AI's mysterious ‘black box’ problem, explained
2023年3月6日 · This inability for us to see how deep learning systems make their decisions is known as the “black box problem,” and it’s a big deal for a couple of different reasons. First, this quality makes it difficult to fix deep learning systems when they produce unwanted outcomes.
What Is a Black Box Model? Definition, Uses, and Examples - Investopedia
2024年4月2日 · A black box model designed for use in the financial markets is a software program that analyses market data and produces a strategy for buying and selling based upon that analysis.
What is Black Box AI? Definition from TechTarget
Simply put, AI systems whose internal workings, decision-making workflows, and contributing factors are not visible or remain unknown to human users are known as black box AI systems. The lack of transparency makes it hard for humans to understand or explain how the system's underlying model arrives at its conclusions.
AI’s Trust Problem - Harvard Business Review
2024年5月3日 · As AI becomes more powerful, it faces a major trust problem. Consider 12 leading concerns: disinformation, safety and security, the black box problem, ethical concerns, bias, instability,...
Why We Need to See Inside AI’s Black Box - Scientific American
2023年5月26日 · For some people, the term “black box” brings to mind the recording devices in airplanes that are valuable for postmortem analyses if the unthinkable happens. For others it evokes small,...
What Is Black Box AI and How Does It Work? | IBM
2024年10月29日 · Black box AI models arise for one of two reasons: Either their developers make them into black boxes on purpose, or they become black boxes as a by-product of their training. Some AI developers and programmers obscure the inner workings of AI tools before releasing them to the public.
2024年4月2日 · so-called “black box problem” or “black-box effect”, which constitutes an inherent limitation of AI challenging AI’s further evolution and public acceptance and sparking a lively debate in scientific community about the potential tools for counteracting it.
The “Black Box Effect” in Artificial Intelligence - IMMERSIA
2024年9月4日 · But what does the black box effect mean? This term refers to the lack of transparency or interpretability in algorithms, making it difficult or even impossible to understand why an AI system reaches certain conclusions or predictions.
Interpreting Black-Box Models: A Review on Explainable Artificial ...
2023年8月24日 · To reduce false negative and false positive outcomes of these back-box models, finding flaws in them is still difficult and inefficient. In this paper, the development of XAI is reviewed meticulously through careful selection and analysis of …
Transparency and the Black Box Problem: Why We Do Not Trust …
2021年9月1日 · This “black box problem” in AI becomes especially worrisome when coupled with outcomes that are ethically problematic, such as biased algorithms or decision models. Without an adequate understanding of how decisions are reached using DL, the criteria for trustworthiness cannot be satisfied.
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