MITIGATING AI BIAS WITH RESPONSIBLE AI DESIGN

Dr. Agatha Liu

Duane Morris LLP

Now that artificial intelligence (AI) is employed widely with unprecedented consequences, there is quite a scramble to implement mitigating measures. For example, the United Trademark and Patent Office (USPTO) is soliciting public comments on what steps the USPTO should take to mitigate harms and risks from AI-enabled invention. Many of the proposed guardrails are applicable to the deployment of AI technology, to conform original output of the AI technology to desired principles, policies, guidelines, etc. However, it is no less valuable to improve the design of the AI technology, especially when various computational techniques can be readily applied.

One fundamental issue with the AI technology is producing inaccurate output, with random, sporadic errors or, more damagingly, systemic deviations leading to bias. This article presents a systematic review of how computational techniques can be utilized to help mitigate such bias. The fundamental issue is not new, and at least some of the relevant computational techniques have respectable histories and wide-ranging applications. It is a good time to evaluate these computational techniques cohesively in the context of reducing the bias coded into or produced by the AI technology. Such evaluation can shed more light on how technology can always be improved by additional technology, and how creators of the AI technology can be more responsible and be incentivized to be so.