减少偏见,确保公平:解释性 AI 在确保 AI 决策的公平性方面发挥重要作用。通过分析模型的决策过程,XAI 能够识别和纠正模型中的潜在偏差,避免不必要的歧视和误判,确保对所有群体的公平性。 可持续性:通过对模型进行解释,开发者能够更好地识别模型的不足之处,从而进行优化和改进。这种持续的反馈机制不仅提升了模型的性能,
Controllable AIAdvances in artificial intelligence (AI) have had a major impact on natural language processing (NLP), even more so with the emergence of large-scale language models like ChatGPT. This paper aims to provide a critical review of explainable AI (XAI) methodologies for AI chatbots,...
近年来各大AI产品例如H2O.ai,SageMaker Clarify中都内置了模型解释模块,更有像Fiddler, Truera等专注于xAI领域的创业公司出现。可解释机器学习在整个机器学习应用流程中都可以得到广泛的应用: 着眼未来 目前模型解释方面的业务知识表达,因果性,各类算法成熟度,框架便利性,以及算力数据方面的挑战还很大,可以说总体还是在一...
Attention mechanisms – We primarily use them in neural networks, especially in natural language processing (NLP) models, to show which input parts the model focuses on when making predictions 3.2. Explainable AI Methods Based on Scope Explainability methods can also differ in scope, depending on ...
Artificial intelligence (AI) helps us solve real-world problems by processing data. We turn real-world information into numbers for AI models to understand and improve. But a big question remains: How do we make sense of AI results in the real world? This is where Explainable AI comes in....
AI Development and Consulting DATA ANALYTICS NLP & TEXT ANALYTICS COMPUTER VISION PREDICTIVE ANALYTICS MACHINE LEARNING BI IMPLEMENTATION Pinned Loading explainable-ai Public 20 contributions in the last year Contribution Graph Day of Week February Feb March Mar April Apr May May June Jun July Jul...
Automotive industry leaders, such as Tesla, have made substantial investments in artificial intelligence (AI) to expedite the introduction of self-driving vehicles to the market, enhancing their competitive capabilities. The integration of AI in supply chain operations has played a crucial role in enab...
Health is a state of complete physical, mental, and social well-being and not merely the absence of disease and infirmity. Artificial intelligence (AI) has recently been widely used in health and related fields. In the past, AI has shown itself as a complex tool and a solution assisting me...
【用LIME & SHAP解释自然语言处理模型】《Explain NLP models with LIME & SHAP》by Susan Li 机器学习模型可解释性简史—A brief history of machine learning model explainability. 可解释的AI无法实现,复杂性是根本原因,可解释性和性能难以兼得。谈谈AI的可解释性,透明性,可理解性和信任问题。—Explainable AI ...
While AI in general, and deep neural networks specifically, have been posting significant performance improvements in NLP related tasks, their adoption in answering qualitative mental health questions such as classifying loneliness has been hampered by the ‘black-box’ nature of AI. This lack of tr...