The paper entitled “Tool types and the establishment of the Late Palaeolithic (Later Stone Age) cultural taxonomic system in the Nile Valley”  submitted by A. Leplongeon offers a review of the many cultural taxonomic in use for the prehistory – especially the Late Palaeolithic/Late Stone Age – of the Nile Valley (Leplongeon 2023). This paper was first developed for a special conference session convened at the EAA annual meeting in 2021 and is intended for an edited volume on the topic of typology and taxonomy in archaeology.

Issues of cultural taxonomy have recently risen to the forefront of archaeological debate (Reynolds and Riede 2019; Ivanovaitė et al. 2020; Lyman 2021). Archaeological systematics, most notably typology, have roots in the research history of a particular region and period (e.g. Plutniak 2022); commonly, different scholars employ different and at times incommensurable systems, often leading to a lack of clarity and inter-regional interoperability. African prehistory is not exempt from this debate (e.g. Wilkins 2020) and, in fact, such a situation is perhaps nowhere more apparent than in the iconic Nile Valley. The Nile Valley is marked by a complex colonial history and long-standing archaeological interest from a range of national and international actors. It is also a vital corridor for understanding human dispersals out of and into Africa, and along the North African coastal zone. As Leplongeon usefully reviews, early researchers have, as elsewhere, proposed a variety of archaeological cultures, the legacies of which still weigh in on contemporary discussions. In the Nile Valley, these are the Kubbaniyan (23.5-19.3 ka cal. BP), the Halfan (24-19 ka cal. BP), the Qadan (20.2-12 ka cal BP), the Afian (16.8-14 ka cal. BP) and the Isnan (16.6-13.2 ka cal. BP) but their temporal and spatial signatures remain in part poorly constrained, or their epistemic status debated. Leplongeon’s critical and timely chronicle of this debate highlights in particular the vital contributions of the many female prehistorians who have worked in the region – Angela Close (e.g. 1978; 1977) and Maxine Kleindienst (e.g. 2006) to name just a few of the more recent ones – and whose earlier work had already addressed, if not even solved many of the pressing cultural taxonomic issues that beleaguer the Late Palaeolithic/Later Stone Age record of this region. 

Leplongeon and colleagues (Leplongeon et al. 2020; Mesfin et al. 2020) have contributed themselves substantially to new cultural taxonomic research in the wider region, showing how novel quantitative methods coupled with research-historical acumen can flag up and overcome the shortcomings of previous systematics. Yet, as Leplongeon also notes, the cultural taxonomic framework for the Nile Valley specifically has proven rather robust and does seem to serve its purpose as a broad chronological shorthand well. By the same token, she urges due caution when it comes to interpreting these lithic-based taxonomic units in terms of past social groups. Cultural systematics are essential for such interpretations, but age-old frameworks are often not fit for this purpose. New work by Leplongeon is likely to not only continue the long tradition of female prehistorians working in the Nile Valley but also provides an epistemologically and empirically more robust platform for understanding the social and ecological dynamics of Late Palaeolithic/Later Stone Age communities there.

 

Bibliography 

Close, Angela E. 1977. The Identification of Style in Lithic Artefacts from North East Africa. Mémoires de l’Institut d’Égypte 61. Cairo: Geological Survey of Egypt.

Close, Angela E. 1978. “The Identification of Style in Lithic Artefacts.” World Archaeology 10 (2): 223–37. https://doi.org/10.1080/00438243.1978.9979732

Ivanovaitė, Livija, Serwatka, Kamil, Steven Hoggard, Christian, Sauer, Florian and Riede, Felix. 2020. “All These Fantastic Cultures? Research History and Regionalization in the Late Palaeolithic Tanged Point Cultures of Eastern Europe.” European Journal of Archaeology 23 (2): 162–85. https://doi.org/10.1017/eaa.2019.59

Kleindienst, M. R. 2006. “On Naming Things: Behavioral Changes in the Later Middle to Earlier Late Pleistocene, Viewed from the Eastern Sahara.” In Transitions Before the Transition. Evolution and Stability in the Middle Paleolithic and Middle Stone Age, edited by E. Hovers and Steven L. Kuhn, 13–28. New York, NY: Springer.

