We strongly sympathize with the aim of a synthetic construction of a “theory of intentional change.” We think, however, that to break the current stagnation in evolutionary social science we need to follow more in the tracks of recent moves toward a causal–mechanistic understanding of evolution in biology (Laubichler & Maienschein Reference Laubichler, Maienschein and Ruse2013) than in the tracks of neo-Darwinism. Darwinism – which is what Wilson et al. really mean by “evolution” – is necessary but not sufficient here; we also need to mind the multilevel organization that evolution produces and that scaffolds Darwinian dynamics.

A fundamental role of Darwinism for adaptation in a generalized sense has been argued convincingly by evolutionary epistemologists following Campbell (Reference Campbell, Barringer, Blanksten and Mack1965; Reference Campbell and Schilpp1974). The idea is that if we disaggregate macroscopic adaptive systems, we will sooner or later find a level or stage on which intrinsic adaptive behavior no longer can be argued to exist. So if we would like to explain adaptation (including foresight) in a way that is consistent with naturalism, we must understand how systems with entirely “blind” components can come to exhibit or embody foresight. The only process known to be capable of such a feat is what Campbell refers to as Blind-Variation-Selective-Retention (BVSR). Indeed, in all cases of adaptation found so far, explanations appear to have gone through the same stages: providence (by a designer), instruction (such as coin in wax), and finally BVSR (Cziko Reference Cziko1995; Reference Cziko2000). This holds for organic evolution, the adaptive immune system, neural systems, and – to a much more limited extent – social systems. However, as we will argue, there appears to be also a fourth stage that modifies that third selectionist stage.

The appeal of Darwinism has been strong also in social science, where examples of selection and retention in populations of variants are easy to find. We have Darwinian evolutionary economics following Nelson and Winter (Reference Nelson and Winter1982) and Dosi (Reference Dosi1982), the “memetics” movement following Dawkins (Reference Dawkins1976), the related replicator–interactor ontology for universal Darwinism introduced by Hull (Reference Hull and Plotkin1988), and the so-called dual-inheritance tradition in anthropology following Boyd and Richerson (Reference Boyd and Richerson1985) and Cavalli-Sforza and Feldman (Reference Cavalli-Sforza and Feldman1981). Boyd and Richerson (Reference Boyd and Richerson2005) describe their approach as a mix between rational choice theory and population genetics, and that is not far from being generally true for current evolutionary approaches to social systems – including that proposed by Wilson et al.

Population genetics focuses on the fate of variants in populations subject to selection pressures that are independent of time, frequency, and not least of all, the evolutionary process itself; it treats development as a black box (Amundson Reference Amundson, Sarkar and Plutynski2008) and assumes that the system is near-decomposable (Simon Reference Simon1996). This may sometimes work as a basis for models of gradual innovation of technology and behavior, which is in practice also how such models have been used. But societal systems are characterized by incessant radical innovation – which is the emergence of qualitative novelty – and they are not generally possible to separate from the rest of the system in a Simonean fashion. This causes problems for formal modeling; not only the state but also the ontology of the system changes on similar time scales (Lane & Maxfield Reference Lane and Maxfield2005). BVSR is embedded in the very structures that it produces – it reappears on emergent levels of organization, and it even reinvents new versions of itself (e.g., clonal and neuronal group selection; see above and Andersson Reference Andersson2008; Reference Andersson2011).

Without radical innovation one is confined to special cases of gradual adjustment of systems to meet predefined functional specifications – similar to what is the case in genetics algorithms (Holland Reference Holland1992). The examples chosen by Wilson et al. indeed represent a sort of social genetic algorithms, which is fine; but the question is how far this goes toward a science of intentional change.

The fourth explanatory stage alluded to above would then be the realization that BVSR must act through systems whose path-dependent organization and dynamics introduce other principles of evolution alongside them, and from which BVSR cannot be disentangled. BVSR is necessary but not sufficient. Along those lines, evolutionary biology has undergone a revolutionary change since the time when it was injected into the above disciplines in social science. Development (in a broad sense) has become an integral part of evolutionary theory, and it is no longer possible to ignore the constraining and channeling effects of the structures that emerge in evolution; for example, evolutionary developmental biology (e.g., Arthur Reference Arthur2011), niche construction theory (Odling-Smee et al. Reference Odling-Smee, Laland and Feldman2003), generative entrenchment (Wimsatt & Griesemer Reference Wimsatt, Griesemer, Sansom and Brandon2007), and developmental systems theory (Oyama et al. Reference Oyama, Griffiths and Gray2001).

Although Wilson et al. repeatedly refer to development, it is not an integral part of their approach. In other words, they do not draw the consequences of minding development, and even less of the notion that BVSR is scaffolded by the structures that are generated in evolution. They see evolution as reducible to BVSR on a single level with only minor adjustments.

So what if we by “intentional change” mean large-scale societal problems that are deeply embedded? What if we, for example, want to understand how to replace unsustainable technologies rather than how to reduce underage smoking? Wilson et al. motivate their work in an admirable way in that direction, but their examples are of a simple social character that we think represents special cases rather than stepping stones on the way to those vexing “wicked problems” (e.g., Rittel & Webber Reference Rittel and Webber1973) that we face in modern society. We think that when it comes to unifying social and natural sciences – including Darwinism – new developmental theories in evolutionary biology fall much better into place as a source of inspiration (see Andersson et al. Reference Andersson, Törnberg and Törnberg2014).

The bedfellows of such a synthesis include developmental evolutionary rather than neo-Darwinian evolutionary biology, systems-level rather than reductionist theories in the social sciences, and developmental rather than behavioral psychology. Although one does not strictly preclude the other, these divisions (which cut just as much within as between disciplines) signify quite profoundly different conceptions about what a science ought to be like. What is needed to cut across those divides is a deeper methodological discussion.