Adrian Currie

Researchers in the life sciences often make uniqueness attributions; about branching events generating new species, the developmental processes generating novel traits and the distinctive cultural selection pressures faced by hominins. Yet since uniqueness implies non-recurrence, such attributions come freighted with epistemic consequences. Drawing on the work of Aviezer Tucker, we show that a common reaction to uniqueness attributions is pessimism: both about the strength of candidate explanations as well as the ability to even generate such explanations. Looking at two case studies—elephant trunks and human teaching—we develop a more optimistic account. As we argue, uniqueness attributions are revisable claims about the availability of several different kinds of comparators. Yet even as researchers investigate the availability of such comparators, they are able to mobilize complex sets of empirical and theoretical tools. Rather than hindering scientific investigation, then, we argue that uniqueness attributions often spur the generation of a range of epistemic goods.

Debate about the epistemic prowess of historical science has focused on local underdetermination problems generated by a lack of historical data; the prevalence of information loss over geological time, and the capacities of scientists to mitigate it. Drawing on Leonelli’s recent distinction between ‘phenomena-time’ and ‘data-time’ I argue that factors like data generation, curation and management significantly complexifies and undermines this: underdetermination is a bad way of framing the challenges historical scientists face. In doing so, I identify circumstances of epistemic scarcity where underdetermination problems are particularly salient, and discuss cases where legacy data—data generated using differing technologies and systems of practice—are drawn upon to overcome underdetermination. This suggests that one source of overcoming underdetermination is our knowledge of science’s past. Further, data-time makes agnostic positions about the epistemic fortunes of scientists working under epistemic scarcity more plausible. But agnosticism seems to leave philosophers without much normative grip. So, I sketch an alternative approach: focusing on the strategies scientists adopt to maximize their epistemic power in light of the resources available to them.

Despite wide recognition that speculation is critical for successful science, philosophers have attended little to it. When they have, speculation has been characterized in narrowly epistemic terms: a hypothesis is speculative due to its (lack of) evidential support. These ‘evidence-first’ accounts provide little guidance for what makes speculation productive or egregious, nor how to foster the former while avoiding the latter. I examine how scientists discuss speculation and identify various functions speculations play. On this basis, I develop a ‘function-first’ account of speculation. This analysis grounds a richer discussion of when speculation is egregious and when it is productive, based in both fine-grained analysis of the speculation’s purpose, and what I call the ‘epistemic situation’ scientists face.

Consideration of evidence and data in historical science is dominated by textual metaphor: we reconstruct the past on the basis of various incomplete records. I suggest that although textual metaphors are often apt, they also lead philosophers and scientists to think about historical evidence in particular ways, and that other perspectives might be fruitful. Towards this, I explore the notion of natural historical evidence being thought of as ‘ruins’. This has several potential benefits. First, the architectural aspect of the metaphor emphasizes the contingency of historical subjects and the coherency of design-based reconstruction. Second, historical data, like ruins, are co-constructed, involving intimate interaction with materials.

Significant work in the philosophy of history has focused on the writing of historiographical narratives, isolated from the rest of what historians do. Taking my cue from the philosophy of science in practice, I suggest that understanding historical narratives as embedded within historical practice more generally is fruitful. I illustrate this by bringing a particular instance of historical practice, Natalie Lawrence’s explanation of the sad fate of Winston the platypus, into dialogue with some of Louis Mink’s arguments in favour of anti-realism about historical events. Attending to how historians seek out and utilize archival resources puts serious pressure on these arguments, motivates realist positions, and re-focuses the philosophy of history towards making sense of historiography as a part of the diversity of historians’ interests.

Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby real-world targets are constructed. In such circumstances, it is unclear what the model is supposed to resemble. Further, while fictionalists often require that models qua models have their content in virtue of construal or interpretation, in some engineering and design contexts success-conditions do not require such content—all that is required is that the model generates the required outputs. I take these points to motivate a view which accommodates fictionalism, but is broader. I articulate and defend an account of models as tools: specifically, material objects which are put to particular uses in particular contexts.

Biologists often study living systems in light of their having evolved, of their being the products of various processes of heredity, adaptation, ancestry, and so on. In their investigations, then, biologists think comparatively: they situate lineages into models of those evolutionary processes, comparing their targets with ancestral relatives and with analogous evolutionary outcomes. This element characterizes this mode of investigation - 'comparative thinking' - and puts it to work in understanding why biological science takes the shape it does. Importantly, comparative thinking is local: what we can do with knowledge of a lineage is limited by the evolutionary processes into which it fits. In light of this analysis, the Element examines the experimental study of animal cognition, and macroevolutionary investigation of the 'shape of life', demonstrating the importance of comparative thinking in understanding both the power and limitations of biological knowledge.

