Artificial Intelligence (AI) System Evaluation Task
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A Artificial Intelligence (AI) System Evaluation Task is a software system evaluation task for assessing AI system properties (such as: AI system accuracy, AI system learning capability, AI system ethical implications).
- Context:
- input: an AI System.
- outout: a AI System Evaluation Result.
- It can be supported by an AI System Evaluation System.
- It can involve methods such as Automated AI System Evaluation, User Study-Based AI System Evaluation, and Expert Review-Based AI System Evaluation.
- It can range from being a Quantitative AI System Evaluation Task to being a Qualitative AI System Evaluation Task.
- It can range from being an Offline AI System Evaluation Task to being a Production AI System Evaluation Task.
- It can range from being a Manual AI System Evaluation Task to an Automated AI System Evaluation Task.
- ...
- Example(s):
- A Chatbot Evaluation Task of a chatbot system, such as for chatbot conversational ability, chatbot response accuracy, and chatbot user satisfaction.
- An Image Recognition System Evaluation Task for image recognition systemss, focusing on aspects like Image Classification Accuracy, Image Processing Speed, and Image Recognition Reliability.
- A Recommendation System Evaluation Task for recommender systems, assessing factors like Recommendation Relevance, Personalization Quality, and User Engagement.
- A Natural Language Processing System Evaluation Task for Natural Language Processing Systems, evaluating areas such as Language Understanding Accuracy, Sentiment Analysis Effectiveness, and Translation Quality.
- A Self-Driving Car System Evaluation Task for Autonomous Vehicle Systems, covering areas like Autonomous Navigation Safety, Obstacle Detection Efficiency, and Adaptive Driving Performance.
- A Healthcare AI System Evaluation Task for AI Healthcare Systems, focusing on Medical Diagnosis Accuracy, Treatment Recommendation Reliability, and Patient Data Analysis Precision.
- A Video Turing Test (VTT).
- ...
- Counter-Example(s):
- A Non-Technical System Evaluation Task, such as evaluating the effectiveness of a human resource management strategy.
- A Hardware System Evaluation Task, which focuses on the physical components and infrastructure rather than software or algorithmic aspects.
- A Financial System Analysis Task, which involves assessing financial performance and compliance but does not involve AI system specifics.
- See: AI System Development Task, Machine Learning Model Evaluation, User-Centered Design, Software Testing.
References
2021
- (Reddy et al., 2021) ⇒ S. Reddy, W. Rogers, V.P. Makinen, E. Coiera, et al. (2021). “Evaluation Framework to Guide Implementation of AI Systems into Healthcare Settings.” In: BMJ Health & Care Informatics. [URL: ncbi.nlm.nih.gov]
- NOTE: It provides an evaluation framework that can be applied at any development or deployment stage of AI systems, with a focus on assessing technical capabilities within healthcare contexts.
2020
- (Jin et al., 2020) ⇒ C. Jin, W. Chen, Y. Cao, Z. Xu, Z. Tan, X. Zhang, L. Deng, et al. (2020). “Development and Evaluation of an AI System for COVID-19.” [URL: pesquisa.bvsalud.org]
- NOTE: It discusses the development and evaluation of an AI system for COVID-19, detailing its comparative performance against radiologists in specific medical imaging applications.
2020
- (McKinney et al., 2020) ⇒ S.M. McKinney, M. Sieniek, V. Godbole, J. Godwin, et al. (2020). “International Evaluation of an AI System for Breast Cancer Screening.” In: Nature. [URL: nature.com]
- NOTE: It focuses on evaluating a new AI system for breast cancer screening, emphasizing the system's development and its effectiveness in cancer detection in mammograms.