don’t agree with them and, as is sometimes the case, find their point of view morally reprehensible. In fact, learning more about how others think can make you a more effective leader, negotiator and manager.

Empathy is not absolution. You can internalize the ideas of others and still vehemently disagree. There is a reason that Special Forces are trained to understand the cultures in which they will operate and it isn’t because it makes them nicer people. It’s because it makes them more lethal operators.

It is only through empathy that we can understand motivations—for good or ill—and design effective strategies to build shared purpose or, if need be, design a dilemma for an opponent. To operate in an often difficult world, you need to understand your environment. That’s why building empathy skills can be like a secret weapon.

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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The Technology of Tomorrow Requires Ecosystems Today

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The Technology Of Tomorrow Requires Ecosystems Today

GUEST POST from Greg Satell

There are a number of stories about what led Hans Lipperhey to submit a patent for the telescope in 1608. Some say that he saw two children playing with lenses in his shop who discovered that when they put one lens in front of each other they could see a weather vane across the street. Others say it was an apprentice that noticed the telescopic effect.

Yet the more interesting question is how such an important discovery could have such prosaic origins. Why was it that it was at that time that somebody noticed that looking through two lenses would magnify objects and not before? How could it have been that the discovery was made in a humble workshop and not by some great personage?

The truth is that history tends to converge and cascade around certain places and times, such as Cambridge before World War I, Vienna in the 1920s or, more recently, in Silicon Valley. In each case, we find that there were ecosystems that led to the inventions that changed the world. If we are going to build a more innovative economy, that’s where we need to focus.

How The Printing Press Led To A New Era Of Science

The mystery surrounding the invention of the telescope in the early 1600s begins to make more sense when you consider that the printing press was invented a little over a century before. By the mid-1500s books were transformed from priceless artifacts rarely seen outside monasteries, to something common enough that people could keep in their homes.

As literacy flourished, the need for spectacles grew exponentially and lens making became a much more common trade. With so many lenses around, it was only a matter of time before someone figured out that combining two lenses would create a compound effect and result in magnification (the microscope was invented around the same time).

From there, things began to move quickly. In 1609, Galileo Galilei first used the telescope to explore the heavens and changed our conception of the universe. He was able to see stars that were invisible to the naked eye, mountains and valleys on the moon and noticed that, similar to the moon, Venus had phases suggesting that it revolved around the sun.

A half century later, Antonie van Leeuwenhoek built himself a microscope and discovered an entirely new world made up of cells and fibers far too small for the human eye to detect. For the first time we became aware of bacteria and protozoa, creating the new field of microbiology. The world began to move away from ancient superstition and into one of observation and deduction.

It’s hard to see how any of this could have been foreseen when Gutenberg printed his first bible. Galileo and van Leeuwenhoek were products of their age as much as they were creators of the future.

How The Light Bulb Helped To Reshape Life, Work And Diets

In 1882, just three years after he had almost literally shocked the world with his revolutionary lighting system, Thomas Edison opened his Pearl Street Station, the first commercial electrical distribution plant in the United States. By 1884 it was already servicing over 500 homes.Yet for the next few decades, electric light remained mostly a curiosity.

As the economist Paul David explains in The Dynamo and the Computer, electricity didn’t have a measurable impact on the economy until the early 1920’s — 40 years after Edison’s plant. The problem wasn’t with electricity itself, Edison quickly expanded his distribution network as did his rival George Westinghouse, but a lack of complementary technologies.

To truly impact productivity, factories had to be redesigned to function not around a single steam turbine, but with smaller electric motors powering each machine. That created the opportunity to reimagine work itself, which led to the study of management. Greater productivity raised living standards and a new consumer culture.

Much like with the printing press, the ecosystem created by electric light led to secondary and tertiary inventions. Radios changed the way people received information and were entertained. Refrigeration meant not only that food could be kept fresh, but sent over large distances, reshaping agriculture and greatly improving diets.

The Automobile And The Category Killer

The internal combustion engine was developed in the late 1870’s and early 1880’s. Two of its primary inventors, Gottlieb Daimler and Karl Benz, began developing cars in the mid-1880’s. Henry Ford came two decades later. By pioneering the assembly line, he transformed cars from an expensive curiosity into a true “product for the masses” and it was this transformation that led to its major impact.

When just a few people have a car, it is merely a mode of transportation. But when everyone has a car, it becomes a force that reshapes society. People move from crowded cities into bedroom communities in the suburbs. Social relationships change, especially for farmers who previously lived their entire lives within a single day’s horse ride of 10 or 12 square miles. Lives opened up. Worlds broadened.

