Telling someone your goals makes them less likely to happen

What are social science's accomplishments?

Jim Manzi writes in his article What social science does -and doesn’t- know that 'the social sciences have not demonstrated the capacity to produce a substantial body of useful, nonobvious, and reliable predictive rules about what they study—that is, human social behavior, including the impact of proposed government programs'.

In the article he says that social sciences have been relatively late in embracing controlled experimentation which is an essential method to settle debates about what works and what not. According to Manzi, even now that the experimental method is becoming more and more popular we cannot expect fast breakthroughs in our scientific knowledge about 'the human condition because of the high 'causal density', the number and complexity of potential causes outcomes of interest, in this domain. He concludes: "At the moment, it is certain that we do not have anything remotely approaching a scientific understanding of human society. And the methods of experimental social science are not close to providing one within the foreseeable future. Science may someday allow us to predict human behavior comprehensively and reliably. Until then, we need to keep stumbling forward with trial-and-error learning as best we can."

Is this a fair judgment of social science's accomplishments? Surely, social scientists have done many experiments and acquired much knowledge. On this blog I have frequently mentioned examples of social scientific knowledge on topics like self-determination theory, growth versus fixed mindsets, development of expert performance and outstanding achievements, stereotype threat, priming, and so forth. But I have to admit, these topics, although very useful,  are examples of relatively fragmentary knowledge about human functioning. A 'scientific understanding of human society', of course, lies on a much higher aggregation level. But I would say that social science can be quite useful even if it can not yet 'predict human behavior comprehensively and reliably'.  I agree, we are very far from understanding the whole of human function and human society. But I wonder if this is a fair criterion for determining the usefulness of social science. Often, you don't have to understand the whole in order to be effective. To name just one example, we know a lot about the do's and don'ts of effective teaching.

Still, I agree with Jim Manzi that in many of the complexer tasks and domains of life we need to stumble forward with trial and error learning.

What are your thoughts?

Deliberate practice overcomes plateaus and limits on improvement of performance

Since Sir Francis Galton’s book on Hereditary Genius, many scientists have argued that heritable factors set limits of performance and only allow a select few individuals to attain exceptional levels. However, recent research rejects the associated learning theory and its implied performance plateaus and shows that expert performance is mediated by acquired complex cognitive mechanisms. It describes different types of deliberate practice activities that develop and refine mental representations, which in turn permit attained performance to exceed performance resulting from extensive experience only. Empirical investigations are reviewed to show that expert performance and outstanding achievements will be primarily constrained by individuals’ engagement in deliberate practice and the quality of the available training resources.

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Results driven improvement

I have mentioned the article Successful change programs begin with results by Robert Schaffer and Harvey Thompson before on this site (here). In that post, I did not link to the original article because I could not find it online. Now, I have found it (it is here) and I recommend that you, as someone who is interested in the solution-focused approach, read it. Here is what I wrote about the article in my previous post:

According to me, one of the most interesting management articles ever was written in 1992 by Schaffer and Thomson. To me, this article in its simplicity and results-focus was kind of like solution-focused change management avant la lettre. Their thought-provoking article was called 'Successful change programs begin with results'. I can't find a direct link to the article but here is a powerpoint presentation about it. Schaffer and Thomson call many change programs activity centered: the focus is on means and processes instead of on outcomes. Great effort is put in implementing programs, methods etc., like total quality management, reengineering and so on, in the hope that results will then automatically follow. The authors defy this logic. They claim that these activity centered approaches hardly ever work because the desired outcomes remain too vague, the change efforts are too large-scale and diffuse, and because means and goals are confused (the method seems to become more important than the originally desired outcomes). Schaffer and Thomson advocate a results-driven improvement process, which has the following characteristics:

1. Organizations only introduce management and process innovations if necessary;
2. Empirical tests show what works and what not;
3. Frequent successes create new energy for improvement;
4. Management creates a continuous learning process by applying lessons learnt in new phases.

I don't know if Schaffer and Thomson have written any other articles and books but this one is still very relevant and to the point. Let me know what you think.

Smart swarms

Social insects like ants, bees and termites and flocks of birds, schools of fish and herds of caribou distribute problem solving among many individuals. The often beautiful and amazing patterns of these groups of animals don't come from pre-existing blueprints or designs but they emerge from the bottom up as a result of interaction among the many individuals of the group. Here is an example:

 

The amazing thing is, and this goes somewhat against our human intuition, there is no centralized hierarchy and control whatsoever in such swarms. The individuals just act out their very simple task or rules and respond to their local circumstances. They repeatedly interact with many other members of the swarm and have no oversight or awareness of the total picture. They are very simple participants in the process; they don't know why they do what they do, they just do it. The swarm itself however is highly intelligent. It is, as it were, one enormous organism consisting of the many individual organisms which interact with each other. A group of ants is so smart that it can find, in very little time, the shortest route to something sweet you dropped on the kitchen floor. The swarm also can find out very fast that a predator is near and respond appropriately. Bees can find a wonderful place to build their hive by swarm intelligence. Flocks of birds and schools of fish can respond amazingly fast when a predator approaches them. Within apparently no time the group has collectively ducked away.

