# A Definition and a Test for Human-Level Artificial Intelligence

arXiv: https://arxiv.org/abs/2011.09410 · HTML: https://mlsanity.com/paper/2011.09410/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [Toward Human-Level Artificial Intelligence](https://mlsanity.com/paper/2108.03793/) (2021)

## Abstract (arXiv)

Despite recent advances of AI research in many application-specific domains, we do not know how to build a human-level artificial intelligence (HLAI). We conjecture that learning from others' experience with the language is the essential characteristic that distinguishes human intelligence from the rest. Humans can update the action-value function with the verbal description as if they experience states, actions, and corresponding rewards sequences firsthand. In this paper, we present a classification of intelligence according to how individual agents learn and propose a definition and a test for HLAI. The main idea is that language acquisition without explicit rewards can be a sufficient test for HLAI.