Is Watson for Oncology per Se Unreasonably Dangerous?: Making A Case for How to Prove Products Liability Based on a Flawed Artificial Intelligence Design

By Frank, Xavier | American Journal of Law & Medicine, May 2019 | Go to article overview

Is Watson for Oncology per Se Unreasonably Dangerous?: Making A Case for How to Prove Products Liability Based on a Flawed Artificial Intelligence Design


Frank, Xavier, American Journal of Law & Medicine


I. BACKGROUND

Watson for Oncology (“WO”) is a supercomputer that employs AI to make cancer treatment recommendations in a fraction of the time it normally takes an oncologist to recommend a course of treatment. It appears that WO can revolutionize how doctors treat cancer, but only if it is proven to be safe and effective. The effectiveness of a medical device is usually verified during a clinical trial, but WO was not subject to any clinical trials. In the absence of clinical testing, International Business Machine (“IBM”) Corporation has sought to demonstrate WO's effectiveness to the medical community by heavily relying upon WO's concordance rates. But WO's concordance rate varies, which suggest it performs inconsistently. The question is whether WO's varying concordance rate should form the basis for a products liability suit.

This Note explores how the law should assess products liability claims against artificially intelligent medical devices. Part I discusses the design and training of WO. Part II explores how AI challenges the existing liability regimes, and then discusses and analyzes why three scholars do not believe the existing legal framework can accommodate claims against artificially intelligent machines. This section then proposes that the existing products liability framework is sufficient to permit a litigant to advance a claim against an artificially intelligent medical device. I argue that courts should adopt a rebuttable presumption or per se rule that holds an artificially intelligent medical device is unreasonably dangerous when a manufacturer intentionally designs the product in such a way that it is not uniformly used or applied by medical practitioners. Part III discusses why, as compared with suing the Food and Drug Administration (“FDA”), the hospital or medical institution, or the oncologist, a plaintiff is more likely to recover by bringing a products liability suit. Finally, Part IV demonstrates how to bring a products liability suit against IBM for WO's defective design.

A. Watson for Oncology

Doctors, hospitals, and healthcare providers are beginning to standardize the use of artificially intelligent medical devices in the treatment of patients. Examples of artificially intelligent medical devices include DeepMind by Google,1 Inner Eye by Microsoft,2 and Watson by IBM.3 IBM's breakthrough technology, Watson, was thrust into the spotlight following its defeat of two longstanding Jeopardy! champions.4 Although Watson has many uses, it has established a reputation for itself within the healthcare industry.5

Watson Health is the subdivision of IBM that is responsible for developing and acquiring AI that can process massive amounts of health-related data—from clinical studies to skin images to genome sequencing—and creating tools that aid medical professionals.6 WO was developed by Watson Health and is an AI device that makes cancer treatment recommendations.7

A supercomputer, WO also employs AI to make cancer treatment recommendations through a multi-step process.8 The process begins with a physician or other medical professional feeding patient data into WO.9 After checking the accuracy of the data, the physician will “Ask Watson,” which prompts WO to analyze the patient data in order to make cancer treatment recommendations.10 WO makes six color-coded recommendations.11 Two recommendations are highlighted with green, which means they are the preferred cancer treatments. 12 The next two recommendations are highlighted with yellow, which means they are treatments that should be considered but are not preferred.13 The final two recommendations are highlighted with red, which indicates that they are not recommended courses of treatment.14

B. Behind the Black Box

On the surface, WO's decision-making process is simple. …

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