Certainty Archive

Decision Making with Computers

As our information, analysis and decisions become uncertain, computers become less effective as decision-making tools.

Chess is a relatively easy decision-making task for computers. Thus, historically, the defeat of Garry Kasparov by Deep Blue was inconsequential when we consider computers still have problems with Go and Poker. The question is, “Why?”

The article, “3 Humans + 1 Computer = Best Prediction” (Harvard Business Review, May 2013 edition) by Matthias Seifert and Allègre Hadida, gives excellent insight into this question. Pragmatically, the answer will help us use computers better as tools in our decision-making. Their conclusion is that it’s a matter of certainty, certainty relative to our information, analysis and decisions.

A wealth of historical information generally represents high informational certainty. Knowing how to analyze this information to form conclusions represents high analytical certainty. Knowing how these conclusions form a decision represents high decision-making certainty. Another way to look at certainty is structure. The more structured and logical the information, analysis and decision are the more effective a computer becomes as our tool.

For example, introducing a proven product into a similar market will have a wealth of historical data, of experience in interpreting that data, and of decisions to make from those interpretations. Conversely, introducing new, very different products in a dissimilar market won’t have this certainty. Computers help more in the first situation than they do in the second.

Thus, computers will be less helpful when:

  • Information is scarce or highly variable without a discernible pattern
  • Information produces many divergent conclusions
  • Conclusions don’t present a clear cut decision

The problem is that we have a tendency to ascribe much more help to computer models than we should in these situations. We need to remember that no matter what the model says, we most likely have more experience than the computer.


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IncompetenceConfidence frequently indicates incompetence. However, leadership often requires confidence. Since people often fear uncertainty, they naturally gravitate to people who provide certainty, and confidence is a form of certainty. We can partially resolve this paradox by asking, “Is the person confident or merely being confident?” This question allows us to see confidence as a psychological weapon of leadership.

In school, we learn debate is rooted in arguments supported by evidence, an objective battle won by stronger facts and arguments. In real-life, we learn it’s more of an emotional contest. Political debates are excellent examples, but even our daily work environments contain examples.

Again, it’s more than good emotions battling bad emotions because people frequently don’t behave the way they claim they do. For instance, people say they value trust and honesty, but in reality, eloquence trumps both. In the end, conviction is often more potent than logic.

Confidence is a form of conviction about outcomes. Martyrs are examples of the power behind convictions. Someone willing to die for what something influences us immensely. Therefore, in many business debates, conviction around weak arguments and facts can easily overrun strong but hesitant, hedging ones. Moreover, since how we feel about the messenger influences how we interpret the message (more), people, especially leaders, can easily influence us if they have conviction and a good relationship with us . . . even when the facts contradict what they say. We sometimes experience this at work when we say someone has great will or will power.

We protect ourselves by being aware of the power confidence holds over us. Raising this to a conscious level is the key. This is true for many subliminal influences. So, next time you run into confidence, ask yourself “Are they using confidence as a smoke screen for incompetence?”


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Faith MoneyWhen I read articles like “Toss a Coin” (The Economist, January 12, 2013 edition), I’m reminded that our economy relies on faith. After all, as the article indicates, the U.S. Treasury prints money to satisfy its debts.

Of course, it prints purposefully to avoid the extremes of inflation and contraction. If the Treasury did not print money, our economy would slowly stop as our population expanded. It’s analogous to adding more oil to an ever-growing car engine so it won’t lock up.

However, the money is simply paper. Nothing tangible supports it. For instance, we can’t exchange dollars for gold. Only the U.S. Government supports it (“This note is legal tender for all debts, public and private”), and our faith supports the government. Since this seems so certain, it’s tough to see this as faith until we experience its loss.

For me, this occurred in the last two weeks of 1989 when visiting Poland for familial reasons. The Communists were transferring power to a democratic government on New Year’s Day. In those two weeks, the Polish zloty went from 3,000/U.S. dollar to 10,000. Knowing we were Americans, cab drivers began demanding payment in U.S. dollars; faith had vanished.

The importance of this prompts the question: How can we apply rationale to something rooted in faith? Do we rationalize religion? This is why neoclassical economics faces the challenge from behavioral economics. It incorporates emotions of which faith is a form. It means business is uniquely human not objective. It’s faith in each other with the U.S. Government (“We the People”) merely a conduit for that faith. Consequently, this dual anchor of people and faith makes business . . . well . . . personal.

What happens when we lose faith in each other?


