基于区块链的毕业设计Ethical AI Checklist – 道德AI检查表

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Ethical AI Checklist

A checklist to go through when designing ethical AI models

This checklist intends to democratise the development of ethical AI. The usage of this checklist should always be to the best of ones abilities. This checklist does not impose any value on what is “ethical” or “fair”, that must always be up to the individual. The intention of this checklist is to be short but comprehensive, and will never exceed 10 points.

The List

  1. Have you sat down and thought about which bias your model may exhibit and which effects that may have, and done your best to mitigate unethical effects?
  2. Have you evaluated your training data for (statistical) unethical bias?
  3. Upon discovering bias, have you not compromised ethicality in favor of model performance?
  4. Have you sat down and thought about edge cases and their impact as well as tested them on the model to the best of your ability?
  5. Have you discussed the model and its training data with a peer in another demographic? (e.g. not white middle-aged man)
  6. Have you discussed the model impact and tested the output on your target audience?
  7. After deploying/publishing, are you continuously monitoring performance to identify unethical behavior?

Upon answering yes to all of these questions, do you feel that you have done your best with your current knowledge and abilities to make this model ethical?

If yes, then proceed.


道德人工智能检查表

设计道德人工智能模型时要经过的检查表

该检查表旨在使道德人工智能的发展民主化。这个检查表的使用应该尽自己最大的能力。本检查表并未对“道德”或“公平”强加任何价值,而“道德”或“公平”必须由个人决定。本检查表的目的是简短而全面,并且永远不会超过10分。

列表

  1. 您是否坐下来思考过您的模型可能会表现出哪些偏见和哪些影响,并尽最大努力减轻不道德的影响?
  2. 您是否对培训数据进行了(统计)不道德偏见评估?
  3. 一旦发现偏差,您是否在模型性能方面牺牲了道德?
  4. 您是否坐下来思考过边缘案例及其影响,并尽您所能在模型上进行了测试?
  5. 您是否与其他人口学领域的同行讨论过该模型及其培训数据?(例如,不是白人中年男子)
  6. 您是否讨论了模型的影响并测试了目标受众的输出?
  7. 部署/发布后,您是否持续监控性能以识别不道德行为?你知道吗

在对所有这些问题回答“是”时,您是否认为您已经尽了最大努力,利用您目前的知识和能力,使这一模式符合道德规范?

如果是,则继续。

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