Human beings are, of course very different from the animals mentioned. In comparison with them, we are extremely intelligent and aware. Sometimes we perform as a swarm, for instance, when we are giving a standing ovation in the theatre. But often we are acting very individually as well. Does swarm intelligence have any relevance and usefulness for us, for instance in the way we do our work and run our companies? Indeed. In the new book The smart swarm, author Peter Miller gives many examples of how swarm intelligence has been applied to improve decision making, planning and other kinds of problem solving. For instance, by making computer programs simulating a group of ants, large companies have found ways to improve their logistic process and also their production process, thereby saving many millions of dollars annually.

My questions to you are: what applications do you see for swarm intelligence in your work? What connection do you see between the solution-focused approach and swarm intelligence? 

A mathematical look at change can be helpful for practical change professionals

A few months ago, mathematics professor Steven Strogatz wrote two columns in the New York Times called Change We Can Believe In and It Slices, It Dices. The columns are about calculus, a branch in mathematics focused on limits, functions, derivatives, integrals, and infinite series. Calculus is the mathematics of change. Its two basic branches are differential calculus and integral calculus. Without giving an in-depth explanation of these two topics, here is a brief introduction.

Differential calculus is the study of the derivative of functions. Calculating the derivative is called differentiation. The derivative tells you how fast something is changing, how far you’re going up or down a slope for every step you take. The derivate is the approximation to the slope of a graph. The derivate can be calculated for each point of a function but also for every point which leads to the derivate function (see picture from www.derivate.it). When a slope is going up its derivate is positive, when a slope is going down it's negative. At the peak and the bottom of a curve it is zero. At those points, change momentarily stands.

Integral calculus is the study of integrals which tells you how much something is accumulating. It is the calculus of summation. Calculating the integral is measuring the area under a curve (see picture on the right). Functions can have some very irregular shapes which can make it quite hard to easily measure this area under the curve. What integral calculus does to solve this problem, is slice that area up into thin slices, calculate the volume of the slices and then cleverly adding them up again. On a side note, integrating is the inverse operation of differentiation.

This is all very well, but is this of any relevance for practical change professionals? I believe it is. As I wrote before, my observation is that people involved in change in organizations, like consultants, project managers, line managers, coaches, sometimes get discouraged about how change is proceeding. Slightly changing your perspective on the change results can be very helpful in such instances. In my post Visualizing progress: expect fluctuation and watch the trend line I explained this as follows.

Progress hardly ever happens in a straight line. The picture on the right shows a real life example of an improvement process. The red line shows the actual values found (for instance the sales at a certain point in time). As you see, the levels constantly fluctuate. The blue line is the trend line which shows that over time there is a slow but steady improvement. The arrows show the following: Arrow 1: fast first results, quick progress. Arrow 2: rather heavy fall back. Arrow 3: quick improvement again. Arrow 4: serious fall back again after which improvement picks up again. It would be very easy to get discouraged when focusing too much on the fluctuations, at point 2 and 4 for instance. Two things are important to remember: 1) It is normal for progress to show this kind of fluctuation, and 2) The trend line is an important line to watch. This line shows you that there is actual growth overall. The trend line is a very motivating line to watch.

Strogatz' points are valuable additions to my previous post. Applying the explanations of derivates and integrals to my original graph you get the picture on the right. Let's apply them to the potentially most depressing point of the graph which is point 4. The red line shows the derivate of point 4, the colored areas show the integral of the graph until point 4. Both give reason for a positive and hopeful view on the change results. The derivate (red line) at point 4 the negative slope is getting less steep which says things are still getting worse but this decline happens more slowly which gives hope that the bottom is in sight and a turn to a positive slope may be near. The colored areas show the integral which, the area under the curve. The red area visualizes the accumulation of everything that has been achieved from point 0 to point 3. As you see it is all below 0 so the result is negative. This blue area visualizes the accumulation of everything that has been achieved from point 3 to point 4 and the absolute value is reaching 0 again, the Nett result of the change process is positive because the blue area is much larger than the red area. A lot has been acheived. The thought, at point 4, that every effort has been in vain is therefore unjustified.

What has science got to do with morality?