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This entry is part 11 of 15 in the series Creative Innovation

Business prizes quantification; yet, ironically, it restricts creativity and innovation in two ways:

  • Encouraging electrical activity in our brains which restricts idea generation
  • Compelling people to confine their ideas to the quantifiable ones

Evangelia G. Chrysikou’s article “Put Your Creative Brain to Work” (Scientific American Mind, July/August 2012 edition, pgs: 26-27) summarizes the body of research to date by saying “idea generation is associated with a state of lower cognitive control” and

. . . generating novel applications for objects also seems to benefit from less filtering of knowledge and experiences, which enables people to consider a greater variety of possible answers.

Essentially, high cognitive control of our brain emits different electrical waves (beta) than low cognitive control (alpha) does. In Heidi K. Gardner’s article, “Coming Through When It Matters Most” (Harvard Business Review, April 2012 edition), we find quantification correlates to people’s need for certainty and conservatism by writing:

In high pressure situations . . . [people] support their responses with hard, usually quantitative, evidence instead of anecdotes and comparisons . . . Enthusiasm for innovation and improvisation gives way to concern for strict professionalism and covering all the basis.

My previous post, “Knowledge States”, helps us see the restrictive nature of quantification by the amount of knowledge we filter from the problem when we do so. This is partially why altering our normal problem-solving process (i.e. don’t worry about quantifying the problem or aspects of it) can be such an effective problem-solving technique.

Thus, the focus on numbers not only alters us physiologically in terms of the electrical waves our brains emit but also mentally in terms of compelling us to filter out unquantifiable knowledge that might contain the solution. Let’s face reality: problems are like squirrels. Neither goes away simply because we cannot quantify them.


Related posts:


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This entry is part 2 of 8 in the series Relationship Building Technique

We often don’t learn the value of listening techniques in building relationships. Consequently, people might not realize we are listening; this needs to occur to build relationships.

Closed questions encourage specific or limited responses. For answers, they usually require one word, short phrases or a response from a menu of possibilities. Often, they begin with the words, “Who,” “How,” “What,” “Where” and “When.” “Yes” and “No” are often typical responses.

Even though many discount their value, when combined with other listening techniques, closed questions become extremely valuable in building relationships. They clarify specifics for us, pinpoint the facts, verify what we heard, nail down agreements and commitments, and test whether we can move.

Some examples include:

  • Are you going out to the plant? (Yes/No)
  • Which color do you want? (Facts)
  • You want me to call the vendor . . . right? (Verification)
  • Is seems you’re saying [X], correct? (Verification)
  • Would today, tomorrow or the next day be better? (Menu)
  • Do you agree? (Agreement)
  • Will you help me? (Commitment)
  • Do you need to tell me anything before we move on? (Testing)
  • Is there anything else I need to cover? (Testing)

From a relational perspective, closed questions convey the feeling that you:

  • Have a purpose for your conversation
  • Grasp the details
  • Understand them
  • Respect their time by getting to specifics

The effect of closed questions is to encourage people to:

  • Conclude that you’re listening and digesting
  • Focus and sort through fuzziness
  • Shorten their answers
  • Clarify agreements and commitments

Closed questions have downsides. They can make discussions feel every interrogative and restrictive if used alone. Nevertheless, when integrated with other listening techniques they can reduce misunderstandings, demonstrate that you’re listening and build relationships.


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The Nature of RankingsEven though rankings are extremely subjective, they seduce us as strongly as the sirens did sailors in Greek mythology. Consequently, we often wreck ourselves on the rocky shores of fantasy island.

In order to understand the lure of rankings, we need to understand the lure of numbers. When we quantify something, it becomes easier to grasp. However, easier doesn’t mean that what we are grasping is real. It’s often easier to understand what we want to believe than it is to understand reality. For example, in reality a woman’s measurements don’t tell us much about her, but that doesn’t prevent them from triggering our fantasies.

Applying this illusionary power to rankings, they tap into our insecure desires for:

  1. Simplifying a complex world
  2. Defining limits to large or limitless knowledge pools
  3. Quantifying the unquantifiable
  4. Delivering certainty in an uncertain world

Rankings perform complex thought for us by determining which is better by deciphering many, many variables. They imply we can get by on much less knowledge by giving importance to the top ten rather than the top million or billion. Their parameters and measurements are subjectively determined, trying to measure something that normally is immeasurable. Finally, as implied above, the quantification inherent in rankings provides certainty; “these are the important ones and that’s it.”

