What is human evaluation?
The process of assessing the performance of AI systems by human judges or evaluators
human evaluation explained in plain English
Human evaluation is a method used to measure how well an AI system is working by having people review and rate its outputs or decisions
Analogy
Think of human evaluation like a taste test for food - just as people are asked to try a new recipe and give their opinion, human evaluation asks people to review the output of an AI system and provide feedback on its quality
Example
For example, a company developing a chatbot might use human evaluation to test how well the chatbot responds to customer inquiries, with human evaluators rating the chatbot's responses for accuracy and helpfulness
How is human evaluation used?
Human evaluation is used in a variety of applications, including natural language processing, image recognition, and decision-making systems, to ensure that the AI system is producing accurate and reliable results
Common misconceptions about human evaluation
One common misconception is that human evaluation is only used for AI systems that interact directly with people, but it can also be used to evaluate AI systems that work behind the scenes, such as those used for data analysis or prediction
History
Human evaluation has been used in AI research for decades, but its importance has grown in recent years as AI systems have become more prevalent and powerful
People also read
- automatic evaluation
The use of algorithms and statistical models to assess the performance of AI systems
- bag of words
A representation of text as a collection of individual words, ignoring grammar and word order
- BERT
A pre-trained language model developed by Google
- bigram
A sequence of two items from a string of tokens
- BLEU
A metric for evaluating the quality of machine translation
- BLEURT
A metric used to evaluate the quality of text generated by language models
- Character N-gram F-score
A measure of the accuracy of text generation models
- constituency parsing
A process in natural language processing to analyze the syntactic structure of sentences
- crash blossom
A phrase or sentence that is ambiguous or open to multiple interpretations due to its grammatical structure
- decoder
A component of a neural network that generates output from encoded input