# Human-Centered Artificial Intelligence and Machine Learning

## TL;DR

This paper discusses the importance of designing AI and machine learning systems with a human-centered perspective, emphasizing understanding humans socioculturally and aiding human comprehension, while addressing social responsibility issues.

## Contribution

It introduces a framework dividing human-centered AI into understanding humans socioculturally and helping humans understand AI, highlighting social responsibility considerations.

## Key findings

- Emphasizes the importance of sociocultural understanding in AI design
- Highlights the role of AI in helping humans interpret AI decisions
- Addresses social responsibility issues like fairness and transparency

## Abstract

Humans are increasingly coming into contact with artificial intelligence and machine learning systems. Human-centered artificial intelligence is a perspective on AI and ML that algorithms must be designed with awareness that they are part of a larger system consisting of humans. We lay forth an argument that human-centered artificial intelligence can be broken down into two aspects: (1) AI systems that understand humans from a sociocultural perspective, and (2) AI systems that help humans understand them. We further argue that issues of social responsibility such as fairness, accountability, interpretability, and transparency.