New infrastructure, like roads and gas stations were built. Improved logistics began to reshape supply chains and factories moved from cities in the north—close to customers—to small towns in the south, where labor and land were cheaper. That improved the economics of manufacturing, improved incomes and enriched lives.

With the means to easily carry a week’s worth of groceries, corner stores were replaced by supermarkets. Eventually suburbs formed and shopping malls sprang up. In the US, Little League baseball became popular. With mobility combined with the productivity effects of electricity, almost every facet of life—where we lived, worked and shopped—was reshaped.

Embarking On A New Era Of Innovation

These days, it seems that every time you turn around you see some breakthrough technology that will change our lives. We see media reports about computing breakthroughs, miracle cures, new sources of energy and more. Unfortunately, very few will ever see the outside of a lab and even fewer will prove commercially viable enough to impact our lives.

Don’t get me wrong. Many of these are real discoveries produced by serious scientists and reported by reputable sources. The problem is with how science works. At any given time there are a myriad of exciting possibilities, but very few pan out and even the ones that do usually take decades to make an impact.

Digital technology is a great example of how this happens. As AnnaLee Saxenian explained in Regional Advantage, back in the 1970s and 80s, when Boston was the center of the technology universe, Silicon Valley invested in an ecosystem, which included not just corporations, but scientific labs, universities and community colleges. New England rejected that approach. The results speak for themselves.

If you want to understand the technology of tomorrow, don’t try to imagine an idea no one has ever thought of, but look at the problems people are working on today. You’ll find a vast network working on quantum computing, a significant synthetic biology economy, a large-scale effort in materials science and billions of dollars invested into energy storage startups.

That’s why, if we are to win the future, we need to invest in ecosystems. It’s the nodes that grab attention, but the networks that make things happen.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Change is Never Simple or Linear

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Change is Never Simple or Linear

GUEST POST from Greg Satell

I still remember the excitement I felt seeing Kyiv, Ukraine for the first time in 2002. I had been living in Eastern Europe for five years by that time and had the privilege of witnessing first-hand how formerly communist countries moved boldly into a new future of peace and prosperity. Still, Kyiv was different somehow, bigger, more raw and bursting with potential.

An often repeated quip at the time was, “Ukraine is like Poland in 1993… and always will be.” Unlike the Visegrad countries of Poland, Czech, Slovakia and Hungary, Ukraine had been an actual Soviet Republic and the degree of institutional and societal rot created greater challenges. Kyiv in 2002 was, in many ways, a cynical place.

Today, no one can deny that a paradigm shift has occurred. No longer seen as a corrupt backwater, Ukraine has inspired the world with its ingenuity, humanity and courage. Its president, Volodomyr Zelensky, is an international hero. Yet the transformation, while still incomplete, didn’t come easily and it has important lessons that we can learn from.

A Material Desire

In the early 2000s, Ukraine felt like a place in limbo. Ravaged by the 1998 ruble crisis and often considered to be a sub-market of Russia, most multinational companies were running their Ukrainian operations from Moscow. The highly publicized murder of journalist Georgiy Gongadze in 2000 just added to the feeling that the country was stuck in a hopeless limbo.

When I first arrived, there was a palpable sense of political apathy. Many Ukrainians traveled to Europe and, with its neighbor Poland ascending to the EU, were more than aware that they were being left behind. Still, it didn’t seem like anything could be done about the corrupt powers that ruled the country, so why worry about things that didn’t concern you?

That began to change in 2004, when a relatively boring technocratic reformer named Viktor Yushchenko, who was credited with taming hyperinflation as a central banker and helping to improve the economy as Prime Minister, emerged as the opposition candidate for President. Powerful interests opposed his reforms. He was poisoned, leaving his face disfigured. Many expected his candidacy to end there, but it transformed him into an inspirational leader.

The forces backing his opponent, an almost cartoonish thug named Viktor Yanukovych, tried to falsify the election, which led to the Orange Revolution. I remember that, at first, the effort often seemed futile. But we persevered and the Supreme Court of Ukraine nullified the falsified election results. Against seemingly all odds, Yushchenko rose to the presidency.

