# Dilemma of the Artificial Intelligence Regulatory Landscape

arXiv: https://arxiv.org/abs/2112.09325 · HTML: https://mlsanity.com/paper/2112.09325/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 17 Dec 2021.

## Builds on (most cited first, 1 of 1)

- [Critical Business Decision Making for Technology Startups -- A PerceptIn Case Study](https://mlsanity.com/paper/2009.03011/) (2020)

## Built on by (most cited first, 3 of 3)

- [A Comprehensive Review and Systematic Analysis of Artificial Intelligence Regulation Policies](https://mlsanity.com/paper/2307.12218/) (2023)
- [Autonomous Mobile Clinics: Empowering Affordable Anywhere Anytime Healthcare Access](https://mlsanity.com/paper/2204.04841/) (2022)
- [Compliance Costs of AI Technology Commercialization: A Field Deployment Perspective](https://mlsanity.com/paper/2301.13454/) (2023)

## Abstract (arXiv)

As a startup company in the autonomous driving space, we have undergone four years of painful experiences dealing with a broad spectrum of regulatory requirements. Compared to the software industry norm, which spends 13% of their overall budget on compliances, we were forced to spend 42% of our budget on compliances. Our situation is not alone and, in a way, reflects the dilemma of the artificial intelligence (AI) regulatory landscape. The root cause is the lack of AI expertise in the legislative and executive branches, leading to a lack of standardization for the industry to follow. In this article, we share our first-hand experiences and advocate for the establishment of an FDA-like agency to regulate AI properly.