2019 · 129 citations · 15 references
Artificial IntelligenceEngineeringAi ModelsAi SafetyEducationIntelligent SystemsAi ReliabilityResponsible AiData ScienceSystems EngineeringTrustworthy Artificial IntelligencePredictive AnalyticsComputer ScienceForecastingTrust In Artificial IntelligenceTrustworthy AiModel TransparencyAutomationIndustrial Artificial IntelligenceModel InterpretabilityTechnologyExplainable Ai
Artificial Intelligence is increasingly playing an integral role in determining our day-to-day experiences. Moreover, with proliferation of AI based solutions in areas such as hiring, lending, criminal justice, healthcare, and education, the resulting personal and professional implications of AI are far-reaching. The dominant role played by AI models in these domains has led to a growing concern regarding potential bias in these models, and a demand for model transparency and interpretability. In addition, model explainability is a prerequisite for building trust and adoption of AI systems in high stakes domains requiring reliability and safety such as healthcare and automated transportation, and critical industrial applications with significant economic implications such as predictive maintenance, exploration of natural resources, and climate change modeling.
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Mukund Sundararajan, Ankur Taly, Qiqi Yan · arXiv (Cornell University) · 2017 · 2.6K citations · Full text
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Explainable artificial intelligence: A survey
Filip Karlo Došilović, Mario Brčić, Nikica Hlupić · 2018 · 1.1K citations