Osiurak and Reynaud (O&R) draw attention to “the elephant in the room”: an overlooked set of cognitive mechanisms that could explain cumulative technological culture (CTC) in human populations. In particular, their technological-reasoning hypothesis states that all humans possess unique, non-social cognitive skills, dubbed their technical potential, “enabling them to acquire and generate a great – perhaps infinite – amount of technical information,” dubbed their technical expertise (sect. 1, para. 3).
There is no doubt that technical-reasoning skills play a role in CTC. Knowing how to design or use artifacts crucially involves understanding how sequences of actions affect physical mechanisms: humans deliberately press buttons, stir mixtures, or flip switches in order to trigger, affect, or terminate processes in our devices. Such action sequences, codified in recipes or user manuals, resist specification in terms of separate motor actions; rather, the technical information or expertise involved in use and design can be analyzed in terms of interdependent sets of actions or plans (Houkes & Vermaas Reference Houkes and Vermaas2010). There is, moreover, no doubt that one's repository of technical information may increase over time, for instance through the application of technical-reasoning skills to episodes of successful use: one may come to recognize which actions reliably lead to which results by means of which artifactual physical mechanisms. Conversely, expertise may improve technical-reasoning skills. Through (reflection on) repeated use, one may enhance skills for specific technologies (improved causal reasoning), or may discern similarities between technologies (improved analogical reasoning).
Accepting these interrelations between technical potential and expertise leaves it unclear, however, exactly what the technical-reasoning hypothesis encompasses. Conceptually, it is compatible with a range of hypotheses that, methodologically, are difficult to differentiate empirically.
At one extreme, one may hypothesize that technical reasoning (i.e., human technical potential) may be necessary for CTC, but that this potential remains elementary in virtually all of us, despite growing technical expertise. Both simple and sophisticated recipes, for instance, are comprised of relatively elementary mechanical actions such as “stirring” and “cutting,” which are not too far above the level of motor actions. At the other extreme, one may hypothesize that technical potential grows in tandem with technical expertise: expert pianists may discern action-result patterns that are beyond the capacities of any novice, both in terms of describing higher-order mechanical actions and in terms of perceiving produced effects.
The range of hypotheses is increased further by considering the role of social (cognitive) mechanisms. Technical expertise grows in part because of mentoring and social interaction, as we guess O&R would agree with. Still, it is conceivable that we may acquire great expertise in, say, cycling exclusively through individual use and technical reasoning skills – where such reasoning skills may, in turn, be relatively stable over time or, rather, vastly improve. Conversely, one may hypothesize that social interaction is necessary for increased expertise, or for acquiring a certain level of expertise. Furthermore, one may differentiate these hypotheses according to different types of technologies: the interaction between technical potential, expertise, and social interaction may be different for, say, cooking than it is for, say, civil engineering.
In light of this, we submit that the main contribution that O&R have made is not so much substantiating one particular hypothesis (viz., their technological-reasoning hypothesis) as revealing a large range of hypotheses regarding the mechanisms that underlie CTC.
By consequence, much care is required, conceptually, to distinguish between various possible hypotheses. Notions such as “potential” and, in particular, “expertise” easily give rise to confusion or to trading on ambiguities: “expertise” may refer to, among other things, a body of more or less codified knowledge, or to skillful use (thus including technical-reasoning skills). Moreover, each hypothesis within the range of aforementioned hypotheses requires careful formulation. It will not do, for instance, to argue that CTC may result from technical-reasoning skills alone by simply providing evidence that the latter necessarily complement social cognitive mechanisms.
Methodologically, enlarging the range of hypotheses has more problematic consequences. Once appropriately formulated and disambiguated, many more hypotheses turn out to be compatible with the available evidence than most parties in this debate appear to realize. We may reasonably claim that technological-reasoning skills play a role in CTC, but this leaves open many issues: whether technological-reasoning skills are more than a necessary complement to social-cognitive mechanisms; how these skills in humans can be characterized independently of growing expertise and social interaction; and to what extent these skills are global or specific to technological domains. Moreover, these issues are not just unresolved at present – it is difficult which evidence could speak in favor or against, say, claims that technological-reasoning skills alone (i.e., without social interaction) suffice for attaining large, “perhaps infinite” levels of expertise.
To be sure, that the available or possible evidence may underdetermine explanatory hypothesis concerning CTC is a problem for anyone interested in this phenomenon and not only for the authors of the target article. Yet to return in closing to their leading metaphor: we may concede their point that there is an elephant in the room, but submit that it may be small, heavily domesticated, or simply impossible to locate because of all the people.
