I’ve been suggesting for a while that generative AI will create new forms of accounting, evaluation and surveillance within organisations. What hadn’t struck me until recently was how intrinsically connected these functions are, based around new capacities to qualitatively summarise (as opposed to quantitatively track) real-time behaviour within organisations. Transactional data will become human readable with potentially huge implications for the digital epistemology which has been building up around us over the last two decades. This is how a prominent start-up offering organisational solutions talks about this promise:
Right now we’re hand-designing information flows and team structure. Instead, let’s use LLMs to share information between teams and help route important work to the right people.
• LLMs can summarize what work everyone does in an organization by parsing over their code, messages, and documents.
• LLMs in conjunction with other AI techniques can also identify common problems in an organization and rank them by severity.
• These models can then group the work of each team member by reviewing their code, messages, and documents, providing a comprehensive summary of their roles.
• We can then route important information to the right people in the organization who have the relevant expertise.
https://blog.mutable.ai/p/the-ai-organization-part-i?utm_source=substack&utm_medium=email
The impulse to summarise based on real activity gets to heart of organisational efficiency, but it also provides a mandate for a vast expansion of real time surveillance. What they describe as “unified AI driven information flow linking all stakeholders” has a mirror-image of total surveillance within organisations, in which all actions become legible in ways which are intensely sinister when filtered through hierarchical relations.
Mark Carrigan 