Reducing Entry Barriers in the Development and Application of AI
TL;DR — An R Street policy study listing what lowers the cost of building AI: high-skill immigration, open datasets, fair-use training data, and access to chips.
R Street Policy Study No. 153, October 2018. Nine pages.
Watney sorts AI’s inputs into skilled people, data and specialised hardware, and proposes policy for each: immigration reform for AI talent, deducting the cost of training workers, open datasets, a clear fair-use exemption for training data, and stable chip supply chains. It closes on antitrust.
What it is: a think-tank policy brief from 2018. Several of its questions (training-data fair use, chip supply) became the main AI policy fights of the following years.
Where this came from
- r/obscurePDFs post, March 2019 — “Reducing entry barriers in the development and application of AI,by Caleb Watney [9 pages]”. Routing record: The obscurePDFs Subreddit
- Link as posted: https://2o9ub0417chl2lg6m43em6psi2i-wpengine.netdna-ssl.com/wp-content/uploads/2018/10/No.-153.pdf
9 pages. A copy is archived locally against link rot; the header links the original source.