How do computers change cultures?

In a study to be published soon in Social Psychology, Nina Hansen and colleagues examined whether and how giving laptops to children in developing countries changes their cultural beliefs and values. It is a fascinating and important study because it looks at how Western technology affects cultural systems in very basic but profound ways. They gave a group of Ethiopian school children laptops. One year later, they did a follow up and compared those children whose laptop was still functioning with a control group as well as a group of students whose laptop had broken down. They note that after this year the children with functioning laptops had become more independent and endorsed more individualistic values. This change was apparently mediated by a change in self-construal, that is the children had changed their values because of changes in how they saw themselves as individuals. The authors also stated that traditional cultural beliefs and norms were not changed, that is collectivistic values and interdependent self-construals were not affected by laptop use. A fascinating finding, but I believe only a first step towards understanding how technology use affects traditional cultural systems.

Here are some of my questions that appeared while reading their article.
They proposed three different mechanisms of how technology affects culture change:
1. Operation of a modern laptop requires a set of complicated actions which children would have to master completely independently of their elders (a self-efficacy explanation)
2. Social usage of technology can change social relations and self-perceptions, eg., through changes in interaction patterns (email) and well-being. This was one mechanisms that I did not quite understood and a bit more explanation of how this may play out in an African context would have been great.
3. Even a cheap and basic laptop of the kind given to children is an immensely valuable object by local standards, increasing their local status vis-à-vis their elders and peers (a social status explanation).


For me, these mechanisms are actually quite important and could have been tested more directly and effectively. The implications of these mechanisms are certainly quite different from a pragmatic and practical perspective (think of interventions and education programmes).

One important aspect for future studies is a more comprehensive test of these mechanisms. For example, the first mechanism requires a change in cognitive structures and abilities. Therefore, a test of cognitive abilities and knowledge pre-post would have been very useful. This mechanism fits in with a number of sociological theories that argue that cultural change happens via changes in values that then lead to different cognitive strategies. Alternatively, you could argue that greater knowledge and self-efficacy in operating technology provides access to different perspectives which then allows children to develop new ideas and values. It would have been a fascinating opportunity to test some of these bigger theories and ideas in a realistic experiment like this one.

The third mechanisms could have been tested directly as their measure of independent values included both self-direction values - which capture self-directed values focused on exploring and experimenting with new ideas as well as power and achievement values - values focused on dominating others, concerns with status and one's position in the social hierarchy according to social norms and expectations. Hence, it would have been very easy to test whether the status explanation is a plausible explanation or not. I think it is important to differentiate whether these changes are driven by knowledge and self-efficacy or by status processes. If the former is true, than providing schools with laptops and sharing resources is a viable mechanism for empowerment, whereas this would not be effective if it was driven by status mechanisms.

Some of their reported data also did not quite gel with the overall message. The usage pattern suggested increasing sharing of the laptop – this suggests more collectivistic behaviour rather than more individualistic behaviour in the classical sense. Hence, the more individualistic changes were accompanied by more collectivistic behaviours!

The design is also problematic in some respects. For example, the criteria for selection of students into the two groups is not discussed. Was allocation to groups random? Were the two groups matched in any other important characteristic?
The authors used single items to measure self-construals. On one hand it is difficult to use standard scales in traditional non-Western communities. On the other hand, given the unknown properties of such Western imposed items, it is hard to understand what the item actually measured and validity and reliability can not be assessed.
It was also curious to see that this item of self-construals only mediated effects of condition on independent values in the laptop condition. In the no laptop condition, there was no correlation between self-construal and values. This may indicate validity problems with the item. Alternatively, it could also mean that our Western findings of relatively close links between the self and values are in fact culturally mediated - that is these links are formed by the use of our cultural products.

Overall, a great field study, but it is not quite answering some of the important questions that are posed in the article.


Hansen, N., Postmes, T., van der Vinne, N., & van Thiel, W. (in press). Information and communication technology and cultural change. How ICT usage changes self-construal and values. Social Psychology.

Are cultural differences (in psychological processes) reducible to individual differences?

A colleague alerted me to an interesting paper published in the prestigious journal Proceedings of National Academy of Sciences. In this article (www.pnas.org/cgi/doi/10.1073/pnas.1001911107), Jinkyng Na and colleagues around senior author Richard Nisbett argue that differences in social orientation and cognition that exist between social classes and national cultures can not be reduced to individual differences. They present data from a moderately sized sample (N=235) of US citizens. The researchers administered a total of 20 tests, which were subdivided into 10 tests supposedly measuring social orientation and 10 tests measuring some form of cognitive style. They found significant differences between two groups of participants described as low and middle class for 5 of the cognitive tests (4 in the predicted direction) and 4 significant differences in the social orientation (3 in the predicted direction). Combining all measures, they also found significant effects. At the individual level, correlations were close to zero and mainly not significant. I have no problems so far.

