In this insightful and interdisciplinary target article, Baumard presents a new perspective on the Industrial Revolution in eighteenth-century England, proposing that affluence, and its accompanying affordances, was responsible for a plastic psychological shift that facilitated innovative behavior. Thus, in contrast to the longstanding adage “Necessity is the mother of invention,” Baumard makes a case that opportunity is the mother of innovation. Considering these opposing stances through the lens of behavioral ecology and cultural evolutionary theory, we suggest that both necessity and opportunity may be drivers of innovativeness, albeit of different types. We propose that to understand innovation, it is helpful to consider mechanisms operating on two different time scales: a behavioral time scale, on which individuals choose whether to try to innovate or to stick to known behaviors, and a developmental time scale, on which conditions may determine the type of experiences that shape individuals’ cognition, thus affecting both their ability and likelihood to innovate.

In behavioral ecology, Life History Theory (Ricklefs & Wikelski Reference Ricklefs and Wikelski2002; Wang et al. Reference Wang, Kruger and Wilke2009; Wolf et al. Reference Wolf, van Doorn, Leimar and Weissing2007) and Optimal Foraging Theory (Caraco Reference Caraco1981; Stephens & Charnov Reference Stephens and Charnov1982; Stephens & Krebs Reference Stephens and Krebs1986) are commonly invoked to explain exploratory and potentially innovative behaviors (Aplin et al. Reference Aplin, Farine, Morand-Ferrron, Cockburn, Thornton and Sheldon2015; Keynan et al. Reference Keynan, Ridley and Lotem2016). However, there is an ongoing debate about the conditions that favor innovativeness, with seemingly conflicting evidence: some findings show that necessity (scarcity) boosts innovation, whereas others, as highlighted by Baumard, support the notion that opportunity (affluence) is the mother of invention (e.g., Benson-Amram & Holekamp Reference Benson-Amram and Holekamp2012; Bokony et al. Reference Bokony, Lendvai, Csongor, Vágási, Pǎtraş, Pap, Németh, Vincze, Papp, Preiszner, Seress and Likér2013; Keynan Reference Keynan, Ridley and Lotem2016; Laland & Reader Reference Laland and Reader1999; Morand-Ferron et al. Reference Morand-Ferron, Cole, Rawles and Quinn2011; Sol et al. Reference Sol, Griffin and Bartomeus2012; Thornton & Samson Reference Thornton and Samson2012). Thus, Baumard presents research that identifies increased exploration and innovativeness in less-stressed individuals (Andrews et al. Reference Andrews, Nettle, Reichert, Bedford, Monaghan and Bateson2018; Bateson et al. Reference Bateson, Brilot, Gillespie, Monaghan and Nettle2015). In contrast, the necessity drives innovation hypothesis (Bokony et al. Reference Bokony, Lendvai, Csongor, Vágási, Pǎtraş, Pap, Németh, Vincze, Papp, Preiszner, Seress and Likér2013; Boserup Reference Boserup1965; Laland & Reader Reference Laland and Reader1999; Reader & Laland Reference Reader and Laland2003; Thornton & Samson Reference Thornton and Samson2012) suggests that risk-taking, explorative, and innovative behaviors are to be expected in stressed and subordinate individuals with less access to resources, because it is those individuals that must be creative to increase their fitness (Berger-Tal et al. Reference Berger-Tal, Nathan, Meron and Saltz2014; Houston & McNamara Reference Houston and McNamara1999; Kolodny & Stern Reference Kolodny and Stern2017; McNamara & Houston Reference McNamara and Houston1992). We propose that one way to reconcile these opposing findings is to focus not on a single axis of exploration and exploitation trade-offs, but rather to think of adaptiveness of different types of problem-solving strategies in different states of affluence and scarcity. Baumard states that Life History Theory “runs against the common sense according to which ‘necessity is the mother of invention’” (sect. 2.4, para. 1). In contrast, we propose that a consideration of the full complexity of the findings in behavioral ecology, cultural evolution, and cognition leads to the conclusion that necessity and opportunity can facilitate innovation; we further predict that they should be expected to correlate with different types of innovations (Arbilly & Laland Reference Arbilly and Laland2017; Fogarty et al. Reference Fogarty2015; Kolodny et al. Reference Kolodny, Creanza and Feldman2015a; Reference Kolodny, Edelman and Lotem2015b).

