How do concepts matter for language in the human-machine era?

The training school is primarily a networking event. It was interactive and provided an excellent opportunity to meet people across a whole spread of research and industry fields. The international nature of the event also provided an array of participants to learn with and from. I found the eclectic nature of people’s backgrounds particularly inspiring: there were doctoral students to professors, sociolinguists looking at ethics and how technologies are changing research methods, to computer scientists working LLMs and using robots and teaching aids for autistic children. It was also enriching to be in a space with people from all over Europe (and beyond), to be able to share different experiences and the differentiated experience of the same technologies or elements through different linguistic lenses.

The training school fed us with a lot of information about different aspects of language technology and our world today. Of this, information relating to the unequal access to technology and availability of linguistic data has really embedded itself into my mind: forty per cent of the world’s population have no access to/do not use the internet. That is not far from half. When we talk about ‘today’s data-driven world’ we are excluding nearly half the world population. Then, who writes the internet, and in what language? English represents over 80% of the internet. And the content is written primarily by only certain people within these societies. The question of who language technology serves and who it excludes is a huge issue that is rarely the focus of conversation, and one that needs to be central when we are thinking that LLMs and the modelling of technologies will shape our society, our thoughts and what people take to be ‘true’.

But on a theoretical level, the question that interests me most was mentioned right at the beginning by Rui Sousa de Silva and Antonio Pareja Lora was the question of understanding. I have always been of the mindset that computers don’t understand what they are generating, not in the way we understand things. It is why we need the human element within technologies to provide this real-world view, why computers produce inconsistencies that strike us as strange. They work in a different and complementary way to us. But what about humans? I have thought about humans and understanding throughout my life as a translator and interpreter, often marvelling that we understand each other at all. But I had not given it much thought specifically in the context of language technology. Does it matter that computers don’t understand? How can the abilities of computers (lots of data, computing power) be leveraged to support humans where they excel (specialist expertise and a real understanding of texts and the world)?