The ethical considerations including inclusion and biases, data protection, and proper implementation among AI in radiology and potential implications

Abstract

Artificial intelligence (AI) has an enorgmoust potential to improve radiologic diagnostics, efficiency, and consistency, through implementation of evidence-based regulations is crucial to prevent ethical violations pertaining to patient privacy, data management, and diagnostic accuracy. Several key terms were searched on PubMed such as “Artificial Intelligence”, "COVID-19", “Ethics” and “Radiology”. Ultimately, 32 articles that were published from June 2016 - November 2020 were included in our review given their presentation of original information and relevance to clinical AI imaging and ethics. Several themes appeared and allowed for the following recommendations: 1. Protocols explaining how patient data will be utilized should be provided to and implemented by providers. 2. Differences in data regulations among industry partners must be considered for successful implementation of AI in radiology, and protections against entities with a financial interest in patient data must be included. 3. Providers should receive education and training on basic AI algorithm methodology to allow them to explain risks to patients and obtain informed consent. 4. Radiologists and AI programmers should work together to allow for feedback, collaboration, and the development of more clinically impactful and ethical AI applications. We conclude by recommending collaboration between providers and programmers with a focus on existing AI platforms over developing new algorithms, as there is a lack of consensus on the proper applications of and regulations needed for already existing technologies. Future research should examine and aim to addressimplicit biases in AI technologies.