This point of view may be useful for expanding the ideas brought forth by Baumard with respect to innovativeness and cultural evolution in humans. On short time scales, necessity may be a driving force for goal-oriented, short-time-scale problem-solving behavior, which involves modest risks and payoffs that can be clearly stated or conceptualized. The innovations of this type will be simple conceptually and will likely involve subgoals that are clearly connected to some reward (Arbilly & Laland Reference Arbilly and Laland2017). On the other hand, opportunity may be a driving force for creative behavior that is directed toward more open-ended problems, where the payoffs are more abstract and not easily defined a priori. The innovative solutions of this type may be more complex, involve a hierarchy of multiple conceptual levels, and include subgoals that in themselves are unrewarding (Kolodny et al. Reference Kolodny, Edelman and Lotem2015c). The innovative behavior in this condition is exploratory in nature. Indeed, the affluent conditions at the onset of the eighteenth century in England could have been particularly well suited for the type of “high-level” innovations that eventually drove the Industrial Revolution.

Alongside immediate need, the ability and tendency to innovate are influenced by dynamics over long time scales: affluent conditions during the development of an individual may allow for extensive exploration, giving rise to a rich cognitive representation of the world (Kolodny et al. Reference Kolodny, Edelman and Lotem2015b). Moreover, the prospect of future opportunities in itself may encourage exploration and gain of such experience (Berger-Tal et al. Reference Berger-Tal, Nathan, Meron and Saltz2014). The accumulated experience shapes the cognitive infrastructure that lends itself to innovation when conditions, as discussed above, encourage such behavior. On the flip side, paucity of exploration during development may later constrain the potential for complex, open-ended, or hierarchically structured innovative behavior, even when conditions favor it. Furthermore, limited resources could potentially lead to developmental trade-offs in which an individual might avert metabolic resources from cognitive development to immune function or other physiological needs; stress during development has been linked to learning deficits in a subset of animal studies (Boogert et al. Reference Boogert, Zimmer and Spencer2013; Crino et al. Reference Crino, Driscoll, Ton and Breuner2014; Farine et al. Reference Farine, Spencer and Boogert2015; Lemaire et al. Reference Lemaire, Koehl, Le Moal and Abrous2000; Nowicki et al. Reference Nowicki, Searcy and Peters2002), warranting further investigation of its effects on human innovation and learning.

We also note that a discussion of these potential “mothers of invention” in a way that is removed from the cultural evolutionary context of those innovations is naturally limited in its ability to predict population-level processes. For example, both demography and environmental variability are likely to shape the dynamics of human innovation and cultural evolution (Carja & Creanza Reference Carja and Creanza2019; Colleran et al. Reference Colleran, Jasienska, Nenko, Galbarczyk and Mace2015; Fogarty et al. Reference Fogarty, Creanza and Feldman2013; Fogarty & Creanza Reference Fogarty and Creanza2017; Reader & MacDonald Reference Reader, MacDonald, Reader and Laband2003). In addition, human culture is uniquely cumulative and shaped by social interactions between individuals who might use different strategies for innovation (Dean et al. Reference Dean, Kendal, Schapiro, Thierry and Laland2012; Derex & Boyd Reference Derex and Boyd2016; Derex et al. Reference Derex, Perreault and Boyd2018; Henrich et al. Reference Henrich, Boyd, Derex, Kline, Mesoudi, Muthukishna, Powell, Shennan and Thomas2016; Lewis & Laland Reference Lewis and Laland2012). These complexities suggest a more nuanced characterization of human innovation would be useful.

In many fields, creativity is categorized into multiple subtypes (Fogarty et al. Reference Fogarty2015): for example, deliberate versus spontaneous creativity or groundbreaking versus everyday creativity. In previous work, we noted that the field of human cultural evolution has not yet embraced this more nuanced perspective on innovation, and we proposed a number of evolutionary models that consider multiple distinct processes of innovation (Creanza et al. Reference Creanza, Kolodny and Feldman2017; Fogarty & Creanza Reference Fogarty and Creanza2017; Fogarty et al. Reference Fogarty2015; Kolodny Reference Kolodny, Creanza and Feldman2015a; Kolodny et al. Reference Kolodny, Creanza and Feldman2016). We predict that motivation for innovation, when tracked along an axis from the most desperate to the most affluent conditions, follows a bowl-shaped curve: High when necessity is great, and also high in times of abundance and leisure, while being lowest in intermediate situations, where fulfillment of basic needs keeps individuals busy but resources are plentiful enough to favor a risk-averse strategy. We further suggest that this interacts with long-term conditions that shape the cognitive infrastructure on which innovative behavior draws. This perspective can reconcile the inconsistency between previous studies and frame Baumard's proposal in a new light: both necessity and opportunity can be the mothers of innovation.