Mitigating AI Bias with Responsible AI Design

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.  […]

Read the full article by Agatha Liu, Ph.D. 

Taking Heed of AI Contracts

Duane Morris partner Neville M. Bilimoria authored the McKnight’s Long-Term Care article, “AI is everywhere! Addressing the legal risks through contracting.”

Mr. Bilimoria writes:

You can’t look in the news or see social media posts each day without hearing about artificial intelligence in healthcare. In fact, the advancements in AI in healthcare are making leaps and bounds, seemingly with each day that goes by.

But nursing homes and assisted living providers need to understand not just the benefits of how AI can improve quality of resident care and improved operations, but also the legal issues surrounding AI in your facility.

Read the full article on the McKnight’s Long-Term Care website.

Promoting AI Use in Developing Medical Devices

The U.S. Food and Drug Administration (FDA) has issued a draft guidance intended to promote the development of safe and effective medical devices that use a type of artificial intelligence (AI) known as machine learning (ML). The draft guidance further develops FDA’s least burdensome regulatory approach for AI/ML-enabled device software functions (ML-DSFs), which aims to increase the pace of innovation while maintaining safety and effectiveness.

Read the full Alert on the Duane Morris website.

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The opinions expressed on this blog are those of the author and are not to be construed as legal advice.

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