For instance, consider these Google searches:

“Top 10” = 743 million results
“Top 100” = 1,083 million
“Top 1,000” = 46 million
“Top 10,000” = 17 million
“Top 100,000” = 2 million
“Top 1,000,000” = .6 million
“Top 1,000,000,000” = 5,250

Clearly, our focus is on the simple with limits; so, the problem is this: How are we going to ever appreciate the billions of unique people, places, creatures and things in this universe if we’re so focused on the top ten?


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The article, Now You Know, in the May 28, 2011 edition of The Economist discussed a study published in Cognition by Elizabeth Bonawitz of the University of California, Berkeley, and Patrick Shafto of the University of Louisville regarding the directing of children in their play. The conclusion is that prior explanation of how to play inhibits exploration and discovery.

Developmentally, businesses, through their everyday managerial practices, tend to instill a resistance to change in their people. They do this by excessively directing their people what to do. This direction not only comes via communications from managers but also procedures managers established. Consequently, employees don’t need to think; they just do as told.

As with any task, practice reduces anxiety of doing it. Uncertainty is no different. To become more accepting and adapting of change, employees need exposure to uncertainty. They need to explore and discover. Reiterated more pragmatically, they need to try and err. However, this requires time and money which is intolerable in most business cultures.

Therefore, managers need to look for tasks and projects that require thinking, exploring and discovering by their employees.  For example, assigning tasks requiring unique customer solutions would help. This could mean simply writing a letter to address a unique customer inquiry. Tasks involving working with people of different personality types work too. Creating a new process or set of procedures is good. Any task where the method or solution isn’t pre-defined or one of several works will help.

If you want to encourage your employees to have a change mentality, you need to give them experience in dealing with uncertainty. It means giving them time to explore and discover, to try and err. It means encouraging them to think for themselves rather than telling them what to do.

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I ran across a good article by Malcom Gladwell in the February 14 & 21 issue of The New Yorker titled, “The Order of Things.” The detail with which he explores rankings of colleges, hospitals and cars demonstrates the immense subjective potential rankings have. What is even more astounding is Gladwell’s discovery of the degree to which many organizations hold their leaders accountable for their place in these rankings.

From an intuitive perspective, people tend to have an emotional connection to statistics; they satisfy feelings for certainty, clarity and knowledgeableness. Thus, when we express arguments statistically, they tend to carry more weight than if we simply express them in words. Rankings clearly define for us what is best, better and good. However, they are more akin to magic where reality is but a trick. Thus, the feelings we receive from rankings (certainty, clarity, knowledgeableness) are satisfied because we want to believe their magic is real.

The Nature of RankingsAs a rule, unless the ranking is comparing very similar things against a single, measurable criterion, it is highly subjective. Therefore, here are some important questions to ask about the ranking to discover how its trick works:

  • Is it really comparing similar things?
  • Is the ranking based upon multiple criteria?
  • How important is each criterion and is it valid?
  • How does it weight the criteria?
  • Is it using some criteria as proxies for things that are difficult to quantify or research?
  • What important criteria are absent because of these difficulties?
  • Is the difference between one rank and each of those immediately above and below it that significant?
  • How accurate was the data collected for each criterion?
  • What problems might have retarded data quality?

Applying these questions will demonstrate that our affinity for rankings is more emotional than pragmatic.

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Is freedom for everybody?

When does freedom become chaos and uncertainty?

This past month, I conversed with a resident of a Muslim country. He commented on how many of his fellow citizens couldn’t understand why Americans thought they were free. “They have all these laws directing them. They can’t drive as fast as they want and they even need the government’s permission to drive (licenses).”

Coincidentally, the December 16th 2010 edition of The Economist reported on driving in Iraq. It’s true, at least there, that Iraq has far fewer driving restrictions than the United States has. It doesn’t even require driving licenses. However, driving there is dangerous. In fact, “the health ministry estimates that six times as many people now die in car accidents as fall victim to political violence.”

I also ran across an article about choice in the same issue. “Too much choice, concluded Sheena Iyengar of Columbia University and Mark Lepper of Stanford, is demotivating.” The article went on to suggest that this is from the anxiety people often feel when making decisions; too much freedom of choice increases anxiety.

There are people who seem to prefer less, and almost no, freedom in their work. They prefer clearly defined directions, rules, policies and procedures dictating their thinking and actions. Why? I have come to learn that this produces a different kind of freedom for some: freedom from responsibility. How can we be responsible for decisions we did not make or regulations we did not write? For some it also produces certainty; they know what the “right” decision is.