A Failure To Survive Victory

We had won, or so we thought. The rightful candidate was elected, justice was done and it seemed like a new era had dawned. Yet soon it became clear that things were not going well. The unity of Yushchenko’s coalition broke down and infighting ensued. Planned reforms stalled in a morass of corruption and incompetence. The financial crisis at the end of 2008 put the last nail in the coffin.

In 2010, Victor Yanukovych, the same man we marched against, rose to the presidency. He was even worse than we had feared. He changed the Constitution to grab more power and threw his opponent, Yulia Tymoshenko, in jail to cripple the opposition. Corruption reached new heights (experts estimate that the regime looted as much as $100 billion—an amount almost equal to the entire GDP of Ukraine).

Things came to a head when Yanukovych backed out of a trade agreement with the EU. It was the final straw. It is one thing to steal, to make a mockery of the rule of law and to run the country far below any reasonable standard of governance. But the prospect of EU integration had come to symbolize inclusion into Europe and a chance to, someday, live a normal life. People once again took to the streets in what came to be called the Euromaidan protests.

The regime fought back, but to little avail. Riot police attacked, yet more people came to Kyiv’s central square, known as the “Maidan.” Yanukovych passed a law outlawing the protests and even more came. Things escalated and the regime started shooting the protestors. Soon there were Molotov cocktails, helmets, and improvised shields. In the end more than 100 people were dead in the streets.

The world took notice and the diplomats came. Meanwhile, away from the cameras, other meetings were held in Parliament. The oligarchs, facing sanctions against their western assets, and even Yanukovych’s allies in his own party, had enough. Suddenly bereft of any support, the corrupt strongman fled from the country. An interim government was announced and Petro Poroshenko was elected president later that Spring.

The Rise Of A Consciousness Based On Shared Values

The Orange Revolution got its name because Orange was the campaign color of Yushchenko’s party, Our Ukraine. It was about changing who was in power in the hopes that he could change things. That was our mistake. You can never base a transformation in any one person, policy or program. It always needs to be rooted in shared values.

“In 2015 we were fighting for an idea. That’s why 2015 was different,” Mustafa Nayem, who initiated the protests, would later tell me. They were called “Euromaidan,” because they were about values, specifically European Values. It was a realization that the material aspirations could not be met without a fundamental change in beliefs and how the country saw itself.

“Immediately after Maidan [in 2005], all the people went home and they calmed down,” Nayem told me. “We lost the chance to push the government towards some changes. In 2013, and after Maidan in 2014, many people are still angry, they’re still active, they’re still pushing. And the inner process of these protests is still proceeding. We have this conversion of civil society.”

These events came to be known as the Revolution of Dignity, because it was the moment that the Ukrainian people demanded to have their sovereignty as an independent country recognized, no matter what the cost. That’s what led Putin to annex Crimea, invade Donbas in 2014 and then the entire country in 2022.

To Shift Opinions You Need To Shift Networks

From the outside, Ukraine’s story can seem like a real life version of the hero’s journey, in which an ordinary person is called to greatness and tested in some profound way which leads to a transformation. Yet Volodymyr Zelensky is not Luke Skywalker, Vladimir Putin is not Darth Vader and Russia does not dominate the universe.

While it is true that Zelensky has a particular set of talents that earlier leaders, such as Viktor Yushchenko, lacked, he has been shaped by context at least as much as he has shaped events. Not only is he a member of the first Ukrainian generation to have little memory or nostalgia for the Soviet Union, he is operating in an ecosystem prepared by two revolutions.

To truly shape events, you must shape networks. That is why Russia is failing and Ukraine is succeeding. One thing I noticed living in both countries is that Ukrainians had a deep desire to connect to the world, while Russians were much more suspicious, fearing that taking in elements of other cultures would corrupt their own.

It is networks of unseen connections that lead to transformation and change. You can’t overpower, you need to attract small groups, loosely connected and united by shared purpose to achieve great things. That never happens in a straightforward manner. We live in a world not of linear cause and effect, but of complex ecosystems, which we need to grow and nurture if they are to achieve their full potential.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Focus on Shaping Networks Not Opinions

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Focus on Shaping Networks Not Opinions

GUEST POST from Greg Satell

Anybody who has ever been married or had kids knows how difficult it can be to convince even a single person. To persuade dozens or hundreds — much less thousands or millions — to change their mind about something important seems like a pipe dream. Yet that doesn’t stop people from spending significant time and energy to do just that.

In fact, there is a massive industry dedicated to shaping opinions. Professionals research attitudes, identify “value propositions,” craft messages and leverage “influencers” in the hopes that they can get people to change their minds. Yet despite the billions of dollars invested each year, evidence of consistent success remains elusive.

