For the 2022 edition of the Edinburgh Lectures in Language Evolution, we virtually welcomed four visiting speakers to deliver talks on the first four Thursdays in June. The invited speakers were Ev Fedorenko (MIT), Tom Griffiths (Princeton), Tecumseh Fitch (Vienna), and Asifa Majid (Oxford).
Inspired by the format of 2021’s Birmingham Lectures, each event began with a virtual talk by one of the visiting speakers that showcased their research. The talk was followed by a panel discussion between all four speakers, after which the audience had an opportunity to join the conversation.
The final talk on June 23 had an in-person reception at the University of Edinburgh, presented in partnership with the UKRI CDT in Natural Language Processing.
June 2nd: Ev Fedorenko, MIT, Department of Neuroscience
Click here to watch the talk recording on YouTube (human captioning coming soon!)
Ev Fedorenko is Associate Professor of Neuroscience at MIT. To study the human language system in adults and children, including those with developmental and acquired brain disorders and otherwise atypical brains, her research employs a range of methodologies including fMRI, intracranial recordings and stimulation, EEG, MEG, and computational modelling.
Talk details
The language system in the human mind and brain
The goal of my research program is to understand the representations and computations that enable us to share complex thoughts with one another via language, and their neural implementation. A decade ago, I developed a robust new approach to the study of language in the brain based on identifying language-responsive cortex functionally in individual participants. Using this functional-localization approach, I identified and characterized a set of frontal and temporal brain areas that i) support language comprehension and production (spoken and written); ii) are robustly separable from the lower-level perceptual (e.g., speech processing) and motor (e.g., articulation) brain areas; iii) are spatially and functionally similar across diverse languages (~50 languages from 12 language families); and iv) form a functionally integrated system with substantial redundancy across different components. In this talk, I will highlight a few discoveries from the last decade and argue that the primary goal of language is efficient information transfer rather than enabling complex thought, as has been argued in one prominent philosophical and linguistic tradition (e.g., Wittgenstein, 1921; Berwick & Chomsky, 2016). First, I will examine the relationship between language and other aspects of cognition. I will show that the language brain regions are highly selective for language over diverse non-linguistic processes while also showing a deep and intriguing link with a system that supports social cognition. And second, I will examine different properties of language and argue that language both has a) properties that make it not suitable for complex thought, and b) properties that make it well-suited for communication. Both of these lines of evidence support the communicative function of language, and suggest that the idea that language evolved to allow for more complexity in thought is unlikely.
June 9th: Tom Griffiths, Princeton, Computational Cognitive Science Lab
Click here to watch the talk recording on YouTube (human captioning coming soon!)
Tom Griffiths is Professor of Psychology and Computer Science at Princeton University. In his research, he is interested in developing mathematical models of higher level cognition, and understanding the formal principles that underlie our ability to solve the computational problems we face in everyday life.
Talk details
Overcoming inductive biases in cumulative cultural evolution
The accumulation of knowledge over successive generations is one of the ways that humans overcome their individual limitations — being able to achieve more than would otherwise be possible with a single brain or a single lifetime. However, we still don’t fully understand the factors that make this process of cumulative cultural evolution possible. Individual humans have inductive biases that help them learn from the limited data they experience. Theoretical and empirical studies of the cultural transmission of information have demonstrated that these inductive biases have a significant impact on the information being transmitted. So how can you build a system that accumulates knowledge out of these noisy and biased components? I will summarize recent work demonstrating the challenges that human inductive biases pose for cumulative cultural evolution and describe one situation in which it was possible to overcome those biases. Much of this work was done in collaboration with Bill Thompson (now a faculty member at the University of California, Berkeley).
June 16th: Tecumseh Fitch, Vienna, Department of Cognitive Biology
Click here to watch the talk recording on YouTube (human captioning coming soon!)
Tecumseh Fitch is Professor of Cognitive Biology at the University of Vienna. His interests include bioacoustics and biolinguistics, specifically the evolution of speech, language and music. He performs experiments with species including humans, fish, birds, reptiles and mammals, and works in both the lab and the field.
Talk details
How to study language evolution: Beyond “evolutionarios”
The scientific study of language evolution has grown steadily more hypothesis driven over the last two decades. Comparative research on a broad range of species, neural research, computer modeling, and a better understanding of gene/culture coevolution are all playing increasingly prominent roles. However, I will argue that future progress will depend not just on more and better empirical research, but on theoretical progress at a meta-scientific level as well. First, a more thorough commitment to testing multiple hypotheses, as opposed to accumulating evidence for one favored “pet hypothesis,” is crucial. Only this method of multiple hypotheses can effectively discriminate among the many plausible hypotheses currently on offer. Second, it is crucial for researchers to recognize that human language evolution required the acquisition of multiple derived traits since our divergence from chimpanzees. Too often, researchers argue (or imply, by omission) that there is some single “magic bullet” that, once evolved, gave our species language in a single leap. This belief is inconsistent both with our knowledge of fossil hominins, and more general biological understanding of the evolution of complex traits. I will illustrate these points using comparative data concerning the evolution of speech and of syntax.
June 23rd: Asifa Majid, Oxford, Department of Psychology
Click here to watch the talk recording on YouTube (human captioning coming soon!)
Asifa Majid is Professor of Cognitive Science at the University of Oxford. Her research investigates the relationship between language, culture, and cognition by conducting studies with adults in different cultures and sub-cultures, and by tracing how concepts develop over a child’s lifetime in diverse cultural contexts. Her work combines laboratory and field experiments, as well as in-depth linguistic studies and ethnographically-informed description.
The in-person reception that took place after this final talk was sponsored by our partner, the UKRI CDT in NLP.
Talk details
Language and Cognition or languages and cognitions?
A hallmark of our species is the variation in communication codes we utilise. While cognitive science has historically emphasised theorising about Language with a capital L (language as a general human capacity) and Cognition with a capital C (the universal properties of the human mind), there is increasing recognition that we must account for the diversity of specific languages and their associated cognitions. This year, 2022, marks the beginning of the International Decade of Indigenous Languages according to the United Nations General Assembly. I would like to use this opportunity to reflect on and revisit what lesser-described languages have to offer us in understanding “The Cognitive Underpinnings of Language”, and what this means for future progress in the field.