AST June 2018 Magazine Volume 24 | Page 14

Volume 24 June 2018 Edition In fact, the learning structures are not similar at all – neither in the process, nor the scale. Though AI algorithms may be potent and sophisticated, they still lack the suppleness of human reasoning and deduction. Specifically, an “intelligent” re- sponse to an outlier – an instance of data that is a stranger to the sta- tistics of the training data – simply cannot be expected from an artificial model. (Artificial intelligence is everywhere. Let’s look at radiology. The rapid development of artificial narrow intelligence mostly in understanding images, text, and videos Successful models can generalize to will have a significant impact on radiology.) data instances that were not present in Nevertheless, radiologists are still responsible the training data, but not if such new instances are very different in their statistical nature. and accountable for the limitations of the AI But just because AI may not be true “intelli- gence,” that doesn’t mean it isn’t useful. In countless sectors, AI adds tremendous value even without the versatility of thought exhibited by human beings. To cite just one example from the medical realm: radiologists, charged with spotting disease in CT-scans and MRIs, are these days grappling with overwhelming workloads and lengthening hours, a dangerous combination that leads to more errors in image analysis. systems they utilize, and, likewise, for patient outcomes. Furthermore, while AI can be employed behind the scenes to enhance efficiency and outcomes, it should not interfere with one crucial element of a doctor’s work – the patient experience. As in radiology, AI applications in other fields will pri- marily serve to bolster, not displace, the work of human professionals. Indeed, as more and more fields are aided by artificial intelligence, human oversight will become more and more imperative. It will be humans who monitor and evaluate However, AI algorithms have shown the ability to the key performance indicators of AI algo- enhance the efficiency and accuracy of radiologists’ rithms, decide how AI will be implemented in work when performing such image analysis, enabling real-world applications without jeopardizing them to focus in on images algorithms have flagged lives, and face accountability for how AI is as problematic – ultimately saving lives in the process. deployed. 12