The truth is that the best indicator of what people do and think is what the people around them do and think. Instead of trying to shape opinions, we need to shape networks. That’s why we need to focus our efforts on working to craft cultures rather than wordsmithing slogans. To do that, we need to understand the subtle ways we influence each other.

The Influencer Myth

Malcolm Gladwell, blockbuster book, The Tipping Point, popularized his “Law of the Few,” which he stated as: “The success of any kind of social epidemic is heavily dependent on the involvement of people with a particular and rare set of social gifts.” This reenergized earlier ideas about opinion leaders, the supposedly secret people who somehow have outsize influence on others.

Perhaps not surprisingly, the communications industry quickly jumped to promote the idea of secret “influentials” living among us. Clearly, if you’re looking to shape opinions, being able to identify such people would be incredibly valuable and, it goes without saying, firms who could claim an expertise in leveraging those powers could earn outsized fees.

Yet the actual evidence that these people actually exist is incredibly thin. Even the original opinion leader research found that influence was highly contextual. In a more recent study of e-mails, it was found that highly connected people weren’t necessary to produce a viral cascade. In another, based on Twitter, it was found that they aren’t even sufficient. So called “Influentials” are only slightly more likely to produce viral chains.

Duncan Watts, co- author of both studies and a pioneer in the science of networks told me, “The Influentials hypothesis, is a theory that can be made to fit the facts once they are known, but it has little predictive power. It is at best a convenient fiction; at worst a misleading model. The real world is much more complicated.”

The Framingham Heart Study

While there is little evidence to suggest that there are special people secretly influencing our attitudes and decisions, there is abundant evidence that completely normal people exert influence all the time. We may ask our nephew about what app to download, or a co-worker about where to go for dinner. We all have people in our lives that we go to for advice about particular things.

Decades of scientific research suggests that the best indicator of what we think and do is what the people around us think and do. A famous series of studies performed in the 1950s—replicated countless times since then—found that when confronted with a overwhelming opinion, people will conform to the majority even if it is obviously wrong.

More recent research indicates that the effect applies not only to people we know well, but that extends even to second and third-degree relationships. So not only our friends, but the friends of their friends as well—many of whom we may have never met—influence us. This effect not only applies to our opinions, but also things like smoking and obesity and behaviors related to cooperation and trust.

The evidence is, in fact, overwhelming. Working to shape opinions is bound to be a fruitless exercise unless we are able to shape the networks in which ideas, attitudes and behaviors form. Fortunately, there are some fairly straightforward ways to do that.

Starting With A Majority

When we’re passionate about an idea, we want it to spread. We want to tell everyone, especially, for psychological reasons which are not quite clear to me, the opposition. There is some strange quirk embedded in human nature that makes us want to try to convince those who are most hostile to the proposition. We want to convince skeptics.

As should be clear by now, that’s a very bad idea. An idea in its early stages is, almost by definition, not fully formed. It hasn’t been tested and doesn’t have a track record. You also lack experience in countering objections. Taking an idea in its infancy into hostile territory almost guarantees failure.

The simple alternative is to start with a majority, even if that majority is only three people in a room of five. You can always expand a majority out, but once you’re in the minority you’re going to get immediate pushback. Go out and find people who are as enthusiastic as you are, who are willing to support your idea, to strengthen it and help troubleshoot.

That’s how you can begin to gain traction and build a sense for shared purpose and mission. As you begin to work out the kinks, you can embark on a keystone project, show some success, build a track record and accumulate social proof. As you gain momentum, you will find that there is no need to chase skeptics. They will start coming to you.

Small Groups, Loosely Connected, But United By A Shared Purpose

The biggest misconception about change is that once people understand it, they will embrace it and so the best way to drive change forward is to explain the need for change in a convincing and persuasive way. Change, in this view, is essentially a communication exercise and the right combination of words and images is all that is required.

Even assuming that it is practical to convince people that way, by the same logic they can just as easily have their mind changed right back by counter-arguments. So even successful shaping opinions is, at best, a temporary solution. Clearly, if we are going to bring about sustainable change, we need to shape not just opinions, but networks as well.

In my book Cascades, I explained how small groups, loosely connected but united by a shared purpose drive transformational change. It happens gradually, almost imperceptibly, at first. Connections accumulate under the surface, barely noticed, as small groups slowly begin to link together and congeal into a network. Eventually things hit a tipping point.

