Unlock the full potential of AI with Building LLMs for Production—our 470+ page guide to mastering LLMs with practical projects and expert insights!


4 Major Concerns in AI and Health Data
Latest   Machine Learning

4 Major Concerns in AI and Health Data

Last Updated on July 25, 2023 by Editorial Team

Author(s): Andrew Austin

Originally published on Towards AI.

The Ethical Challenges of AI with a focus on Healthcare

This member-only story is on us. Upgrade to access all of Medium.

This is part of a 10-part series about the Ethics and Governance of Artificial Intelligence for Health that the World Health Organization created.

Andrew Austin

View list6 storiesImage by Author

When it comes to AI and health data, the quality of data is paramount. Poor-quality, biased, or non-representative data can distort the performance of AI. There may also be no available data for marginalized groups. Data may be difficult to collect due to language barriers, or training data may be based on unpublished and unverified results. This systemic bias is due to… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