We argue that narratives are central to the success of historical reconstruction. Narrative explanation involves tracing causal trajectories across time. The construction of narrative, then, often involves postulating relatively speculative causal connections between comparatively well-established events. But speculation is not always idle or harmful: it also aids in overcoming local underdetermination by forming scaffolds from which new evidence becomes relevant. Moreover, as our understanding of the past’s causal milieus become richer, the constraints on narrative plausibility become increasingly strict: a narrative’s admissibility does not turn on mere logical consistency with background data. Finally, narrative explanation and explanation generated by simple, formal models complement one another. Where models often achieve isolation and precision at the cost of simplification and abstraction, narratives can track complex changes in a trajectory over time at the cost of simplicity and precision. In combination both allow us to understand and explain highly complex historical sequences.

Here’s something I’m willing to claim we know: Homo sapiens, in particular the Polynesian settlers who first arrived in Aotearoa around the twelfth century, take the lion’s share of causal blame for the extinction of a lineage of enormous flightless birds: the moa. Stretching to three metres at their tallest, moa were a distinctive and remarkable feature of Aotearoa’s primeval forests, playing the main browser and grazer role in this unique bird-based ecosystem. Once humans turned up forests were burned, moa were stalked, and human-0introduced arrivals such as kiore had dramatic ecological repercussions. Within a few centuries, the moa were gone.

Both paleobiology and investigations of ‘major evolutionary transitions’ are intimately concerned with the macroevolutionary shape of life. It is surprising, then, how little studies of major transitions are informed by paleontological perspectives and. I argue that this disconnect is partially justified because paleobiological investigation is typically ‘phenomena-led’, while investigations of major transitions are ‘theory-led’. The distinction turns on evidential relevance: in the former case, evidence is relevant in virtue of its relationship to some phenomena or hypotheses concerning those phenomena; in the latter, evidence is relevant in virtue of providing insights into, or tests of, an abstract body of theory. Because paleobiological data is by-and-large irrelevant to the theory which underwrites the traditional conception of major transitions, it is of limited use to that research program. I suggest that although the traditional conception of major transitions is neither ad-hoc or problematically incomplete, its promise of providing unificatory explanations of the transitions is unlikely to be kept. Further, examining paleobiological investigations of mass extinctions and organogenesis, I further argue that whether or not transitions in paleobiology count as ‘major’ turns on how we conceive of major transitions ; although major transitions potentially have a unified theoretical basis, recent developments suggest that investigations are becoming increasingly phenomena-led; adopting phenomena-led investigations maximizes the evidence available to paleobiologists.

There has been much discussion of the moral, legal and prudential implications of geoengineering, and of governance structures for both the research and deployment of such technologies. However, insufficient attention has been paid to how such measures might affect geoengineering in terms of the incentive structures which underwrite scientific progress. There is a tension between the features that make science productive, and the need to govern geoengineering research, which has thus far gone underappreciated. I emphasize how geoengineering research requires governance which reaches beyond science’s traditional boundaries, and moreover requires knowledge which itself reaches beyond what we traditionally expect scientists to know about. How we govern emerging technologies should be sensitive to the incentive structures which drive science.

It is often thought that the vindication of experimental work lies in its capacity to be revelatory of natural systems. I challenge this idea by examining laboratory experiments in ecology. A central task of community ecology involves combining mathematical models and observational data to identify trophic interactions in natural systems. But many ecologists are also lab scientists: constructing microcosm or ‘bottle’ experiments, physically realizing the idealized circumstances described in mathematical models. What vindicates such ecological experiments? I argue that ‘extrapolationism’, the view that ecological lab work is valuable because it generates truths about natural systems, does not exhaust the epistemic value of such practices. Instead, bottle experiments also generate ‘understanding’ of both ecological dynamics and empirical tools. Some lab work, then, aids theoretical understanding, as well as targeting hypotheses about nature. 1Introduction2Trophic Interactions and Observational Techniques3Cryptic Dynamics in Bottle Experiments4Extrapolationism 4.1Ecological possibility and actuality4.2Ecological heterogeneity5Understanding 5.1The epistemic good of understanding5.2Bottle experiments as understanding-generators5.3How understanding travels6Conclusion

Common philosophical accounts of creativity align creative products and processes with a particular kind of agency: namely, that deserving of praise or blame. Considering evolutionary examples, we explore two ways of denying that creativity requires forms of agency. First, we argue that decoupling creativity from praiseworthiness comes at little cost: accepting that evolutionary processes are non-agential, they nonetheless exhibit many of the same characteristics and value associated with creativity. Second, we develop a ‘product-first’ account of creativity by which a process is creative just in case it gives rise to products deserving of certain forms of aesthetic engagement.