Leplongeon, Alice. 2023. “Tool Types and the Establishment of the Late Palaeolithic (Later Stone Age) Cultural Taxonomic System in the Nile Valley.” https://doi.org/10.5281/zenodo.8115202

Leplongeon, Alice, Ménard, Clément, Bonhomme, Vincent and Bortolini, Eugenio. 2020. “Backed Pieces and Their Variability in the Later Stone Age of the Horn of Africa.” African Archaeological Review 37 (3): 437–68. https://doi.org/10.1007/s10437-020-09401-x

Lyman, R. Lee. 2021. “On the Importance of Systematics to Archaeological Research: The Covariation of Typological Diversity and Morphological Disparity.” Journal of Paleolithic Archaeology 4 (1): 3. https://doi.org/10.1007/s41982-021-00077-6

Mesfin, Isis, Leplongeon, Alice, Pleurdeau, David, and Borel, Antony. 2020. “Using Morphometrics to Reappraise Old Collections: The Study Case of the Congo Basin Middle Stone Age Bifacial Industry.” Journal of Lithic Studies 7 (1): 1–38. https://doi.org/10.2218/jls.4329

Plutniak, Sébastien. 2022. “What Makes the Identity of a Scientific Method? A History of the ‘Structural and Analytical Typology’ in the Growth of Evolutionary and Digital Archaeology in Southwestern Europe (1950s–2000s).” Journal of Paleolithic Archaeology 5 (1): 10. https://doi.org/10.1007/s41982-022-00119-7

Reynolds, Natasha, and Riede, Felix. 2019. “House of Cards: Cultural Taxonomy and the Study of the European Upper Palaeolithic.” Antiquity 93 (371): 1350–58. https://doi.org/10.15184/aqy.2019.49

Wilkins, Jayne. 2020. “Is It Time to Retire NASTIES in Southern Africa? Moving Beyond the Culture-Historical Framework for Middle Stone Age Lithic Assemblage Variability.” Lithic Technology 45 (4): 295–307. https://doi.org/10.1080/01977261.2020.1802848

“Archaeology, Typology and Machine Epistemology” submitted by G. Lucas (1) offers a refreshing and welcome reflection on the role of computer-based practice, type-thinking and approaches to typology in the age of big data and the widely proclaimed ‘Third Science Revolution’ (2–4). At the annual meeting of the EAA in Maastricht in 2017, a special thematic block was dedicated to issues and opportunities linked to the Third Science Revolution in archaeology “because of [its] profound and wide ranging impact on practice and theory in archaeology for the years to come” (5). Even though the Third Science Revolution, as influentially outlined by Kristiansen in 2014 (2), has occasionally also been met with skepticism and critique as to its often implicit scientism and epistemological naivety (6–8), archaeology as a whole seems largely euphoric as to the promises of the advancing ‘revolution’. As Lucas perceptively points out, some even regard it as the long-awaited opportunity to finally fulfil the ambitions and goals of Anglophone processualism. The irony here, as Lucas rightly notes, is that early processualists initially foregrounded issues of theory and scientific epistemology, while much work conducted under the banner of the Third Science Revolution, especially within its computational branches, does not. Big data advocates have echoed Anderson’s much-cited “end of theory” (9) or at least emphatically called for an ‘empirization’ and ‘computationalization’ of theory, often under the banner of ‘data-driven archaeology’ (10), yet typically without much specification of what this is supposed to mean for archaeological theory and reflexivity. The latter is indeed often openly opposed by archaeological Third Science Revolution enthusiasts, arguably because it is viewed as part of the supposedly misguided ‘post-modernist’ project.

Lucas makes an original meta-archaeological contribution here and attempts to center the epistemological, ontological and praxeological dimensions of what is actually – in situated archaeological praxis and knowledge-production – put at stake by the mobilization of computers, algorithms and artificial intelligence (AI), including its many but presently under-reflected implications for ordering practices such as typologization. Importantly, his perspective thereby explicitly and deliberately breaks with the ‘normative project’ in traditional philosophy of science, which sought to nail down a universal, prescriptive way of doing science and securing scientific knowledge. He instead focuses on the practical dimensions and consequences of computer-reliant archaeologies, what actually happens on the ground as researchers try to grapple with the digital and the artefactual and try to negotiate new insights and knowledge, including all of the involved messiness – thereby taking up the powerful impetus of the broader practice turn in interdisciplinary science studies and STS (Science and Technology Studies (11)) (12–14), which have recently also re-oriented archaeological self-observation, metatheory and epistemology (15). This perspective on the dawning big data age in archaeology and incurred changes in the status, nature and aims of type-thinking produces a number of important insights, which Lucas fruitfully discusses in relation to promises of ‘automation’ and ‘novelty’ as these feature centrally in the rhetorics and politics of the Third Science Revolution. 