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Osiurak and Reynaud (O&R) draw attention to “the elephant in the room”: an overlooked set of cognitive mechanisms that could explain cumulative technological culture (CTC) in human populations. In particular, their technological-reasoning hypothesis states that all humans possess unique, non-social cognitive skills, dubbed their technical potential, “enabling them to acquire and generate a great – perhaps infinite – amount of technical information,” dubbed their technical expertise (sect. 1, para. 3).
There is no doubt that technical-reasoning skills play a role in CTC. Knowing how to design or use artifacts crucially involves understanding how sequences of actions affect physical mechanisms: humans deliberately press buttons, stir mixtures, or flip switches in order to trigger, affect, or terminate processes in our devices. Such action sequences, codified in recipes or user manuals, resist specification in terms of separate motor actions; rather, the technical information or expertise involved in use and design can be analyzed in terms of interdependent sets of actions or plans (Houkes & Vermaas Reference Houkes and Vermaas2010). There is, moreover, no doubt that one's repository of technical information may increase over time, for instance through the application of technical-reasoning skills to episodes of successful use: one may come to recognize which actions reliably lead to which results by means of which artifactual physical mechanisms. Conversely, expertise may improve technical-reasoning skills. Through (reflection on) repeated use, one may enhance skills for specific technologies (improved causal reasoning), or may discern similarities between technologies (improved analogical reasoning).
Accepting these interrelations between technical potential and expertise leaves it unclear, however, exactly what the technical-reasoning hypothesis encompasses. Conceptually, it is compatible with a range of hypotheses that, methodologically, are difficult to differentiate empirically.
At one extreme, one may hypothesize that technical reasoning (i.e., human technical potential) may be necessary for CTC, but that this potential remains elementary in virtually all of us, despite growing technical expertise. Both simple and sophisticated recipes, for instance, are comprised of relatively elementary mechanical actions such as “stirring” and “cutting,” which are not too far above the level of motor actions. At the other extreme, one may hypothesize that technical potential grows in tandem with technical expertise: expert pianists may discern action-result patterns that are beyond the capacities of any novice, both in terms of describing higher-order mechanical actions and in terms of perceiving produced effects.
The range of hypotheses is increased further by considering the role of social (cognitive) mechanisms. Technical expertise grows in part because of mentoring and social interaction, as we guess O&R would agree with. Still, it is conceivable that we may acquire great expertise in, say, cycling exclusively through individual use and technical reasoning skills – where such reasoning skills may, in turn, be relatively stable over time or, rather, vastly improve. Conversely, one may hypothesize that social interaction is necessary for increased expertise, or for acquiring a certain level of expertise. Furthermore, one may differentiate these hypotheses according to different types of technologies: the interaction between technical potential, expertise, and social interaction may be different for, say, cooking than it is for, say, civil engineering.
In light of this, we submit that the main contribution that O&R have made is not so much substantiating one particular hypothesis (viz., their technological-reasoning hypothesis) as revealing a large range of hypotheses regarding the mechanisms that underlie CTC.
By consequence, much care is required, conceptually, to distinguish between various possible hypotheses. Notions such as “potential” and, in particular, “expertise” easily give rise to confusion or to trading on ambiguities: “expertise” may refer to, among other things, a body of more or less codified knowledge, or to skillful use (thus including technical-reasoning skills). Moreover, each hypothesis within the range of aforementioned hypotheses requires careful formulation. It will not do, for instance, to argue that CTC may result from technical-reasoning skills alone by simply providing evidence that the latter necessarily complement social cognitive mechanisms.
Methodologically, enlarging the range of hypotheses has more problematic consequences. Once appropriately formulated and disambiguated, many more hypotheses turn out to be compatible with the available evidence than most parties in this debate appear to realize. We may reasonably claim that technological-reasoning skills play a role in CTC, but this leaves open many issues: whether technological-reasoning skills are more than a necessary complement to social-cognitive mechanisms; how these skills in humans can be characterized independently of growing expertise and social interaction; and to what extent these skills are global or specific to technological domains. Moreover, these issues are not just unresolved at present – it is difficult which evidence could speak in favor or against, say, claims that technological-reasoning skills alone (i.e., without social interaction) suffice for attaining large, “perhaps infinite” levels of expertise.
To be sure, that the available or possible evidence may underdetermine explanatory hypothesis concerning CTC is a problem for anyone interested in this phenomenon and not only for the authors of the target article. Yet to return in closing to their leading metaphor: we may concede their point that there is an elephant in the room, but submit that it may be small, heavily domesticated, or simply impossible to locate because of all the people.
Acknowledgment
Research by Krist Vaesen was supported by the Netherlands Organisation for Scientific Research (NWO, Vidi-grant 276-20-021).
Conflict of interest
None.