Heyes suggests that selective social learning comes in two varieties. One is common, domain general, and associative. The other is rare, domain specific, and metacognitive. We argue that this binary distinction cannot quite do the work she assigns it and sketch a framework in which additional strategies for selective social learning might be accommodated.

Heyes’ book is an important contribution that rightly integrates cognitive development and cultural evolution. However, understanding the cultural evolution of cognitive gadgets requires a deeper appreciation of complexity, feedback, and self-organization than her book exhibits.

I argue, with examples, that most human cognitive skills are neither instincts nor gadgets but mechanisms shaped both by evolved dispositions and by cultural inputs. This shaping can work either through evolved skills fulfilling their function with the help of cultural skills that they contribute to shape, or through cultural skills recruiting evolved skills and adjusting to them.

Attempted answers are given to (a) whether nonhuman great apes (apes) also have evolved imitation (answer: no); (b) whether humans can transmit imitation as a gadget to apes (answer: yes, partly); (c) whether human-to-ape transmission can kickstart subsequent and stable ape cultural evolutionary psychology (“CEP”; answer: unlikely); and (d) when CEP evolved in our lineage (answer: relatively late).

Sociocultural developmental psychology can drive new directions in gadgetry science. We use autobiographical memory, a compound capacity incorporating episodic memory, as a case study. Autobiographical memory emerges late in development, supported by interactions with parents. Intervention research highlights the causal influence of these interactions, whereas cross-cultural research demonstrates culturally determined diversity. Different patterns of inheritance are discussed.

Heyes sets out an intriguing theory but it raises more questions than compelling answers concerning culturally shaped cognition. I set out what I see as the most pressing questions, ranging over the book's early chapters concerning the structure of the theory, to two of Heyes’ four exemplar cognitive domains, selective social learning and imitation.

Responding to commentaries from psychologists, neuroscientists, philosophers, and anthropologists, I clarify a central purpose of Cognitive Gadgets – to overcome “cognition blindness” in research on human evolution. I defend this purpose against Brunerian, extended mind, and niche construction critiques of computationalism – that is, views prioritising meaning over information, or asserting that behaviour and objects can be intrinsic parts of a thinking process. I argue that empirical evidence from cognitive science is needed to locate distinctively human cognitive mechanisms on the continuum between gadgets and instincts. Focussing on that requirement, I also address specific challenges, and applaud extensions and refinements, of the evidence surveyed in my book. It has been said that “a writer's idea of sound criticism is ten thousand words of closely reasoned adulation.” I cannot disagree with this untraceable wag, but the 30 commentators on Cognitive Gadgets provided some 30,000 words of criticism that are of much greater scientific value than adulation. I am grateful to them all. The response that follows is V-shaped. It starts with the broadest conceptual and methodological issues and funnels down to matters arising from specific empirical studies.

Since the Industrial Revolution, human societies have experienced high and sustained rates of economic growth. Recent explanations of this sudden and massive change in economic history have held that modern growth results from an acceleration of innovation. But it is unclear why the rate of innovation drastically accelerated in England in the eighteenth century. An important factor might be the alteration of individual preferences with regard to innovation resulting from the unprecedented living standards of the English during that period, for two reasons. First, recent developments in economic history challenge the standard Malthusian view according to which living standards were stagnant until the Industrial Revolution. Pre-industrial England enjoyed a level of affluence that was unprecedented in history. Second, behavioral sciences have demonstrated that the human brain is designed to respond adaptively to variations in resources in the local environment. In particular, Life History Theory, a branch of evolutionary biology, suggests that a more favorable environment (high resources, low mortality) should trigger the expression of future-oriented preferences. In this paper, I argue that some of these psychological traits – a lower level of time discounting, a higher level of optimism, decreased materialistic orientation, and a higher level of trust in others – are likely to increase the rate of innovation. I review the evidence regarding the impact of affluence on preferences in contemporary as well as past populations, and conclude that the impact of affluence on neurocognitive systems may partly explain the modern acceleration of technological innovations and the associated economic growth.

Baumard suggests that the advent, through phenotypic plasticity mechanisms, of future-oriented preferences and creative mindsets in eighteenth-century Great Britain explains the wave of innovations that drove the British Industrial Revolution. We argue that, although this approach is promising, Baumard's model would benefit from being supplemented by demographic, economic, and sociological explanations independent of Life History Theory (LHT).

Invention is an investment in which the costs of the Research and Development (R&D) project balance future returns. Those returns depend on objective factors like wage and capital costs but also on subjective factors because they are future projections. The more optimistic the inventor, the higher are the projected returns. Baumard uses Life History Theory (LHT) to relate optimism to the affluence of inventors and their societies.

Current empirical evidence does not seem to confirm that an improvement in living conditions is the cause of the shift in the human mindset toward innovation and long-term risky investment. However, it may well be one of the conditions for greater tolerance of income inequality in exchange for a steady increase in average income.

What impelled the Industrial Revolution's spectacular economic growth? Life History Theory, Baumard argues, explains how England's world-supreme affluence psychologically fostered innovation; moreover, wherever similar affluence abounds, a “civilizing process” bringing enlightenment and democracy is apt to evolve. Baumard insightfully analyzes a “constellation of affluence” but proffers somewhat whiggish history given England's prior and unique proto-capitalist culture of economic liberty and individualism.

The most general theory of life history evolution, that of r versus K selection, implies that innovation in the form of plasticity is more likely to be adaptive under poor rather than good resource conditions, the opposite of how Baumard has it. However, this does focus on benefits rather than costs, and including both allows for greater diversity of outcomes.

Is it true that innovation occurs only in abundant environments? Baumard defends that increased standards of living are a necessary condition for a change in life history strategy to help understand the Industrial Revolution. Here, we argue that many examples of innovations occur in scarce environments when there is near-zero opportunity cost. We suggest potential psychological pathways to explain this dual-cognitive process.

It is emphasized that environmental predictability is another important condition that plays roles in slow strategies that are related to innovation; that economic inequality, except as measured by Gross Domestic Product (GDP) per capita, influences innovation; and that switching global life history from a slow to a fast strategy is a response adopted in response to new challenges during the post-Industrial Revolution period.

History is a potential tool for cognitive scientists interested in metacognitive categories like “creativity” and “innovation.” As a way of thinking, history suggests alternative accounts of the development of innovation and growth, for example. Life History Theory is one such account, but its roots in the Industrial Revolution make it a problematic tool for telling the history of that period.

I argue that the increased rate of innovation in eighteenth-century England cannot be understood without accounting for the unprecedented level of contact between England and other societies as a consequence of sixteenth-century colonialism. I propose cultural interconnectedness and in-group cooperation as two potential alternative explanations for the psychological changes and innovative behavior described by Baumard.

Baumard's perspective asserts that “opportunity is the mother of innovation,” in contrast to the adage ascribing this role to necessity. Drawing on behavioral ecology and cognition, we propose that both extremes – affluence and scarcity – can drive innovation. We suggest that the types of innovations at these two extremes differ and that both rely on mechanisms operating on different time scales.

Did affluence lead to psychological changes such as reduced discounting, and did these changes facilitate the innovation associated with the Industrial Revolution? I argue that claims of this sort are best made when they can be supported by causal evidence and good psychological measurement. When we have neither identifying variation nor adequate measures, the toolbox of psychologists is not useful.