The last time I blindly accepted an invitation to speak was in 2012, when I was invited to an exclusive round table on the future of linguistics at a renowned research institute. As a fresh postdoc I was honoured and bedazzled. When the programme was circulated, I got a friendly email from a colleague asking me how I’d ended up there, and whether I thought the future of linguistics was to be all male.

This is a the second part in a two part series of peer commentary on a recent preprint. The first part is here. I ended that post by noting I wasn’t sure all preprint authors were aware of the public nature of the preprint. I am now assured they are, and have heard from the senior author that they are working on a revised version.

One of the benefits of today’s preprint culture is that it is possible to provide constructive critique of pending work before it is out, thereby enabling a rapid cycle of revision before things are committed to print. I have myself benefited from comments on preprints, and have acknowledged such public pre-publication reviews in several of my papers. The below remarks are shared in that spirit.

Clark & Fischer propose that people see social robots as interactive depictions and that this explains some aspects of people’s behaviour towards them. We agree with C&F’s conclusion that we don’t need a novel ontological category for these social artefacts and that they can be seen as intersecting with a lineage of depictions from Michelangelo’s David to Mattel’s talking barbie doll. We have two constructive contributions to make.

A lot of our recent work revolves around working with conversational data, and one thing that’s struck me is that there are no easy ways to create compelling visualizations of conversation as it unfolds over time. The most common form seems to be pixelated screenshots of transcription software not made for this purpose.

Will synthetic text generators usher in a new age of creative thinking? The remarkable fluency of large language models may make them interesting tools for rapidly exploring semantic and stylistic spaces, yet the deceptive ease with which they generate output also provides countless new ways of appropriating ideas and erasing authorship.

It’s easy to forget amidst a rising tide of synthetic text, but language is not actually about strings of words, and language scientists would do well not to chain themselves to models that presume so. For apt and timely commentary we turn to Bronislaw Malinowski who wrote: In follow-up work, Malinowski has critiqued the unexamined use of decontextualised strings of words as a proxy for Meaning: Malinowski did not write this on his substack,

We don’t generally see PhD dissertations as an exciting genre to read, and that is wholly our loss. As the publishing landscape of academia is fast being homogenised, the thesis is one of the last places where we have a chance to see the unalloyed brilliance of up and coming researchers. Let me show you using three examples of remarkable theses I have come across in the past years.

Sketches, visualizations and other forms of externalizing cognition play a prominent role in the work of just about any scientist. It’s why we love using blackboards, whiteboards, notebooks and scraps of paper. Many folks who had the privilege of working the late Pieter Muysken fondly remember his habit of grabbing any old piece of paper that came to hand, scribbling while talking, then handing it over to you.

Over two years ago I wrote about the unstoppable tide of uninformation that follows the rise of large language models. With ChatGPT and other models bringing large-scale text generation to the masses, I want to register a dystopian prediction.

The construction of gothic cathedrals like Chartres was governed not by blueprints but by “talk, tradition, and templates” — at least that is what Turnbull has compellingly argued. When you come across such a neatly alliterative triad, there are two ways you can go. You can adopt the terms in an unexamined way and rely on their alliterative power.