The good news is that decades of research suggest that tipping point is much smaller than most people think. Everett Rogers’ “S-curve” research estimated it at 10%-20% of a system. Erica Chenoweth’s research calculated the tipping point to be at 3.5% of a society. Damon Centola at the University of Pennsylvania suggests the tipping point to be at 25% of an organization.

I would take each of these numbers with a grain of salt. The salient point here is that nowhere does the evidence suggest we need anything close to 51% support for change to take hold. Our job as leaders is to cultivate networks, help them connect and inspire them with a sense of shared values and shared purpose.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Three Reasons Change Efforts Fail

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Three Reasons Change Efforts Fail

GUEST POST from Greg Satell

There’s no question we have entered a transformative age, with major shifts in technology, resources, demography and migration. Over the next decades, we will have to move from digital from post-digital, from carbon to zero-carbon and from the Boomer values to those of Millennials and Zoomers. Migration will strain societies’ social compact.

Unfortunately, we’re really bad at adapting to change. We’ve known about the climate threat for decades, but have done little about it. The digital revolution, for all the hoopla, has been a big disappointment, falling far short of its promise to change the world for the better. Even at the level of individual firms, McKinsey finds that the vast majority of initiatives fail.

One key factor is that we too often assume that change is inevitable. It’s not. Change dies every day. New ideas are weak, fragile, and in need of protection. If we’re going to bring about genuine transformation, we need to take that into account. The first step is to learn the reasons why change fails in the first place. These three are a good place to start.

1. A Flawed Idea

One obvious reason that change fails is that the idea itself is flawed in some way. Barry Libenson found this out when he was hired to be CIO at the industrial conglomerate Ingersoll Rand. It was his first CIO role and Barry was eager to please the CEO, who he saw as a mentor. So he agreed to aggressive very performance targets for modernizing systems.

Yet while Barry was being financially incentivized to upgrade technology, each of the division leaders were financially incentivized to maximize profit growth. Every dollar they invested in modernizing systems would eat into their performance bonus. Perhaps not surprisingly, Barry’s modernization program didn’t go as well as he’d hoped.

There are a number of tools that can help to troubleshoot ideas and uncover flaws. Pre-mortems force you to imagine how a project could fail. Red Teams set up a parallel group specifically to look for flaws. Howard Tiersky, CEO of the digital transformation agency From Digital and author of the Wall Street Journal bestseller Winning Digital Customers, often uses de Bono’s Six Thinking Hats to help the team take different perspectives.

Most of all, we need to come to terms with the reality that our ideas are always wrong. Sometimes they’re off by a little and sometimes they’re off by a lot, but they’re always wrong, so we always need to be on the lookout for problems. As the physicist Richard Feynman put it.“The first principle is that you must not fool yourself — and you are the easiest person to fool. So you have to be very careful about that.”

2. Failure To Build Trust

Proposed in 1983 by Ira Magaziner, the Rhode Island’s Greenhouse Compact is still considered to be an impressive policy even today, 40 years later. In fact, the bipartisan CHIPS Act is based on the same principle, that targeted, strategic government investments can help simulate economic development in the private sector.

The plan in Rhode Island was to establish four research centers or “greenhouses” throughout the state to help drive development in new technologies, like robotics, medicine and thin film materials, as well as existing industries in which the state had built-in advantages, such as tourism, boat-building and fishing. It quickly gained support among the state’s elite

Yet things quickly soured. There were a number of political scandals that reduced faith in Rhode Island’s government and fed into the laissez-faire zeitgeist of the Reagan era. Critics called the plan “elitist,” for taxing “ordinary” citizens to subsidize greedy corporations. When the referendum was held, it plan got less than a fifth of the vote.

Magaziner’s mistake — one he would repeat with the healthcare plan during the Clinton Administration—was ignoring the need to build trust among constituencies. Getting the plan right is never enough. You need to methodically build trust and support as you go.

3. Identity and Dignity

One of the biggest mistakes change leaders make is assuming that resistance to change has a rational basis. They feel that if they listen to concerns and address them, they will be able to build trust and win over skeptics. Unfortunately, while doing those things is certainly necessary for a successful change effort, it is rarely sufficient.

The simple fact is that human beings form attachments to people, ideas and things and when they feel those attachments are threatened, it offends their identity, dignity and sense of self. This is the most visceral kind of resistance. We can argue the merits of a particular idea and methodically build trust, but we can’t ask people to stop being who they think they are.