My post of yesterday mentioned Sam Harris' book, The Moral Landscape: How Science Can Determine Human Values. Traditionally, scientists have refrained from interfering much with morality, leaving moral issues largely to philosophy and religion. But this reluctance seems to get less these days. Recently Edge even organized a conference called THE NEW SCIENCE OF MORALITY with Roy Baumeister, Paul Bloom, Joshua D. Greene, Jonathan Haidt, Sam Harris, Marc D. Hauser, Joshua Knobe, Elizabeth Phelps, and David Pizarro as speakers.

A central theme of many morality scientists is how human moral behavior is shaped into us over the course of both biological and cultural evolution. Matt Ridley is one author who has written about this.

In his book The Origins of Virtue: Human Instincts and the Evolution of Cooperation,  Ridley explains the paradox that our minds have been build by selfish genes to be social, trustworthy and co-operative. He says we owe our success as a species to these social instincts. He explains that morality is the stuff society is made of. In short his argument goes like this: 1) Society is important because it allows for division of labor. It allows for people to specialize. And the sums of all our specialized efforts are greater than they would be if we all had been generalists. In other words: society is synergy between specialists. 2) In order to have a harmonious society, we have to be well-connected to each other. This requires us to be co-operative, social and trustworthy. 3) Being social, co-operative and trustworthy is a way to thrive and thereby an evolutionary advantage. These traits are built into our nature by evolution.

In his recent book The Rational Optimist: How Prosperity Evolves, Matt Ridley says that exchange is the root of human virtue and prosperity. He says that we as a species have been able to change extraordinarily, not primarily because we have evolved so dramatically as individuals but because human intelligence became collective and cumulative in a way that distinguishes us from all other species. By starting to exchange things we discovered 'the division of labor', specialization by individuals for mutual gain. Specialization leads to expertise which made innovation possible because it provides the specialist with a reason and an opportunity to invest extra time in improving tools or techniques and developing new ones. In addition to this, friendliness, tolerance and civility will increase due to the fact that the individuals who have echanged goods, will be aware they are interdependent. On a larger scale, in complex networks, the same applies, providing the freeness and fairness of exchange is governed by rules. The greater the interconnected communities become, the more different habits it acquires, the more specializations it can develop and the more its collective intelligence grows. This video summarizes that mechanism.

Back to Sam Harris. I think he has a strong case. He says morality must be defined by thriving of conscious creatures. And if science can inform us about how to promote thriving, morality is, at least to some extent, a scientific topic. Many examples of how science has something to say about human thriving come to my mind right away. I think these support Harris' case. I will mention four of them.

1. The first is positive psychology, which I think can be defined as the science of human thriving. PP researchers are in the process of discovering more and more determinants of human thriving.
2. A second example is the work on stereotype threat. Stereotype threat is the tendency to expect, perceive, and be influenced by negative stereotypes about one’s social category, such as one’s age, sex, sexual orientation, ethnicity, profession, nationality, political affiliation, mental health status, and so on. Stereotype threat can be harmful by creating racial, gender, and social class achievements gaps in schools and in the workplace and tensions across group lines. Research has shown that the harmful effects of stereotype threat can be prevented and undone by relatively simple interventions (read more here). 
3. A third example is research on the relationship between equality in communities and thriving. Research by Richard Wilkinson and Kate Pickett, two English epidemiologists, show how high levels of inequality in societies in harmful for everyone within them. Their research shows how high levels of equality within a society has a strong positive impact on social well being and health (read more).
4. A fourth example is the work of Robert Frank, author of What price the moral high ground? Based on recent theoretical and empirical insights in economics, psychology and biology, he challenges the cynical view on humanity which was long held in mainstream economics. Economics' assumptions that people are purely driven by self-interest and opportunism are not valid and even harmful. He comes to the conclusion that in the course of social and economic interaction, pure selfishness generally does not work and ethical behavior does. Also he says, that moral behavior can and is likely to emerge spontaneously in competitive environments. But he also cautions that the way we structure those environments strongly affects the amount of moral behavior we actually observe: "The mere possibility of spontaneous, self-sustaining moral behavior is a profoundly optimistic notion. But we must be careful not to become intoxicated by it. In particular, it provides no reason whatever to just sit back and allow events to unfold".

The Moral Landscape: Q & A with Sam Harris

1. Are there right and wrong answers to moral questions?
Morality must relate, at some level, to the well-being of conscious creatures. If there are more and less effective ways for us to seek happiness and to avoid misery in this world—and there clearly are—then there are right and wrong answers to questions of morality.

2. Are you saying that science can answer such questions?
Yes, in principle. Human well-being is not a random phenomenon. It depends on many factors—ranging from genetics and neurobiology to sociology and economics. But, clearly, there are scientific truths to be known about how we can flourish in this world. Wherever we can have an impact on the well-being of others, questions of morality apply.

Read the whole article here