Why should we care about bias in AI?
Artificial intelligence (AI) has the power to produce incredible insights for your company, but its algorithms are only as accurate as the information we feed them. When this information is incomplete, inaccurate, or outdated in any way, the results AI produces can be biased – resulting in unfair or incomplete outcomes with the potential to negatively impact certain groups of people.
How can we mitigate AI biases?
Education and training are critical steps to mitigating bias in AI. In this ideapaper, we outline how a data ethics framework can be the foundation of your company’s culture and practices, enabling you to effectively mitigate and recognize bias in AI.
Download the ideapaper to find:
- What bias in AI is
- How AI becomes biased
- Prominent examples across a platitude of industries
- The negative business repercussions of bias in AI
- The role of data ethics in mitigating AI bias