With regard to automation, Lucas makes the important point that machine or computer work as championed by big data proponents cannot adequately be qualified or understood if we approach the issue from a purely time-saving perspective. The question we have to ask instead is what work do machines actually do and how do they change the dynamics of archaeological knowledge production in the process? In this optic, automation and acceleration achieved through computation appear to make most sense in the realm of the uncontroversial, in terms of “reproducing an accepted way of doing things” as Lucas says, and this is precisely what can be observed in archaeological practice as well. The ramifications of this at first sight innocent realization are far-reaching, however. If we accept the noncontroversial claim that automation partially bypasses the need for specialists through the reproduction of already “pre-determined outputs”, automated typologization would primarily be useful in dealing with and synthesizing larger amounts of information by sorting artefacts into already accepted types rather than create novel types or typologies. If we identity the big data promise at least in part with automation, even the detection of novel patterns in any archaeological dataset used to construct new types cannot escape the fact that this novelty is always already prefigured in the data structure devised. The success of ‘supervised learning’ in AI-based approaches illustrates this. Automation thus simply shifts the epistemological burden back to data selection and preparation but this is rarely realized, precisely because of the tacit requirement of broad non-contentiousness. 

Minimally, therefore, big data approaches ironically curtail their potential for novelty by adhering to conventional data treatment and input formats, rarely problematizing the issue of data construction and the contested status of (observational) data themselves. By contrast, they seek to shield themselves against such attempts and tend to retain a tacit universalism as to the nature of archaeological data. Only in this way is it possible to claim that such data have the capacity to “speak for themselves”. To use a concept borrowed from complexity theory, archaeological automation-based type-construction that relies on supposedly basal, incontrovertible data inputs can only ever hope to achieve ‘weak emergence’ (16) – ‘strong emergence’ and therefore true, radical novelty require substantial re-thinking of archaeological data and how to construct them. This is not merely a technical question as sometimes argued by computational archaeologies – for example with reference to specifically developed, automated object tracing procedures – as even such procedures cannot escape the fundamental question of typology: which kind of observations to draw on in order to explore what aspects of artefactual variability (and why). The focus on readily measurable features – classically dimensions of artefactual form – principally evades the key problem of typology and ironically also reduces the complexity of artefactual realities these approaches assert to take seriously. The rise of computational approaches to typology therefore reintroduces the problem of universalism and, as it currently stands, reduces the complexity of observational data potentially relevant for type-construction in order to enable to exploration of the complexity of pattern. It has often been noted that this larger configuration promotes ‘data fetishism’ and because of this alienates practitioners from the archaeological record itself – to speak with Marxist theory that Lucas briefly touches upon. We will briefly return to the notion of ‘distance’ below because it can be described as a symptomatic research-logical trope (and even a goal) in this context of inquiry. 

In total, then, the aspiration for novelty is ultimately difficult to uphold if computational archaeologies refuse to engage in fundamental epistemological and reflexive self-engagement. As Lucas poignantly observes, the most promising locus for novelty is currently probably not to be found in the capacity of the machines or algorithms themselves, but in the modes of collaboration that become possible with archaeological practitioners and specialists (and possibly diverse other groups of knowledge stakeholders). In other words, computers, supercomputers and AI technologies do not revolutionize our knowledge because of their superior computational and pattern-detection capacities – or because of some mysterious ‘superintelligence’ – but because of the specific ‘division of labour’ they afford and the cognitive challenge(s) they pose. Working with computers and AI also often requires to ask new questions or at least to adapt the questions we ask. This can already be seen on the ground, when we pay attention to how machine epistemologies are effectively harnessed in archaeological practice (and is somewhat ironic given that the promise of computational archaeology is often identified with its potential to finally resolve "long-standing (old) questions"). The Third Science Revolution likely prompts a consequential transformation in the structural and material conditions of the kinds of ‘distributed’ processes of knowledge production that STS have documented as characteristic for scientific discoveries and knowledge negotiations more generally (14, 17, 18). This ongoing transformation is thus expected not only to promote new specializations with regard to the utilization of the respective computing infrastructures emerging within big data ecologies but equally to provoke increasing demand for new ways of conceptualizing observations and to reformulate the theoretical needs and goals of typology in archaeology. The rediscovery of reflexivity as an epistemic virtue within big data debates would be an important step into this direction, as it would support the shared goal of achieving true epistemic novelty, which, as Lucas points out, is usually not more than an elusive self-declaration. Big data infrastructures require novel modes of human-machine synergy, which simply cannot be developed or cultivated in an atheoretical and/or epistemological disinterested space. 

