Explainability is an English word. Below you'll find 5 example sentences showing how it's used in practice.
Explainability in a sentence
Explainability meaning
The state of being explainable.
Using Explainability
- The main meaning on this page is: The state of being explainable.
Context around Explainability
- Average sentence length in these examples: 18.2 words
- Position in the sentence: 3 start, 2 middle, 0 end
- Sentence types: 5 statements, 0 questions, 0 exclamations
Corpus analysis for Explainability
- In this selection, "explainability" usually appears near the start of the sentence. The average example has 18.2 words, and this corpus slice is mostly made up of statements.
- Around the word, determination, gain and provides stand out and add context to how "explainability" is used.
- Recognizable usage signals include credit determination explainability can inform and explainability provides businesses. That gives this page its own corpus information beyond isolated example sentences.
- By corpus frequency, "explainability" sits close to words such as aaas, aacc and aacs, which helps place it inside the broader word index.
Example types with explainability
The same corpus examples are grouped by length and sentence type, making it easier to see the contexts in which the word appears:
While the desire for AI explainability is understandable, its importance is often overstated. (13 words)
For example, in a use case like credit determination, explainability can inform future credit risk models. (16 words)
One way to gain explainability in AI systems is to use machine learning algorithms that are inherently explainable. (18 words)
Key to achieving this is ‘explainability’ (why and how the expected outcome is going to happen) and ‘interpretability’ (how effectively you can predict the outcome). (25 words)
Explainability provides businesses the opportunity to communicate more clearly with their customers too – a win-win in all scenarios. (19 words)
One way to gain explainability in AI systems is to use machine learning algorithms that are inherently explainable. (18 words)
Example sentences (5)
Explainability provides businesses the opportunity to communicate more clearly with their customers too – a win-win in all scenarios.
For example, in a use case like credit determination, explainability can inform future credit risk models.
While the desire for AI explainability is understandable, its importance is often overstated.
Key to achieving this is ‘explainability’ (why and how the expected outcome is going to happen) and ‘interpretability’ (how effectively you can predict the outcome).
One way to gain explainability in AI systems is to use machine learning algorithms that are inherently explainable.