My friend J. lived in Vienna during the Pandemic. His five-year old daughter used to play with the neighbour’s child. Interaction came naturally for the two of them. They were about the same age. Except, they didn’t have a common language. One spoke only German, the other Dutch and English. That wasn’t a problem though. They had a tablet handy, with Google Translate on it.
By default, we think of AI – and digital technology– in terms of its individual benefits. We ask, how can the machine help me reach my goals, or the goals of my company? Technology takes on a different meaning if we consider it in the context of a group. The question here becomes, how could the machine transform relationships?
I wonder if there is a subset of UX research that focuses on collective experiences, or if companies explicitly design software for communities. What kind of tools would we need to draw user personas and empathy maps, not for individuals but for groups? And how would we pitch this collective value proposition?
I shared a piece on Linkedin not long ago. It’s an article about the Prehistory of the Internet, challenging the default narrative. We’ve all heard of ARPANET, how the Internet was born from a military project to create a distributed communication network – one that would resist a nuclear apocalypse. This colours the way we think about the Net.
Yet there is another strand in the genealogy: bulletin boards, organised on a local basis, accessed through modems, via phone lines. This thread is not about scientists exchanging knowledge in real time, or military generals coordinating reconstruction efforts. It’s about random weirdos discussing whatever online, or using the technology to meet up and discuss arcane areas of pop culture.
Reductionism is tempting. We love to say that something is just something. It’s comforting, and it makes us sounds smart. Yet most of the world is hybrid, messy – sources confused and mingling. Same with the Internet: it’s a global distributed network, resilient and globally connected. It’s also an aggregate of local networks, enabling new ways of organising communities. It’s a whole lot of other things too.
Recognising this hybridity – more generally recognising complexity – is about more than precision for the sake of it. It’s about gaining greater freedom. The more we train ourselves to recognise that the things around us have complex genealogies, the more we can imagine different futures – each in the continuity of a different ancestry.
In 2020, an AI wrote a piece for the Guardian. By scanning the enormous amount of texts available on the web, the machine was able to reproduce verbal patterns in a way that somewhat made sense. This is writing through brute force computation, aggregating cliches.
Yet, it’s not exactly true that an AI wrote a piece for the Guardian – to the same extent that few authors write alone. The final text was edited. Humans used their critical meaning-making ability to select, arrange, and cut through the various drafts compiled by the machine.
We like to think of authorship in romantic terms. The poet is a pure fount of original thought. They’re a channel for the Godly muse to reach other humans. The first draft is a work of genius. Editors only polish and refine. AI-writing seriously challenges this view.
But what if we framed things differently? What if we placed editors at the core of the human effort of meaning-making. The first draft is just an attempt at capturing what floats around. Editing is where original thought emerges. If we were to use this model, then we could also think of AI as a mediumnic tool, at the service of the editor. A tool to capture an elusive ‘spirit of the times’, better than any first draft.
Code serialises problems. It’s formal logic and clear communication. How surprising then that it’s not part of our English curriculum, as an extension of argument analysis. Coding as the art of unambiguous thought, expressed in unambiguous language.