Lucas’ exploration ultimately prompts us to ask big questions (again), and this is why this is an important contribution. The elephant in the room, of course, is the overly strong notion of objectivity on which much computational archaeology is arguably premised – linked to the vow to eventually construct ‘objective typologies’. This proclivity, however, re-tables all the problematic debates of the 1960s and – to speak with the powerful root metaphor of the machine fueling much of causal-mechanistic science (19, 20) – is bound to what A. Wylie (21) and others have called the ‘view from nowhere’. Objectivity, in this latter view, is defined by the absence of positionality and subjectivity – chiefly human subjectivity – and the promise of the machine, and by extension of computational archaeology, is to purify and thus to enhance processes of knowledge production by minimizing human interference as much as possible. The distancing of the human from actual processes of data processing and inference is viewed as positive and sometimes even as an explicit goal of scientific development. Interestingly, alienation from the archaeological record is framed as an epistemic virtue here, not as a burden, because close connection with (or even worse, immersion in) the intricacies of artefacts and archaeological contexts supposedly aggravates the problem of bias. The machine, in this optic, is framed as the gatekeeper to an observer-independent reality – which to the backdoor often not only re-introduces Platonian/Aristotelian pledges to a quasi-eternal fabric of reality that only needs to be “discovered” by applying the right (broadly nonhuman) means, it is also largely inconsistent with defendable and currently debated conceptions of scientific objectivity that do not fall prey to dogma.  

Furthermore, current discussions on the open AI ChatGPT have exposed the enormous and still under-reflected dangers of leaning into radical renderings of machine epistemology: precisely because of the principles of automation and the irreducible theory-ladenness of all data, ecologies such as ChatGPT tend to reinforce the tacit epistemological background structures on which they operate and in this way can become collaborators in the legitimization and justification of the status quo (which again counteracts the potential for novelty) – they reproduce supposedly established patterns of thought. This is why, among other things, machines and AI can quickly become perpetuators of parochial and neocolonial projects – their supposed authority creates a sense of impartiality that shields against any possible critique. With Lucas, we can thus perhaps cautiously say that what is required in computational archaeology is to defuse the authority of the machine in favour of a new community archaeology that includes machines as (fallible) co-workers. Radically put, computers and AI should be recognized as subjects themselves, and treated as such, with interesting perspectives on team science and collaborative practice.

 

Bibliography

1. Lucas, G. (2022). Archaeology, Typology and Machine Epistemology. https:/doi.org/10.5281/zenodo.7620824.

2. Kristiansen, K. (2014). Towards a New Paradigm? The Third Science Revolution and its Possible Consequences in Archaeology. Current Swedish Archaeology 22, 11–34. https://doi.org/10.37718/CSA.2014.01.

3. Kristiansen, K. (2022). Archaeology and the Genetic Revolution in European Prehistory. Elements in the Archaeology of Europe. https://doi.org/10.1017/9781009228701

4. Eisenhower, M. S. (1964). The Third Scientific Revolution. Science News 85, 322/332. https://www.sciencenews.org/archive/third-scientific-revolution.

