AI & ML
Growing One's AI Tools: A Paradigm of Practice-Grown Tools
arXiv cs.HC0 views
arXiv:2611.06132v1 Announce Type: new Abstract: Professionals have long used software built for them by others. This article reports the growth of a professional computer-assisted interpreting (CAI) tool built by its own user, a conference interpreter without programming training. Drawing on an eight-week version-controlled record with telemetry from 133 logged sessions and over 20,000 recognized utterances, the article traces how real conference work drove the tool through 62 commits and six versions. The record shows capabilities deployed on the day their need appeared and one strategy change that cut median end-to-end delay by over a third within one afternoon. The article then proposes the paradigm of practice-grown tools, defined by the shift from using to growing, the co-evolution of tool and practice through breakdown and repair, bounded local computation, and an assessment corollary, and it formulates three propositions toward tool-inclusive assessment of practitioners, from tool-making literacy to a compute-standardized format for certifying what they and their tools achieve together.
Source:https://arxiv.org/abs/2611.06132PreviousFluidic Body: Swarm Robots as a Fluid Extension of the HandNextProGram: A Grammar for Progressive Computation Pipelines
Related posts
Curvature-Calibrated Quasi-Bayesian Updating for Moment-Restricted Models
0arXiv stat.TH
Ordinal Credit Assignment: Multi-Step Reinforcement Learning from Comparisons Alone
0arXiv stat.TH
Optimal estimation of generalized causal effects in cluster-randomized trials with multiple outcomes
0arXiv stat.TH
Bayesian Nonparametric Global-local Clustering of High-dimensional Functions
0arXiv stat.TH
Sigmoid-FTRL: Design-Based Adaptive Neyman Allocation for AIPW Estimators
0arXiv stat.TH
Polynomial-Time Differentially Private Synthetic Graph Release with Nearly-Linear Additive Error
0arXiv stat.TH