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What Can the Lithic Record Tell Us About the Evolution of Hominin Cognition?

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Abstract

This paper examines the inferential framework employed by Palaeolithic cognitive archaeologists, using the work of Wynn and Coolidge as a case study. I begin by distinguishing minimal-capacity inferences from cognitive-transition inferences. Minimal-capacity inferences attempt to infer the cognitive prerequisites required for the production of a technology. Cognitive-transition inferences use transitions in technological complexity to infer transitions in cognitive evolution. I argue that cognitive archaeology has typically used cognitive-transition inferences informed by minimal-capacity inferences, and that this reflects a tendency to favour cognitive explanations for transitions in technological complexity. Next I look at two alternative explanations for transitions in technological complexity: the demographic hypothesis and the environmental hypothesis. This presents us with a dilemma: either reject these alternative explanations or reject traditional cognitive-transition inferences. Rejecting the former is unappealing as there is strong evidence that demographic and environmental influences play some causal role in technological transitions. Rejecting the latter is unappealing as it means abandoning the idea that technological transitions tell us anything about transitions in hominin cognitive evolution. I finish by briefly outlining some conceptual tools from the philosophical literature that might help shed some light on the problem.

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Fig. 1

Source Didier Descouens; reproducible under the terms of the Creative Commons Attribution-Share Alike 4.0 International License. URL: https://upload.wikimedia.org/wikipedia/commons/8/87/Biface_Cintegabelle_MHNT_PRE_2009.0.201.1_V2.jpg. Accessed 20 Aug 2019

Fig. 2

Source Ambrose (2001), reproduced here with the permission of the American Association for the Advancement of Science

Fig. 3

Source Dagmar Hollmann; reproducible under the terms of the Creative Commons Attribution-Share Alike 4.0 International License. URL: https://upload.wikimedia.org/wikipedia/commons/4/4c/Loewenmensch1.jpg. Accessed 20 Aug 2019

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Notes

  1. See in particular Lewontin (1998) and Smith and Wood (2017). For a general summary (though Currie is an optimist) see Currie (Currie 2018, pp. 16–18).

  2. Another important background assumption here is that the tool is the product of a standing ability, and not of blind luck. In other words, it is a technology that its maker can reproduce with some reliability. Thanks to Kim Sterelny for helpful discussion here.

  3. Here I divert somewhat from Currie and Killin’s account, which builds a necessity clause into minimal-capacity inferences (Currie and Killin 2019, pp. 266–272). This suggests they are thinking of them as deductive claims. I am here characterising them as inductive, but I don’t think too much hangs on this issue.

  4. The structure of the record as one characterised by stasis and change has been challenged (Kuhn 2019). I agree with the general critique that periods traditionally described as ‘static’—in particular, the Oldowan and the Acheulean—in fact show significant variation and increasing complexity over time. Nonetheless, these periods do display striking standardisation of form.

  5. Another implicit commitment embedded in Coolidge and Wynn’s inference is something like the following: given a large enough time-scale and a diverse range of environments, a capacity will show up in the material record. In other words, adaptation pressures are such that we can reasonably expect to see a signal of a cognitive trait if it exists. Thanks to Kim Sterelny for helpful discussion here.

  6. See also Henrich (2004).

  7. It should be noted that it is very difficult to produce estimations of population sizes in the distant past. As a result, there are very real issues when it come to testing demographic hypotheses.

References

  • Ambrose SH (2001) Paleolithic technology and human evolution. Science 291(5509):1748–1753

    Google Scholar 

  • Baddeley N (2000) The episodic buffer: a new component of working memory? Trends Cogn Sci 4(11):417–423

    Google Scholar 

  • Baddeley A (2011) Working memory: theories, models, and controversies. Annu Rev Psychol 63(1):1–29

    Google Scholar 

  • Baddeley AD, Hitch G (1974) Working memory. In: Bower GH (ed) Psychology of learning and motivation. Academic Press, New York, pp 47–89

    Google Scholar 

  • Carneiro RL (1967) On the relationship between size of population and complexity of social organization. Southwest J Anthropol 23(3):234–243

    Google Scholar 

  • Cole J (2016) Accessing hominin cognition: language and social signaling in the lower to middle Palaeolithic. In: Wynn T, Coolidge FL (eds) Cognitive models in Palaeolithic archaeology. Oxford University Press, Oxford, pp 157–195

    Google Scholar 

  • Collard M, Kemery M, Banks S (2005) Causes of toolkit variation among hunter-gatherers: a test of four competing hypotheses. Can J Archaeol 29(1):1–19

    Google Scholar 

  • Coolidge FL, Wynn T (2018) The rise of homo sapiens: the evolution of modern thinking, 2nd edn. Oxford University Press, Oxford

    Google Scholar 

  • Currie A (2018) Rock, bone, and ruin: an optimist’s guide to the historical sciences. MIT Press, Cambridge

