Transparency and the Black Box Problem: Why We Do Not Trust AI

By Warren J. von Eschenbach. Philosophy & Technology, 2021

644 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Informatics, Safety Research

View Paper: https://www.semanticscholar.org/paper/a8a3f8cbb8455f09d6e0c6f582997d8f85ac1ec0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Saleh Afroogh
2. Ali Akbari
3. Mohammadali Kargar
4. Emmie Malone
5. Hananeh Alambeigi

In Health Informatics

1. Saleh Afroogh
2. Ali Akbari
3. Mohammadali Kargar
4. Emmie Malone
5. Hananeh Alambeigi

In Safety Research

1. Saleh Afroogh
2. Ali Akbari
3. Mohammadali Kargar
4. Emmie Malone
5. Hananeh Alambeigi

Citations in the corpus

• Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden (2022, background): “the “black box” problem) might yield resistance to some AI systems [61].”
• Trust in AI: progress, challenges, and future directions (2024, positive): “These black-box networks are complex and opaque in terms of operation (von Eschenbach, 2021), and even sometimes, the developer has limited access to how they operate.”