Navigating the AGI Revolution: Retraining and Redefining Human Purpose
William Zen, Kushal Agrawal, Stefano Orsini, Manoj S · Team Zen
Submitted to AI Safety Entrepreneurship Hackathon. Sprint projects are early-stage work by participants, not Apart Research publications.
We propose FutureProof, an application that helps retrain workers who have the potential to lose their jobs to automation in the next half-decade. The app consists of two main components - an assessment tool that estimates the probability that a user’s job is at risk of automation, and a learning platform that provides resources to help retrain the user for a new, more future-proof role.
Reviews
This addresses crucial societal impacts of AI advancement. From my work at MLT helping underrepresented founders, I appreciate the focus on worker transition support.
(1) Research foundation is adequate but could be strengthened with more empirical data.
(2) Addresses important societal safety concerns though threat model could be more specific.
(3) Implementation plan needs more concrete details and validation methods.
This is a cool tool that could be used. But it's unclear how much value-add it would be to those actually being replaced. Retraining is the hard part of the process, and that's not being covered in this tool. Not to mention how to monetise such a solution.
Cite this project
@misc{zen2025navigating,
title = {{Navigating the AGI Revolution: Retraining and Redefining Human Purpose}},
author = {William Zen and Kushal Agrawal and Stefano Orsini and Manoj S},
year = {2025},
month = jan,
note = {Submitted to AI Safety Entrepreneurship Hackathon, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/navigating-the-agi-revolution-retraining-and-redefining-human-purpose}},
url = {https://apartresearch.com/sprints/projects/navigating-the-agi-revolution-retraining-and-redefining-human-purpose}
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