5. The ‘Third Science Revolution’ in Archaeology. http://www.eaa2017maastricht.nl/theme4 (March 16, 2023).

6. Ribeiro, A. (2019). Science, Data, and Case-Studies under the Third Science Revolution: Some Theoretical Considerations. Current Swedish Archaeology 27, 115–132. https://doi.org/10.37718/CSA.2019.06

7. Samida, S. (2019). “Archaeology in times of scientific omnipresence” in Archaeology, History and Biosciences: Interdisciplinary Perspectives, pp. 9–22. https://doi.org/10.1515/9783110616651

8. Sørensen, T. F.. (2017). The Two Cultures and a World Apart: Archaeology and Science at a New Crossroads. Norwegian Archaeological Review 50, 101–115. https://doi.org/10.1080/00293652.2017.1367031

9. Anderson, C. (2008). The end of theory: The data deluge makes the scientific method obsolete. Wired. https://www.wired.com/2008/06/pb-theory/.

10. Gattiglia, G. (2015). Think big about data: Archaeology and the Big Data challenge. Archäologische Informationen 38, 113–124. https://doi.org/10.11588/ai.2015.1.26155

11. Hackett, E. J. (2008). The handbook of science and technology studies, Third edition, MIT Press/Society for the Social Studies of Science.

12. Ankeny, R., Chang, H., Boumans, M. and Boon, M. (2011). Introduction: philosophy of science in practice. Euro Jnl Phil Sci 1, 303. https://doi.org/10.1007/s13194-011-0036-4

13. Soler, L., Zwart, S., Lynch, M., Israel-Jost, V. (2014). Science after the Practice Turn in the Philosophy, History, and Social Studies of Science, Routledge.

14. Latour, B. and Woolgar, S. (1986). Laboratory life: the construction of scientific facts, Princeton University Press.

15. Chapman, R. and Wylie, A. (2016) Evidential reasoning in archaeology, Bloomsbury Academic.

16. Greve, J. and Schnabel, A. (2011). Emergenz: zur Analyse und Erklärung komplexer Strukturen, Suhrkamp.

17. Shapin, S., Schaffer, S. and Hobbes, T. (1985). Leviathan and the air-pump: Hobbes, Boyle, and the experimental life, including a translation of Thomas Hobbes, Dialogus physicus de natura aeris by Simon Schaffer, Princeton University Press.

18. Galison, P. L. and Stump, D. J. (1996).The Disunity of Science: Boundaries, Contexts, and Power, Stanford University Press.

19. Pepper, S. C. (1972). World hypotheses: a study in evidence, 7. print, University of California Press.

20. Hussain, S. T. (2019). The French-Anglophone divide in lithic research: A plea for pluralism in Palaeolithic Archaeology, Open Access Leiden Dissertations. https://hdl.handle.net/1887/69812 

21. A. Wylie, A. (2015). “A plurality of pluralisms: Collaborative practice in archaeology” in Objectivity in Science, pp. 189-210, Springer. https://doi.org/10.1007/978-3-319-14349-1_10

The paper entitled “Investigating relationships between technological variability and ecology in the Middle Gravettian (ca. 32-28 ky cal. BP) in France” [1] submitted by A. Vignoles and colleagues offers a robust and interesting new analysis of the niche differences between the Rayssian and Noaillian facies of the Middle Gravettian in France.

Understanding technological variability in the Palaeolithic is a long-standing challenge. Previous debates have vacillated between strong, quasi-ethnic culture-historical interpretations rooted in the traditional European school and extreme functional stances that would see artefact forms and their frequencies with assemblages conditioned by site function. While both positions have their merits, many empirical and conceptual caveats haunt them equally [see 2]. In this new study Vignoles and colleagues, so-called eco-cultural niche modelling is applied in an attempt to explore whether, and if so, which environmental background factors may have conditioned the emergence and persistence of two sub-cultural categories (facies) within the Middle Gravettian: the Rayssian and the Noaillian. These are are defined through, respectively, a specific knapping method and the presence of a specific burin type, and the occurrence of these seems divided by the Garonne River. Eco-cultural niche modelling has emerged as an archaeological application of distribution models widely employed in ecology, including palaeoecology, to understand organismal niche envelopes [3]. They constitute powerful tools for using the spatial and chronological information inherent in the archaeological record to up-scale interpretations of human-environment relations beyond individual site stratigraphies or dating series. Another important feature of such models is that their performance can, as Vignoles et al. also show, be formally evaluated and replicated. Following on from earlier applications of such techniques [e.g. 4], the authors here present an interesting study that uses very specific archaeological indicators – namely the Raysse method and the Noaillian burin – as defining features for the units (communities, traditions) whose adaptations they investigate. While broad tool types have previously been used as cultural taxonomic indicators in niche modelling studies [5], the present study is ambitious in its attempt to understand variability at a relatively small spatial scale. This mirrors equally interesting attempts of doing so in later prehistoric contexts [6].