Abstract‘Behavioural modernity’ isn’t what it used to be. Once conceived as an integrated package of traits demarcated by a clear archaeological signal in a specific time and place, it is now disparate, archaeologically equivocal, and temporally and spatially spread. In this paper we trace behavioural modernity’s empirical and theoretical developments over the last three decades, as surprising discoveries in the material record, as well the reappraisal of old evidence, drove increasingly sophisticated demographic, social and cultural models of behavioural modernity. We argue, however, that some approaches to identifying and categorizing modernity have not kept up with this new picture. This is due to what we term ‘Rubicon expectations’: classificatory and interpretive practices which look for or assume clear demarcations in behavioural and cultural processes. We develop a philosophical account of ‘investigative disintegration’ to capture how our understanding of behavioural modernity has changed, and how Rubicon-based practices have become inadequate. Disintegration, in the form we analyse, occurs when scientists’ conception of a phenomenon shifts sufficiently to reshape an investigation’s epistemic structure. For behavioural modernity, the explanatory weight which once lay on identifying ‘switch-points’ in the innate suite of hominin cognitive capacities, lies now in understanding the social and demographic environments that were capable of sustaining and nourishing more complex material cultures. Finally, we argue that the phenomenon itself has not disintegrated to the point that we are left with no interesting explanandum: for all its mosaic, disparate nature, there are still good reasons for behavioural modernity to retain its central place in investigation of our species' origins.

Cognitive archaeologists infer from material remains to the cognitive features of past societies. We characterize cognitive archaeology in terms of trace-based reasoning, which in the case of cognitive archaeology involves inferences drawing upon background theory linking objects from the archaeological record to cognitive features. We analyse such practices, examining work on cognitive evolution, language, and musicality. We argue that the central epistemic challenge for cognitive archaeology is often not a paucity of material remains, but insufficient constraint from cognitive theories. However, we also argue that the success of cognitive archaeology does not necessarily require well-developed cognitive theories: Success might instead lead to them.

I develop an account of the relationship between aesthetics and knowledge, focusing on scientific practice. Cognitivists infer from ‘partial sensitivity’—aesthetic appreciation partly depends on doxastic states—to ‘factivity’, the idea that the truth or otherwise of those beliefs makes a difference to aesthetic appreciation. Rejecting factivity, I develop a notion of ‘epistemic engagement’: partaking genuinely in a knowledge-directed process of coming to epistemic judgements, and suggest that this better accommodates the relationship between the aesthetic and the epistemic. Scientific training (and other knowledge-directed activities), I argue, involves ‘attunement’: the co-option of aesthetic judgements towards epistemic ends. Thus, the connection between aesthetic appreciation and knowledge is psychological and contingent. This view has consequences for the warrant of aesthetic judgement in science, namely, the locus of justification is those processes of attunement, not the aesthetic judgements themselves.

Caitlin Wylie’s “Preparing Dinosaurs: the work behind the scenes” (MIT Press 2021) provides a rich ethnographic analysis of the work of fossil preparators. On her account, knowledge in vertebrate paleontology is mediated through a three-way division of labour between paleontologists, preparators and volunteers, each with their own role, expertise and responsibility. In this review, I develop her notion of ‘preparation as knowledge’, focusing in particular on the nature of objectivity in paleontological knowledge and on the middle-road she indicates between constructivist and realist approaches to epistemology.

Many accounts of scientific modeling conceive of models as fictions: scientists interact with models in ways analogous to various aesthetic objects. Fictionalists follow most other accounts of modeling by taking them to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby real-world targets are constructed. In such circumstances, it is unclear what the model is supposed to resemble. Further, while fictionalists often require that models qua models have their content in virtue of construal or interpretation, in some engineering and design contexts success-conditions do not require such content—all that is required is that the model generates the required outputs. I take these points to motivate a view which accommodates fictionalism, but is broader. I articulate and defend an account of models as tools: specifically, material objects which are put to particular uses in particular contexts.

Angela Potochnik’s Idealization and the Aims of Science defends an ambitious and systematic account of scientific knowledge: ultimately science pursues human understanding rather than truth. Potochnik argues that idealization is rampant and unchecked in science. Further, given that idealizations involve departures from truth, this suggests science is not primarily about truth. I explore the relationship between truths about causal patterns and scientific understanding in light of this, and suggest that Potochnik underestimates the importance and power of highly particular narrative explanations.

Angela Potochnik’s Idealization and the Aims of Science (Chicago) defends an ambitious and systematic account of scientific knowledge: ultimately science pursues human understanding rather than truth. Potochnik argues that idealization is rampant and unchecked in science. Further, given that idealizations involve departures from truth, this suggests science is not primarily about truth. I explore the relationship between truths about causal patterns and scientific understanding in light of this, and suggest that Potochnik underestimates the importance and power of highly particular narrative explanations.