Chimpanzees learn to crack nuts faster than humans

6 minute read

Early this year, Christophe Boesch and coworkers released a paper describing their observations on how fast chimpanzees and humans learn to crack nuts. They collected data on human foragers from the Mbendjele group, and chimpanzees of the Taï forest, watching how children and juvenile chimpanzees learn from other individuals, the extent that older individuals “teach” by intentionally directing their behavior toward the learners, and measuring the rate at which individuals can get panda nuts out of their shells.

The method that each group uses to crack nuts is very similar.

Most people’s intuition probably would suggest that humans would learn how to crack nuts faster than chimpanzees. Boesch and coworkers found the opposite: Chimpanzees learn much faster than humans, and chimpanzees attain adult proficiency at much younger ages than humans do.

Figure showing nutcracking speed versus age in chimpanzees and human hunter-gatherers
Figure 1 from Boesch et al. 2019. Original caption: "Learning curves for the ‘number of nuts cracked per minute’ in Taï chimpanzees and Mbendjele foragers; (a) when considering absolute age (above) and (b) when considering relative age whereby 1.0 corresponds to the population-specific age of first reproduction. Indicated are the fitted model and its confidence intervals. For the plot age was binned (bin width: 0.1 year), and the number nuts cracked per minute was averaged per age bin. Symbol area represents the total observation time per age bin (0.1 to 15.8 hours)."

This is just an incredible figure. Taï chimpanzee adults and Mbendjele adults both end up with a similar pace of nutcracking – the humans average a bit higher but the variation among human and chimpanzee adults overlaps completely.

The paper includes a nice paragraph describing the acquisition of technical knowledge in humans from many small-scale societies. The overarching generalization is that human foragers and small-scale agriculturalists take many years to attain maximum performance in tasks that require some technical learning:

Recent studies about the acquisition of technical intelligence skills in humans revealed that apprentices may need many years of practice before reaching adult expertise. Despite social exposure to expert tool users’ performances and advice, apprentices only acquire the skills after many years of practice and with slow progress in performance. For example, stone knappers in Langda, New Guinea begin to acquire the technique as adults but appear to encounter difficulties in following the guidance and advice from skilled individuals, as for at least five years, they continue to produce much shorter adze heads employing different strategies than the ones demonstrated to them. A similar pattern has been observed in Khambhat, India, with the acquisition of another type of stone knapping technique, where apprentices pay no attention to some aspects of the technique used by experts, such that their final products are quite different from those of the latter. As a result, high quality beads are produced only after seven to ten years of practice. Similarly, long learning processes have also been documented for the hourly return rate in hunting and honey, palm heart, or tuber gathering among the Ache or the Hiwi, for the reported age of acquisition in different tasks ranging from food and craft production to music and story-telling among the Tsimane of South America, and for the production of knapping stones as tools for hideworking in Ethiopia.

The cross-cultural buildup of such data over the last 20 years has given rise to the idea that learning technical processes is so difficult that humans must be specially adapted to be able to learn this stuff. In such studies, the apparently very long period of skill acquisition is characteristic even of tasks like honey collection and digging tubers.

But the fact that chimpanzees learn to crack nuts much faster than humans causes Boesch and coworkers to suggest an alternative hypothesis. Humans are slower at learning how to do things because humans have a larger number of specialized technical tasks to learn how to do. They term this a “life history” hypothesis, because their proposition is that humans develop slower and need to attain full competency at adulthood, not as juveniles, and so humans have the luxury of taking longer at each individual task, possibly enabling them to learn a larger number of specialized tasks.

Both of these hypotheses take what seems like a bug and try to make it a feature. Humans in foraging societies take 20 years to achieve peak hunting returns. Why should this be, when lions manage to achieve peak returns in only 3 or 4 years? According to the “hard to learn” hypothesis, it is because human hunting is a lot harder to do than lion hunting, because humans are using a very technical set of abilities. According to the “life history” hypothesis, it is because humans have lots of other things on their plate, and their learning has to balance all these things against the timeline of development.

Obviously, the nutcracking example busts the “hard to learn” logic, because chimpanzees are using the same method as humans, and achieve peak performance much faster.

But the “life history” hypothesis doesn’t seem to describe the pattern for learned skills that humans start to perform as adolescents and fail to become fully proficient until age 35 or higher. I come back to the question of why it takes humans 20 years to achieve peak hunting success. The problem is similar in timeline to the “apprenticeship” examples of specialized tool manufacture mentioned above.

One answer might be that the “life history” hypothesis works for easier tasks, and the “hard to learn” hypothesis works for harder ones. Chimpanzees do not become craft specialists or tenured professors. Maybe these really are uniquely difficult, and that’s why it takes humans so long to become proficient at them (and many never become proficient).

I would offer an alternative possibility: Humans may take a long time to gain apparent efficiency of performance in such tasks because human social relationships hold back performance.

Some tasks are communal, meaning that all individuals in a group may benefit from one person’s effort, while no person can monopolize the fruits of her labor. As a result, individuals are disincentivized from maximal performance, as long as that performance has costs. For example, hunters in a hunting and gathering society vary greatly in their average success rate and return rate of meat. Studies of hunters in such societies have shown that adolescents have low return rates, which increase gradually up to age 35 or 40. Those returns later decline at older and older ages. This pattern has previously been explained as the delay caused by the time needed to learn complicated hunting skills. But such a hypothesis neglects the costs of hunting. Such costs include energetic costs from hunting effort, risk of injury or death while hunting, the opportunity costs of socializing or pursuing other activities, and the social obligations that are imposed upon good hunters, among others. In a food sharing group, a young hunter would be entirely rational to pursue a strategy of increasing learning effort only as older hunters decline in their abilities.

Likewise, an apprentice often would be best served not to attain too great a skill while still under the thumb of his master. If the apprentice can actually monopolize the benefits of his own labor, the situation would be different, but an apprentice’s independence depends on an intricate network of social relationships, not purely the quality of his work.

It is at the same time quite true that some human technical tasks are made vastly more complicated by cultural rules. For example, something as simple as a bead has many culturally determined characteristics, including length, diameter, smoothness, type of drill hole, material, and many others that increase the difficulty of an craftsman attaining the necessary precision.

My point is that watching how fast individuals in real societies attain maximal performance is a very bad measure of how fast they might be able to learn. Human motivation is social, not merely economic.