Applications of niche modelling that use analytical units defined through archaeological characteristics (technology, typology) are opening up exciting new opportunities for pinning down precisely which environmental or climatic features these cultural components reference, if any. The study by Vignoles et al. makes a good case. At the same time, this approach also acutely raises questions of cultural taxonomy, of how we define our units of analysis and what they might mean [7]. It remains unclear to whether we can define such units on the basis of very different technological traits if the aim is to then use them as taxonomically equivalent in subsequent analyses. There is also a risk that these facies become reified as traditions of sub-cultures – then often further equated with specific people – through an overly normative view of their constituent technological elements. In addition, studies of adaptation in principle need to be conscious of the so-called ‘Galton’s Problem’, where the historical relatedness of the analytical units in question need to be taken into account in seeking salient correlations between cultural and environmental features [8]. In pushing forward eco-cultural niche modelling, the study by Vignoles et al. thus takes us some way forward in understanding the potentially adaptive variability within the Gravettian; future work should consider more strongly the specific historical relatedness amongst the cultural taxa under study and follow more theory-driven definition thereof. Such definition would also allow the post-analysis interpretations of eco-cultural niche modelling to be more explicit. Without doubt, the Gravettian as a whole – including, for instance, phenomena such as the Maisierian [9] – would benefit from additional and extended applications of this method. Similarly, other periods of the Palaeolithic also characterized by such variability (e.g. the Magdalenian and Final Palaeolithic) offer additional cases moving forward.

Bibliography

[1] Vignoles, A. et al. (2020). Investigating relationships between technological variability and ecology in 1 the Middle Gravettian (ca. 32-28 ky cal. BP) in France. PCI Archaeology. 10.31219/osf.io/ud3hj

[2] Dibble, H.L., Holdaway, S.J., Lin, S.C., Braun, D.R., Douglass, M.J., Iovita, R., McPherron, S.P., Olszewski, D.I., Sandgathe, D., 2017. Major Fallacies Surrounding Stone Artifacts and Assemblages. Journal of Archaeological Method and Theory 24, 813–851. 10.1007/s10816-016-9297-8

[3] Svenning, J.-C., Fløjgaard, C., Marske, K.A., Nógues-Bravo, D., Normand, S., 2011. Applications of species distribution modeling to paleobiology. Quaternary Science Reviews 30, 2930–2947. 10.1016/j.quascirev.2011.06.012

[4] Banks, W.E., d’Errico, F., Dibble, H.L., Krishtalka, L., West, D., Olszewski, D.I., Townsend Petersen, A., Anderson, D.G., Gillam, J.C., Montet-White, A., Crucifix, M., Marean, C.W., Sánchez-Goñi, M.F., Wolfarth, B., Vanhaeren, M., 2006. Eco-Cultural Niche Modeling: New Tools for Reconstructing the Geography and Ecology of Past Human Populations. PaleoAnthropology 2006, 68–83.

[5] Banks, W.E., Zilhão, J., d’Errico, F., Kageyama, M., Sima, A., Ronchitelli, A., 2009. Investigating links between ecology and bifacial tool types in Western Europe during the Last Glacial Maximum. Journal of Archaeological Science 36, 2853–2867. 10.1016/j.jas.2009.09.014

[6] Whitford, B.R., 2019. Characterizing the cultural evolutionary process from eco-cultural niche models: niche construction during the Neolithic of the Struma River Valley (c. 6200–4900 BC). Archaeological and Anthropological Sciences 11, 2181–2200. 10.1007/s12520-018-0667-x

[7] Reynolds, N., Riede, F., 2019. House of cards: cultural taxonomy and the study of the European Upper Palaeolithic. Antiquity 93, 1350–1358. 10.15184/aqy.2019.49

[8] Mace, R., Pagel, M.D., 1994. The Comparative Method in Anthropology. Current Anthropology 35, 549–564. 10.1086/204317

[9] Pesesse, D., 2017. Is it still appropriate to talk about the Gravettian? Data from lithic industries in Western Europe. Quartär 64, 107–128. 10.7485/QU64_5