Don’t waste your time trying to convince the unconvincible. Your efforts will be very unlikely to succeed and very likely to exhaust and frustrate you. The good news is that irrational resistors, if left to their own devices, will often discredit themselves eventually. You can also speed up the process by designing a dilemma action.

What can be hardest about change, especially when we feel passionately about it, is that at some point, we need to accept that others will not embrace it and we will have to leave some behind. Not every change is for everybody. Some will have to pursue a different journey, one to which they can devote their passions and seek out their own truths.

Change Is Not Inevitable

People like to quote the ancient Greek philosopher Heraclitus, who said things like “the only constant is change” and “no man ever steps in the same river twice, for it’s not the same river and he’s not the same man.” They’re clever quotes and they give us confidence that the change we seek is not only possible, but inevitable.

Yet while change in general may be inevitable, the prospects for any particular change initiative are decidedly poor and the failure to recognize that simple fact is why so many transformation efforts fall short. The first step toward making change succeed is to understand and internalize just how fragile a new, unproven initiative really is.

To bring genuine change about you can’t expect to just push forward and have everyone fall in line. No amount of executive sponsorship or program budget will guarantee victory. To move forward, you will need to listen to skeptics, identify and fix flaws in your idea to methodically build trust. Even then, you will have to outsmart those who have an irrational lust to kill change and who act in ways that are dishonest, underhanded and deceptive.

Change is always, at some level, about what people value. That’s why to make it happen you need to identify shared values that reaffirm, rather than undermine, people’s sense of identity. Recognition is often a more powerful incentive than even financial rewards. In the final analysis, lasting change always needs to be built on common ground.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Bridging Differences to Drive Creativity and Innovation

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Bridging Differences to Drive Creativity And Innovation

GUEST POST from Greg Satell

I have a friend who was once ambushed on a TV show panel. Being confronted with a clearly offensive remark, she was caught off-guard, said something that was probably unwise (but not untrue or unkind), and found herself at the center of a media-driven scandal. It would cost her enormously, both personally and professionally.

I often think about the episode and not just because it hurt my friend, but also because I wonder what I would have done if put in similar circumstances. My friend, who is black, Muslim and female, is incredibly skilled at bridging differences and navigating matters of race, gender and religion. If she fell short, would I even stand a chance?

We are encouraged to think about matters of diversity in moral terms and, of course, that’s an important aspect. However, it is also a matter of developing the right skills. The better we are able to bridge differences, the more effectively we can collaborate with others who have different perspectives, which is crucial to becoming more innovative and productive.

The Challenge Of Diversity

There is no shortage of evidence that diversity can enhance performance. Researchers at the University of Michigan found that diverse groups can solve problems better than a more homogeneous team of greater objective ability. Another study that simulated markets showed that ethnic diversity deflated asset bubbles.

While those studies merely simulate diversity in a controlled setting, there is also evidence from the real world that diversity produces better outcomes. A McKinsey report that covered 366 public companies in a variety of countries and industries found that those which were more ethnically and gender diverse performed significantly better than others.

However, it takes effort to reap the benefits of diversity. Humans are naturally tribal. In a study of adults that were randomly assigned to “leopards” and “tigers,” fMRI studies noted hostility to out group members. Similar results were found in a study involving five year-old children and even in infants. Group identification, even without any of the normal social cues, is enough to produce bias.

The innate distinctions we make regarding each other carry over to work environments. When researchers at Kellogg and Stanford put together groups of college students to solve a murder mystery, teams made up of students from the same sorority or fraternity felt more successful, even though they performed worse on the task than integrated groups.

We rarely welcome someone who threatens our sense of self. So those outside the dominant culture are encouraged to conform and are often punished when they don’t. They are less often invited to join in routine office socializing and promotions are less likely to come their way. When things go poorly, it’s much easier to blame the odd duck than the trusted insider.

Group Identity And Individual Dignity

In western civilization, since at least the time of Descartes, we have traditionally thought in rational terms about how humans behave. We tend to assume that people examine facts to make judgments and that any disputes can be overcome through discussion and debate, through which we will arrive at an answer that is objectively correct.

Yet what if we actually did things in reverse, intuitively deciding what was right and then coming up with rational explanations for how we feel? Discussion and debate wouldn’t achieve anything. If rational arguments are merely explanations of deeply held intuitions, the “arguments” from the other side would seem to be downright lies or just crazy.

