black box

简明释义

黑匣子

英英释义

例句

1.When it comes to artificial intelligence, many algorithms operate like a black box, making it difficult to interpret their decision-making processes.

在人工智能方面，许多算法像黑匣子一样运作，使得解释它们的决策过程变得困难。

2.The company's financial practices were a black box, leading to concerns about transparency and accountability.

公司的财务做法是一种黑匣子，导致人们对透明度和问责制的担忧。

3.The flight recorder is often referred to as a black box, which is crucial for investigating aviation accidents.

飞行记录仪通常被称为黑匣子，对于调查航空事故至关重要。

4.In software development, a black box testing approach focuses on the outputs generated from various inputs without knowing the internal workings.

在软件开发中，黑匣子测试方法关注于从不同输入生成的输出，而不考虑内部工作原理。

5.Scientists often describe complex ecosystems as a black box because many interactions are not fully understood.

科学家们常常将复杂的生态系统描述为黑匣子，因为许多相互作用尚未完全理解。

作文

In today's technological world, the term black box (黑箱) has become increasingly relevant. Originally used in engineering and aviation, a black box refers to a device or system whose internal workings are not visible or understandable to the user. This concept can be applied to various fields, including computer science, economics, and even psychology. Understanding the implications of the black box phenomenon is crucial as it shapes our interactions with technology and influences decision-making processes.In aviation, for instance, the flight recorder, commonly known as a black box, plays a vital role in understanding the causes of accidents. It records various parameters of flight data and cockpit conversations, providing invaluable insights during investigations. The black box serves as a metaphor for systems that operate without transparency. Users rely on the output without comprehending the underlying mechanisms, which can lead to trust issues and a lack of accountability.Similarly, in the realm of artificial intelligence (AI), algorithms often function as black boxes. These complex models process vast amounts of data to produce results, but the intricacies of their decision-making processes remain obscure. For example, when an AI system recommends a particular product to a consumer, the user may not understand how the algorithm arrived at that suggestion. This lack of transparency raises ethical concerns, especially when these systems impact significant areas like hiring practices, criminal justice, and healthcare.The black box nature of AI can lead to biases in decision-making, as the data used to train these models may reflect societal prejudices. If we do not scrutinize the contents of the black box, we risk perpetuating discrimination and inequality. Therefore, it is essential to advocate for explainable AI, where the decision-making process is made transparent, allowing users to understand how outcomes are derived.Moreover, the black box concept extends beyond technology into economics and finance. Models predicting market behavior often operate as black boxes, where investors rely on outputs without fully grasping the assumptions and data feeding into these models. This reliance can lead to misguided investments and financial crises, as seen in the 2008 financial meltdown, where opaque financial instruments contributed to widespread economic instability.In conclusion, the black box (黑箱) phenomenon is a double-edged sword. While it enables the efficient functioning of complex systems, it also poses risks related to transparency, accountability, and ethics. As technology continues to evolve, it is imperative that we demand clarity regarding the inner workings of such systems. By fostering a culture of transparency and understanding, we can mitigate the potential dangers associated with black boxes and harness their benefits responsibly. Ultimately, as users and consumers of technology, we must strive to illuminate the black boxes in our lives, ensuring that we are not just passive recipients of information but informed participants in a rapidly changing world.

在当今科技世界中，术语黑箱（black box）变得越来越相关。最初用于工程和航空，黑箱指的是一种设备或系统，其内部工作对用户不可见或不可理解。这个概念可以应用于多个领域，包括计算机科学、经济学甚至心理学。理解黑箱现象的含义至关重要，因为它塑造了我们与技术的互动，并影响决策过程。例如，在航空中，飞行记录仪通常被称为黑箱，在理解事故原因方面发挥着至关重要的作用。它记录各种飞行数据和驾驶舱对话，为调查提供了宝贵的见解。黑箱作为一个隐喻，代表那些在没有透明度的情况下运作的系统。用户依赖输出而不理解潜在机制，这可能导致信任问题和缺乏问责制。同样，在人工智能（AI）的领域中，算法往往作为黑箱运作。这些复杂的模型处理大量数据以产生结果，但其决策过程的复杂性仍然模糊不清。例如，当一个AI系统向消费者推荐特定产品时，用户可能无法理解算法是如何得出该建议的。这种缺乏透明度引发了伦理问题，尤其是当这些系统影响到重要领域如招聘、刑事司法和医疗保健时。黑箱的AI性质可能导致决策中的偏见，因为用于训练这些模型的数据可能反映社会偏见。如果我们不审视黑箱的内容，就有可能延续歧视和不平等。因此，倡导可解释的AI至关重要，让决策过程透明化，使用户能够理解结果是如何得出的。此外，黑箱概念超越了技术，扩展到经济和金融领域。预测市场行为的模型往往作为黑箱运作，投资者依赖输出而未能完全理解输入这些模型的假设和数据。这种依赖可能导致误导性的投资和金融危机，正如2008年金融崩溃所示，模糊的金融工具助长了广泛的经济不稳定。总之，黑箱（black box）现象是一把双刃剑。虽然它使复杂系统的高效运作成为可能，但也带来了与透明度、问责制和伦理相关的风险。随着技术的不断发展，我们必须要求对这些系统的内部工作进行清晰的说明。通过培养透明和理解的文化，我们可以减轻与黑箱相关的潜在危险，并负责任地利用其好处。最终，作为技术的用户和消费者，我们必须努力照亮生活中的黑箱，确保我们不仅仅是信息的被动接受者，而是在快速变化的世界中积极参与的知情者。