    Google Scholar 

  • Currie A, Killin A (2019) From things to thinking: cognitive archaeology. Mind Lang 34(2):263–279

    Google Scholar 

  • Davidson I (2019) Evolution of cognitive archaeology through evolving cognitive systems: a chapter for Tom Wynn. In: Overmann KA, Coolidge FL (eds) Squeezing minds from stones: cognitive archaeology and the evolution of the human mind. Oxford University Press, Oxford, pp 79–101

    Google Scholar 

  • Davidson I, Noble W (1989) The Archaeology of perception: traces of depiction and language [and comments and reply]. Curr Anthropol 30(2):125–155

    Google Scholar 

  • Davidson I, Noble W (1993) Tools and language in human evolution. In: Gibson K, Ingold T (eds) Tools and language in human evolution. Cambridge University Press, Cambridge, pp 363–388

    Google Scholar 

  • Ericsson KA, Delaney PF (1999) Long-term working memory as an alternative to capacity models of working memory in everyday skilled performance. In: Ericsson KA, Delaney PF (eds) Models of working memory: mechanisms of active maintenance and executive control. Cambridge University Press, New York, pp 257–297

    Google Scholar 

  • Ericsson KA, Kintsch W (1995) Long-term working memory. Psychol Rev 102(2):211–245

    Google Scholar 

  • Ericsson KA, Patel V, Kintsch W (2000) How experts’ adaptations to representative task demands account for the expertise effect in memory recall: comment on Vicente and Wang (1998). Psychol Rev 107(3):578–592

    Google Scholar 

  • Flannery KV, Ucko PJ, Dimbleby GW (1969) The domestication and exploitation of plants and animals. In: Ucko PJ, Dimbleby GW (eds) The domestication and exploitation of plants and animals. Duckworth, London, pp 73–100

    Google Scholar 

  • Henrich J (2004) Demography and cultural evolution: how adaptive cultural processes can produce maladaptive losses: the Tasmanian case. Am Antiq 69(2):197–214

    Google Scholar 

  • Henshilwood CS, Dubreuil B (2011) The Still Bay and Howiesons Poort, 7759 ka: symbolic material culture and the evolution of the mind during the African Middle Stone Age. Curr Anthropol 52(3):361–400

    Google Scholar 

  • Henshilwood CS, d’Errico F, Yates R, Jacobs Z, Tribolo C, Duller GAT, Mercier N, Sealy JC, Valladas H, Watts I, Wintle AG (2002) Emergence of modern human behavior: middle stone age engravings from South Africa. Science 295(5558):1278–1280

    Google Scholar 

  • Hiscock P (2014) Learning in lithic landscapes: a reconsideration of the hominid toolmaking niche. Biol Theory 9(1):27–41

    Google Scholar 

  • Jagher R (2016) Nadaouiyeh Aïn Askar, an example of upper Acheulean variability in the Levant. Quatern Int 411:44–58

    Google Scholar 

  • Jeffares B (2008) Testing times: regularities in the historical sciences. Stud Hist Philos Sci Part C 39(4):469–475

    Google Scholar 

  • Keller CM, Keller JD (1996) Cognition and tool use: the blacksmith at work. Cambridge University Press, Cambridge

    Google Scholar 

  • Killin A (2018) The origins of music: evidence, theory, and prospects. Music Sci 1: 1-23. https://doi.org/10.1177/2059204317751971

    Google Scholar 

  • Klein RG (2000) Archeology and the evolution of human behavior. Evol Anthropol 9(1):17–36

    Google Scholar 

  • Kosse K (1990) Group size and societal complexity: thresholds in the longterm memory. J Anthropol Archaeol 9(3):275–303

    Google Scholar 

  • Kosso P (2001) Knowing the past: philosophical issues of history and archaeology. Humanity Books, New York

    Google Scholar 

  • Kuhn SL (2014) Signaling theory and technologies of communication in the Paleolithic. Biol Theory 9(1):42–50

    Google Scholar 

  • Kuhn SL (2019) The evolution of Paleolithic technologies: a macroscopic perspective. Routledge, London

    Google Scholar 

  • Lewontin RC (1998) The evolution of cognition: questions we will never answer. In: Sternberg S, Scarborough D (eds) Methods, models, and conceptual issues: an invitation to cognitive science. An invitation to cognitive science. The MIT Press, Cambridge, pp 106–132

    Google Scholar 

  • Malafouris L (2016) Material engagement and the embodied mind. In: Wynn T, Coolidge FL (eds) Cognitive models in Palaeolithic archaeology. Oxford University Press, Oxford, pp 69–87

    Google Scholar 

  • Mithen S (1996) The prehistory of the mind: the cognitive origins of art and science. Thames and Hudson, London

    Google Scholar 

  • Overmann KA (2016) Materiality and numerical cognition: a material engagement theory perspective. In: Wynn T, Coolidge FL (eds) Cognitive models in Palaeolithic archaeology. Oxford University Press, Oxford, pp 89–112