In The Righteous Mind, social psychologist Jonathan Haidt points to decades of evidence that suggest that is exactly how we do things. We rely on social intuitions to make judgments and then design logic to explain why we feel that way. He also makes the point that many of our opinions are a product of our inclusion in a particular group.

Hardly the product of cold logic, our opinions are, in large part, manifestations of our identity. Our ideas are not just things we think. They are expressions of who we think we are.

Talking Past Each Other

Clearly, the way we tend to self-sort ourselves into groups based on identity will shape how we perceive what we see and hear, but it will also affect how we share and access data. Recently, a team of researchers at MIT looked into how we share information — and misinformation — with those around us. What they found was troubling.

When we’re surrounded by people who think like us, we share information more freely because we don’t expect to be rebuked. We’re also less likely to check our facts, because we know that those we are sharing the item with will be less likely to inspect it themselves. So when we’re in a filter bubble, we not only share more, we’re also more likely to share things that are not true. Greater polarization leads to greater misinformation.

The truth is that we all have a need to be recognized and when others don’t share a view that we feel strongly about, it offends our sense of dignity. The danger, of course, is that in our rapture we descend into solipsism and fail to recognize the dignity of others. That can lead us to dangerous and ugly places.

In Timothy Snyder’s masterful book Bloodlands, which explores the mass murders of Hitler and Stalin, the eminent historian concludes that the reason that humans can do unspeakable things to other humans is that they themselves feel like victims. If your very survival is at stake, then just about anything is warranted and cruelty can seem like justice.

Once our individual dignity becomes tied to our group identity, a different perspective can feel like more than just an opposing opinion, but a direct affront and that’s what may have precipitated the public attack on my friend. The verbal assault was probably motivated by her assailant’s need to signal inclusion in an opposing tribe.

Building Shared Identity And Purpose

Our identity and sense of self drives a lot of what we see and do, yet we rarely examine these things because we spend most of our time with people who are a lot like us, who live in similar places and experience similar things. That’s why our innate perceptions and beliefs seem normal and those of others strange, because our social networks shape us that way.

As we conform to those around us, we are setting ourselves apart from those who are shaped by different sets of experiences. While there is enormous value to be unlocked by integrating with diverse perspectives, it takes work to be able to bridge those differences. What we hear isn’t always what others say and what we say isn’t what others always hear.

In his book, Identity, political scientist Francis Fukuyama explains that our identities aren’t fixed, but develop and change over time. In fact, we routinely choose to add facets to our identity, while shedding others, changing jobs, moving neighborhoods, breaking off some associations as we take on others. “Identity can be used to divide, but it can and has also been used to integrate,” Fukuyama writes.

Yet integrating identities takes effort. We first need to acknowledge that our truth isn’t the only truth and that others, looking at the same facts, can honestly come to different conclusions than we do. We need to suspend immediate judgment and devote ourselves to a common undertaking with a shared sense of mission and purpose.

This is no easy task. It takes significant effort. However, it is at this nexus of identity and purpose that creativity and innovation reside, because when we learn to collaborate with others who possess knowledge, skills and perspectives that we don’t, new possibilities emerge to achieve greater things.

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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We Must Stop Worshiping Algorithms

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We Must Stop Worshiping Algorithms

GUEST POST from Greg Satell

In 1954 the economist Paul Samuelson received a postcard from his friend Jimmie Savage asking, “ever hear of this guy?” The ”guy” in question was Louis Bachelier, an obscure mathematician who wrote a dissertation in 1900 that anticipated Einstein’s famous paper on Brownian motion published five years later.

The operative phrase in Bachelier’s paper, “the mathematical expectation of the speculator is zero,” was as powerful as it was unassuming. It implied that markets could be tamed using statistical techniques developed more than a century earlier and would set us down the path that led to the 2008 financial crisis.

For decades we’ve been trying to come up with algorithms to help us engineer our way out of uncertainty and they always fail for the same reason: the world is a messy place. Trusting our destiny to mathematical formulas does not eliminate human error, it merely gives preference to judgements encoded in systems beforehand over choices made by people in real time.

The False Promise Of Financial Engineering

By the 1960s a revolution in mathematical finance, based on Bachelier’s paper and promoted by Samuelson, began to gain momentum. A constellation of new discoveries such as efficient portfolios, the capital asset pricing model (CAPM) and, later, the Black-Scholes model for options pricing created a standard model for thinking about economics and finance.