As the diagram to the right asks, “When does more freedom become chaos and uncertainty to us?” For each of us, that varies. For some of us, it restricts freedom so much that it might not even seem like freedom anymore. So, is freedom for everybody?

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“In the modern world the stupid are cocksure while the intelligent are full of doubt.” -Bertrand Russell, from his essay ‘The Triumph of Stupidity’, published in 1933.

Professors Justin Kruger and David Dunning provide supporting research. Their findings are categorically called the Dunning-Kruger Effect (DKE). In my earlier post about lying, we saw liars using confidence to encourage lies to take hold. Since confidence is a feeling that taps into our security needs, it naturally attracts us. Thus, a mother’s embrace is to a child what confidence is to an adult.

It seems natural though that those who are most competent should have the most confidence; but why does DKE claim the opposite? The incompetent don’t really know what they don’t know.

Imagine two generals. One sends his scouts out and finds no enemy forces. Another does the same and finds a force twice his size. Which general is going to feel more confident about his situation, the one with no enemy around or the one with? However, we then find out that the first general only sent his scouts out five miles while the second fifty miles. Which now? The answer doesn’t change because the first general didn’t know his scouts should have gone out fifty miles.

However, measuring competency isn’t as easy as measuring how far scouts ventured. The potential problems that concern the competent are staging far beyond a horizon the incompetent can’t see or don’t know exists. Thus, ignorance is not only blissful but confident.

Want proof? Next time you’re before a group of CEO’s ask how many of them believe their earnings growth over the last year is in the lower half of the group? You’ll get a number far less than 50% . . . maybe even 25%.

Related link: Why People Fail to Recognize Their Own Incompetence

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Knowledge States

By Mike Lehr

While helping a non-profit, a board member said, “We can only deal with a problem if we know there is one.” Here the state knowledge assumes alters our perspective. In this case, it causes us to ignore the idea of prevention, dealing with problems before they arise. In reality, problems don’t care whether we know or prove they exist. Thus, if knowledge’s form can alter our perspective and prevent us from seeing potential solutions, it is important to have a grasp on the different states of knowledge.

To that end, I’ve created the map to the right. It has five basic states: Unknown, Aware, Know, Prove and Quantify. Each is a subset of the previous one:

Knowledge Map

Knowledge Map


  • Unknown: Not knowing what we don’t know
  • Aware: Knowing what we don’t know, or not being able to express what we do know
  • Know: Knowing without proof but being able to express what we know
  • Prove: Using approaches that adhere closely to the scientific method or the one used in courts of law.
  • Quantify: Being able to count, calculate or formulate.

By looking at knowledge’s states in this manner, we see how much reality we exclude if we only accept what is quantifiable and provable. Imagine in warfare or the game of poker if we took no action unless we could prove it was the right one. Business is not immune to this. Therefore, success is more determined by how we treat what we don’t know or barely know and not by how we treat what we can prove and quantify. Thus, if we lived by the advice of the board member above, we would surely fail without a great amount of fortune.

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The scientific method’s usefulness falls far short of people’s belief in it. In other words, hype exceeds reality, and it becomes a panacea for solving problems of any type. The emotions behind this belief are so strong that people are often willing to deny, ignore or discount a reality if they cannot “prove” it. Since emotions and relationships often fall in this unproven domain and play important roles in many events, this belief can retard innovation and problem solving where intuitive approaches are viable solutions.

The inherent weaknesses of the scientific method are produced by its strengths as a disciplined inquiry. In its rigid quest to define observations and hypotheses, to control the experimental process, to quantify results and to present conclusions in a manner that can repeat results with different experimenters; the method excludes aspects of reality that aren’t easily observed, defined, controlled, quantified, presented or repeated. For example, something as obvious as good leadership being good for business cannot be addressed by the scientific method. The same holds true for proving that a good sales person sells more than a bad one or that good morale is better for business than bad morale is.

The proof of the scientific method’s inherent weaknesses is the common observation that what works in the laboratory doesn’t necessarily work in reality. That is why the idea must be reintroduced to reality via developmental and engineering phases. This is reflected in everyday life through disclaimers on product guarantees. For example, a window might be guaranteed but only if the homeowner uses the installer recommended by the window manufacturer. In other words, the best window in the laboratory might not be the best in reality because it’s too difficult to install.

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