    Google Scholar 

  • Planer RJ (2017) Talking about tools: did early pleistocene hominins have a protolanguage? Biol Theory 12(4):211–221

    Google Scholar 

  • Powell A, Shennan S, Thomas MG (2009) Late pleistocene demography and the appearance of modern human behavior. Science 324(5932):1298–1301

    Google Scholar 

  • Premo LS, Kuhn SL (2010) Modeling effects of local extinctions on culture change and diversity in the Paleolithic. PLoS ONE 5(12):e15582

    Google Scholar 

  • Richerson PJ, Boyd R (2013) Rethinking paleoanthropology: a world queerer than we supposed. In: Hatfield G, Pittman H (eds) Evolution of mind, brain, and culture. University of Pennsylvania Press, Philadelphia, pp 263–302

    Google Scholar 

  • Saragusti I, Sharon I, Katzenelson O, Avnir D (1998) Quantitative analysis of the symmetry of artefacts: lower Paleolithic handaxes. J Archaeol Sci 25(8):817–825

    Google Scholar 

  • Smith RJ, Wood B (2017) The principles and practice of human evolution research: are we asking questions that can be answered? CR Palevol 16(5–6):670–679

    Google Scholar 

  • Sterelny K (2007) Social intelligence, human intelligence and niche construction. Philos Trans R Soc Lond B 362(1480):719–730

    Google Scholar 

  • Sterelny K, Hiscock P (2014) Symbols, signals, and the archaeological record. Biol Theory 9(1):1–3

    Google Scholar 

  • Stiner MC (2001) Thirty years on the broad spectrum revolution and Paleolithic demography. Proc Natl Acad Sci 98(13):6993–6996

    Google Scholar 

  • Stiner MC, Munro ND, Surovell TA, Tchernov E, Bar-Yosef O (1999) Paleolithic population growth pulses evidenced by small animal exploitation. Science 283(5399):190–194

    Google Scholar 

  • Stiner M, Munro N, Surovell T (2000) The tortoise and the hare: small-game use, the broad-spectrum revolution, and Paleolithic demography. Curr Anthropol 41(1):39–79

    Google Scholar 

  • Stout D (2011) Stone toolmaking and the evolution of human culture and cognition. Philos Trans 366(1567):1050–1059

    Google Scholar 

  • Stout D, Chaminade T (2007) The evolutionary neuroscience of tool making. Neuropsychologia 45(5):1091–1100

    Google Scholar 

  • Stout D, Chaminade T (2012) Stone tools, language and the brain in human evolution. Philos Trans 367(1585):75–87

    Google Scholar 

  • Stout D, Toth N, Schick K, Chaminade T (2008) Neural correlates of early stone age toolmaking: technology, language and cognition in human evolution. Philos Trans 363(1499):1939–1949

    Google Scholar 

  • Tomlinson G (2015) A million years of music: the emergence of human modernity. MIT Press, Cambridge

    Google Scholar 

  • Torrence R (1983) Time budgeting and hunter-gatherer technology. In: Baily G (ed) Hunter-gatherer economy in prehistory: a European perspective. Cambridge University Press, Cambridge, pp 11–22

    Google Scholar 

  • Torrence R (1989) Retooling: towards a behavioral theory of stone tools. In: Torrence R (ed) Time, energy, and stone tools. New directions in archaeology. Cambridge University Press, Cambridge, pp 57–66

    Google Scholar 

  • Torrence R (2001) Hunter-gatherer technology: macro- and microscale approaches. In: Panter-Brick C, Layton RH, Rowley-Conwy P (eds) Hunter-gatherers: an interdisciplinary perspective. Cambridge University Press, Cambridge, pp 73–98

    Google Scholar 

  • Waters CK (2007) Causes that make a difference. J Philos 104(11):551–579

    Google Scholar 

  • Wynn T (1985) Piaget, Stone Tools and the Evolution of Human Intelligence. World Archaeology 17(1):32–43

    Google Scholar 

  • Wynn T (2002) Archaeology and cognitive evolution. Behav Brain Sci 25(3):389–402 discussion 403–38

    Google Scholar 

  • Wynn T, Coolidge FL (2004) The expert Neandertal mind. J Hum Evol 46(4):467–487

    Google Scholar 

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Acknowledgements

Thanks to Kim Sterelny, Anton Killin, Rachael Brown, Adrian Currie, Julia Haas, Ben Henke, Ron Planer and three annonymous referees for detailed feedback. I would also like to thank audiences at ANU and Pittsburgh HPS for helpful comments.

Funding

This study was funded by an Australian National University Research Scholarship.

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Correspondence to Ross Pain.

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Pain, R. What Can the Lithic Record Tell Us About the Evolution of Hominin Cognition?. Topoi 40, 245–259 (2021). https://doi.org/10.1007/s11245-019-09683-0

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