As things gathered steam, Samuelson’s colleague at MIT, Paul Cootner, compiled the most promising papers in a 500-page tome, The Random Character of Stock Market Prices, which became an instant classic. The book would become a basic reference for the new industries of financial engineering and risk management that were just beginning to emerge at the time.

However, early signs of trouble were being ignored. Included in Cootner’s book was a paper by Benoit Mandelbrot that warned that there was something seriously wrong afoot. He showed, with very clear reasoning and analysis, that actual market data displayed far more volatility than was being predicted. In essence, he was pointing out that Samuelson and his friends were vastly underestimating risk in the financial system.

Leading up to the Great Recession, other warning signs would emerge, such as the collapse of LTCM hedge fund in 1998 and of Enron three years later, but the idea that mathematical formulas could engineer risk out of the system endured. The dreams turned to nightmares in 2008, when the entire house of cards collapsed into the worst financial crisis since the 1930s.

The Road To Shareholder Value

By 1970, Samuelson’s revolution in economics was well underway, but companies were still run much as they were for decades. Professional managers ran companies according to their best judgment about what was best for their shareholders, customers, employees and the communities that they operated in, which left room for variance in performance.

That began to change when Milton Friedman, published an Op-Ed in The New York Times, which argued that managers had only one responsibility: to maximize shareholder value. Much like Bachelier’s paper, Friedman’s assertion implied a simple rule-of-thumb with only one variable to optimize for, rather than personal judgement, should govern.

This was great news for people managing businesses, who no longer had to face the same complex tradeoffs when making decisions. All they had to worry about was whether the stock price went up. Rather than having to choose between investing in factories and equipment to produce more product, or R&D to invent new things, they could simply buy back more stock.

The results are now in and they are abysmal. Productivity growth has been depressed since the 1970s. While corporate profits have grown as a percentage of GDP, household incomes have decoupled from economic growth and stagnated. Markets are less free and less competitive. Even social mobility in the US, the ability for ordinary people to achieve the American dream, has been significantly diminished.

The Chimera Of “Consumer Welfare”

The Gilded Age in America that took place at the end of the 19th century was a period of rapid industrialization and the amassing of great wealth. As railroads began to stretch across the continent, the fortunes of the Rockefellers, Vanderbilts, Carnegies and Morgans were built. The power of these men began to rival governments.

It was also an era of great financial instability. The Panic of 1873 and the Panic of 1893 devastated a populace already at the mercy of the often avaricious tycoons who dominated the marketplace. The Sherman Antitrust Act of 1890 and the Clayton Antitrust Act of 1914 were designed to re-balance the scales and bring competition back to the market.

For the most part they were successful. The breakup of AT&T in the 1980s paved the way for immense innovation in telecommunications. Antitrust action against IBM paved the way for the era of the PC and regulatory action against Microsoft helped promote competition in the Internet. American markets were the most competitive in the world.

Still, competition is an imprecise term. Robert Bork and other conservative legal thinkers wanted a simple, more precise standard, based on consumer welfare. In their view, for regulators to bring action against a company, they had to show that the firm’s actions raise the prices of goods or services.

Here again, human judgment was replaced with an algorithmic approach that led to worse outcomes. Over 75% of industries have seen a rise in industry concentration levels since the late 1990s, which has helped to bring about a decline in business dynamism and record income inequality.

The Chimera Of Objectivity

Humans can be irrational and maddening. Decades of research have shown that, when given the exact same set of facts, even experts will make very different assessments. Some people will be more strict, others more lenient. Some of us are naturally optimistic, others are cynics. A family squabble in the morning can affect the choices we make all day.

So it’s not unreasonable to want to improve quality and reduce variance in our decision making by taking a more algorithmic approach by offering clear sets of instructions that hold sway no matter who applies them. They promise to make things more reliable, reduce uncertainty and, hopefully, improve effectiveness.

Yet as Yassmin Abdel-Magied and I explained in Harvard Business Review, algorithms don’t eliminate human biases, they merely encode them. Humans design the algorithms, collect the data that form the basis for decisions and interpret the results. The notion that algorithms are purely objective is a chimera.

The problem with algorithms is that they encourage us to check out, to fool ourselves into thinking we’ve taken human error out of the system and stop paying attention. They allow us to escape accountability, at least for a while, as we pass the buck to systems that spit out answers which affect real people.

Over the past 20 or thirty years, we’ve allowed this experiment to play out and the results have been tragic. It’s time we try something else.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini (NanoBanana)

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