Author: Barbara Cosgrove
Publisher: Workday
Publication Year: 2020
Summary: The following blog post gives technology companies 8 ways to incorporate ethical considerations into building their AI algorithms. 1). Define a common agreement about what AI ethics means. This definition needs to be attainable, actionable, and relevant. 2). Build ethical AI into the product development and release framework. Trying to create ethical AI should not be an extra task for developers or make the work more complex. If you build ethics into product development, then it does not have to be an extremely complex task added on. 3). Create cross-functional groups of experts to guide all decisions on the design, development, and deployment of responsible machine learning and AI. Groups such as legal, public policy, public privacy, and ethics and compliance already within a company can examine future uses of Machine Learning in products. 4). Bring customer collaboration into the design, development, and deployment of AI. It is important to gain feedback from the people who will be affected by the use of AI in order to address concerns and needs. 5). Take a “lifecycle” approach to bias in machine learning. A lifestyle approach contains checkpoints to perform bias reviews and assessments. 6). Be transparent. Companies should explain how and why they are using the data. 7). Empower employees to design responsible products. This can happen through required ethics training. 8). Share what you know and learn from others in the industry.