Social Engineering Blogs

An Aggregator for Blogs About Social Engineering and Related Fields

Farming and the Evolution of Speech

As we know, many of our nonverbal behaviors have deep roots in our own process of evolution, but maybe our verbal behaviors have historical roots too.

While perhaps not quite as deeply ingrained as biological evolution, a new study in Science found evidence that many of our speech patterns can be linked back to changing dietary practices due to the dawn of agriculture. Specifically, our use of sounds like “F” and “V” can be linked to changing jaw and overbite structures that arose around that time.

Postdoctoral researchers Damián Blasi and Steven Moran got their idea from 34 year old linguistic analyses that found that contemporary hunter-gatherers lacked some of the linguistic types, called labiodentals, that many agricultural based people had.

When humans became accustomed to chewing foods high in fibers, the jaw bone is put under pressure and molars are worn down. This results in a more even mouth, developing away from an overbite and also making it easier to pronounce sounds like “F” and “V”.

While this idea may have some intuitive credibility, such an attitude was not shared in linguistic communities when linguist Charles Hockett made these unusual observations. Instead, he was met with skepticism, and it was that skepticism that Blasi and Moran sought to validate by proving Hockett wrong.

But they were very surprised. In order to assess Hockett’s claim, they made use of computer models to simulate how the human mouth makes sounds with varying degrees of overbite, and they analyzed languages around the world to see which languages most frequently used labiodental sounds.

The results are incredible striking. The computer models indicate that overbites make labiodental sounds much harder, with contemporary edge-to-edge teeth reducing the necessary effort by almost 30 percent.

Similarly, they discovered that labiodentals were much less common among languages used by hunter-gatherer communities. What might be most striking about these findings is the fact that they were able to track the progress of labiodentals emerging in languages throughout history, finding a steady increase in their use as societies developed and became more focused on expansive settled agriculture.

It is not all good news for those of us who enjoy our labiodentals, as we are also more at risk of cavities and of our teeth becoming overcrowded.

However, this study makes important strides in tracking how our communicative patterns are closely tied to our evolution and to our society. This is important if you are trying to better understand people of different cultures.

For instance, this study shows certain commonalities among those who speak Indo-European languages, emphasizing cross-cultural similarities. Yet, on the other hand, the fact that these speech patterns only emerged because of certain social arrangements also shows how deep the communicative gap can be between people of different cultures.

Still, that doesn’t mean you can’t learn how to better read people and communicate across cultural divides. This is one of Humintell’s specialties, and we even offer a cross-cultural training class!

Expressing Corruption?

Many of us worry about corruption amongst political elites, but could it be possible to actually recognize it in their faces?

In a pretty creative study, a team of psychologists from the California Institute of Technology sought to explore whether people could detect evidence of corruption by government officials by providing them with pictures of their faces. This study helps shed light both on efforts to effectively read other people but also on efforts by citizens to better evaluate our elected representatives.

While this may seem initially like a pretty far-fetched idea, there is a long history of research showing that people tend to make competent decisions about people’s trustworthiness from images of their faces. This has even been applied to potential leaders, where prosocial outcomes lead to positive evaluations.

However, this study makes an important break in shifting from just evaluations of a person’s charisma and perceived competence to actually determining if they have been practicing deception. Still, there is some prima facie credibility in that guilty expressions are generally identifiable.

To answer their question, the study authors undertook a series of experimental designs, showing images of politicians and asking participants to identify salient traits, such as corruptibility, dishonesty, and selfishness but also including more prosocial tendencies like competence and ambition.

In the first of these studies, participants were exposed to a series of 72 photos of actual elected officials in the United States. Of those, half had been convicted of some form of corruption, such as violations of campaign finance laws.

Before exposing participants to these photos, they were prompted with an instruction that they would have to designate the official’s level (1-5) of a given trait as quickly as possible, and they only had about four seconds to do so. This sought to ensure that people were judging based on spontaneous and initial reactions of emotional recognition.

Subsequent studies functioned similarly in an effort to strengthen the generalizability of any findings. This included varying the level of government that a given official held or using variants of the initial traits.

Overall, this series of experiments found broad support for the ability of participants to identify political corruption in faces of elected officials. This held up across variants, suggesting that it would apply more broadly outside of a limited experimental setting.

While many questions about generalizability and the precise causal mechanisms remain, this ambitious study does give us further evidence that our ability to read faces and detect deception has great potential even in photographs.

It would of course be interesting to see if an observer professionally trained in deception detection and people reading would do better.

In the meantime, check out some of Dr. Matsumoto’s work on politics and deception!

Prompted to Mimic Faces

Spontaneous Facial Mimicry

At the beginning of each block, an introduction-picture was presented, followed by 2–4 trials. (A) In the Emotion-Inference condition, the instruction “How does XXX (e.g., Hashimoto) feel?” was presented in Japanese. (B) In the Passive (control) condition, a fixation cross was presented. Reprinted from the ATR Facial Expression Image Database DB99 under a CC BY license, with permission from ATR-Promotions Inc., original copyright (2006).

Facial mimicry is known to be central to understanding the emotional states of others, but this exciting new study looks at the conditions under which we engage in such activity.

Emotional recognition is incredibly central to social interactions, and facial mimicry allows us to do so instantaneously. However, there is dispute over when we spontaneously or automatically engage in such behavior. It is this dispute which an exciting new paper in Plos One attempts to answer.

Specifically, the study authors are attempting to determine what factors make an individual engage in mimicry and what factors prevent them from doing so. This builds off of previous research finding that socio-ecological factors, like group membership and the identities of the people in question, inhibit or encourage the spontaneous mimicry necessary for emotional recognition.

While the role of such social factors is an ambitious one, the study authors sought a more manageable effort within that context. Previous research has indicated that facial mimicry occurs when there is an intention on behalf of the individual to deduce emotional states, and they sought to extend those findings in a more robust fashion, with an eye to the broader question.

Participants were recruited from the Hokkaido University student body and asked to review a selection of photographs and videos of people’s faces exhibiting various emotions. During this process, their facial muscles were analyzed to detect the presence of facial mimicry, in a similar fashion as previous studies.

However, not all participants were asked to identify the emotions displayed in the various images. Instead, half of them were simply asked to record age, gender, and other demographic features. This required emotional recognition from only half of the group.

The hypothesis was that those primed to look for emotions would also spontaneously engage in facial mimicry, while those looking at demographic factors would not.

The electromyography (EMG) scans were able to detect facial muscle movement as a reasonable indicator of facial mimicry, and it turns out that those asked to detect emotions showed markedly higher rates of muscle movement than those who were not. This provides pretty compelling evidence in support of their hypothesis.

This is definitely one of those times where many readers may be unclear exactly why any of this matters. Since facial mimicry, and thus emotional recognition, are not automatic but tied to intention, the social context begins to be seen as more important.

Differing group membership, for instance, can actively inhibit the intention to recognize emotions, leading to ignorance or devaluing of emotions. This is particularly fascinating (and troubling) given our previous blogs on the role that group membership has on violence and anger.

What it also means is that you, as an aspiring people reader, can choose to engage in facial mimicry and choose to better read people. This is something we can learn how to do, which is what Humintell tries to do, but it is also something we have to want to do.