The findings capitalize on a well-known statistical phenomena that within-group correlations and between-group correlations are independent and that the total correlation is the combination of both types of correlations. Put differently, correlations between variables (within groups) are statistically independent from the mean differences between groups. The correlation between all variables across all groups can be predicted if the variances and covariances are known. To their credit they discuss this phenomenon and present some simulations in this direction (without acknowledging that these issues have been discussed for at least 30 years in methodological circles, but also fail to realize the importance of separating the within-group from the between-group effects).

What really concerns me is their interpretation of this pattern. They argue that cultural differences are valid and can not be reduced to individual level differences. Where is the problem here?

In their starting example, they refer to both IQ and personality. For both variables, reliable and stable instruments had been constructed first and subsequently, differences were also found between ethnic and cultural groups. Therefore, we have a clear idea of what is happening at the individual level and then need to figure how between-group differences can be understood (which is an on-going debate). Following on from this, they now proceed to two vaguely defined and heterogeneously measured domains, namely social orientation (defined as independence and interdependence) and cognitive style (broadly defined as analytic versus holistic). The cross-cultural literature is full of studies that show small to moderate differences between different societies (most typically US student samples versus East Asian student samples). Yet, there is no consensus on definitions, measurement or a clear understanding of what these variables really are. Indeed, variables are lumped together that are studied as different phenomena in different areas of psychology. For example, happiness is certainly not the same as self-construals or intensity of emotions. Attributions are not the same construct as thematic versus taxonomic categorization tasks. The tests also involve various different methods (which can be seen as strength or weakness depending on the viewpoint). A stroop task is often capturing different psychological processes compared to self-reports, as the heated debate on implicit versus explicit attitudes demonstrates. Looking at this array of tests, I would simply not expect a strong correlation. We are not dealing with a coherent psychological phenomenon.

The mean differences between the two groups could be due to a large number of variables. Some of the causal variables may be strongly related: education, opportunities in life, and various other variables related to wealth immediately spring to mind. In a famous quote, one of the pioneers on cognitive styles Herman Witkin explicitly argued that field independence (as measured by the FLT) is associated with formal education. Wealth is probably also the most important variable influencing social orientation, a fact that is widely known since the famous study by Hofstede published in 1980. Hence, nothing new here. But the problem is  how wealth is influencing these variables and this most likely happening through different psychological processes. Hence, there is no reason to assume that these group differences are actually related rather than being probably influenced by a host of similar but distal variables.

In the latter parts of the paper, the authors then sink in a mess of tautological arguments. Because previous studies have shown these differences, then these differences need to be real and valid and hence, the individual and group level are distinct. Remember, this was what they wanted to test!

Yet, the authors also fail to notice the major shortcomings in many of the previous studies. For example, many of them did not test whether the instruments were equivalent or whether there were instrument, method, sampling or administration biases that could have influenced these results. Furthermore, these previous studies did not link potential explanatory variables to the observed differences, which is a standard practice in comparative psychological research (see for example http://pps.sagepub.com/content/1/3/234.abstract).

The current paper also fails to provide evidence on the equivalence of the measures. More importantly, it is not discussed how the two different groups are actually defined. What is social class and how were people grouped and on what criteria? The current study essentially is non-replicable.

What is a better approach? This has been discussed by a number of eminent cross-cultural psychologists, including Michael Bond, Kwok Leung, Ype Poortinga, Fons van de Vijver, David Matsumoto and others; and I have also occasionally added my two cents to this debate in a number of publications. The way forward is to come up with meaningful, reliable and valid instruments in each group that are equivalent in all cultures of interest. Next, we need to identify the situational, biological or psychological variables that are likely to explain the (predicted) differences between groups. The important element for understanding differences comes in empirically measuring these variables and demonstrating the link between our expected explanatory variable and the observed difference. As an added bonus, we could examine the influence at individual and group (cultural) level. Essentially, we are talking about a multi-level model here. There are now good examples and an increasing number of people use this important approach.

This is a scientifically more productive endeavor than setting up straw arguments based on statistical artefacts. One only wonders how something like this could get into a prestigious journal like PNAS....