Overview of AI concepts-Responsible AI
负责任的人工智能实例。
·
| Principle | Description |
|---|---|
|
Fairness |
AI models are trained using data, which is generally sourced and selected by humans. There's substantial risk that the data selection criteria, or the data itself reflects unconscious bias that may cause a model to produce discriminatory outputs. AI developers need to take care to minimize bias in training data and test AI systems for fairness. |
|
Reliability and safety |
AI is based on probabilistic models, it is not infallible. AI-powered applications need to take this into account and mitigate risks accordingly. |
|
Privacy and security |
Models are trained using data, which may include personal information. AI developers have a responsibility to ensure that the training data is kept secure, and that the trained models themselves can't be used to reveal private personal or organizational details. |
|
Inclusiveness |
The potential of AI to improve lives and drive success should be open to everyone. AI developers should strive to ensure that their solutions don't exclude some users. |
|
Transparency |
AI can sometimes seem like "magic", but it's important to make users aware of how the system works and any potential limitations it may have. |
|
Accountability |
Ultimately, the people and organizations that develop and distribute AI solutions are accountable for their actions. It's important for organizations developing AI models and applications to define and apply a framework of governance to help ensure that they apply responsible AI principles to their work. |
负责任的人工智能实例
以下场景应应用负责任的人工智能实践：
- 人工智能驱动的大学录取系统应经过测试，确保其公平评估所有申请材料，既考虑相关学术标准，又避免基于无关人口统计因素的无端歧视。
- 采用计算机视觉检测物体的机器人解决方案应避免造成意外伤害或损坏。实现该目标的方法之一是：在与实体物体交互前，通过概率值判断物体识别的"置信度"，若置信度低于特定阈值则停止任何操作。
- 机场等安保区域使用的面部识别系统，应在临时通行需求结束后立即删除个人图像数据。同时需设置防护措施，防止操作员或非必要用户访问这些图像。
- 提供语音交互的人工智能代理应同步生成文字字幕，避免听障用户无法使用该系统。
- 采用人工智能贷款审批系统的银行应披露AI使用情况，并说明训练数据特征（不涉及机密信息）。
有“AI”的1024 = 2048，欢迎大家加入2048 AI社区
更多推荐
12
0- 0
已为社区贡献6条内容
所有评论(0)