Introduction

Artificial intelligence (AI) has a significant impact on many aspects of modern life, from education, entertainment, commerce to healthcare. Research and experiments show that AI application can provide an efficient improvement in all areas of healthcare from diagnostics to treatment. It is also certain that AI algorithms perform better than human intervention in different tasks such as correlating symptoms and analyzing medical images from electronics medical records [1]. In contrast, the demand for healthcare service has seen exponential increase and many countries are going under a shortage in healthcare practitioners, especially physicians. This paves the importance of considering using AI applications in healthcare to address ongoing shortage in practitioners. Toward this, it is believed that AI-powered tools are important in the next generation healthcare ecosystems. Despite the potential improvement that AI can bring to the healthcare sector, there are also many challenges that need be addressed when developing an AI-application for healthcare. Some of these challenges are Security, Ethics, Legal and Privacy. These challenges are arising due to the usage of patient data in AI-algorithms.

Security:

The healthcare sector is one of the most vulnerable in industries when it comes to cybersecurity. This vulnerability has significantly increase during the Covid-19 pandemic. The intensity of healthcare-related incidents, Artificial intelligence (AI) applications and cybersecurity threats in healthcare are currently facing severe attacks. Cyberattacks have become more advanced using AI, therefore attacking systems that are secured with conventional methods becomes easier. It is thus important that AI applications in healthcare have a high consideration while developing new AI- algorithm for security to constantly manage and secure the increasing volume of healthcare Internet of Things (IoT) sensor nodes as they connect and disconnect from healthcare networks. New AI techniques are expected to enhance cybersecurity by assisting human system managers with automated monitoring, analysis, and responses to adversarial attacks [2]

Ethics and Privacy

AI applications in healthcare present a set of ethics and privacy challenges that need to be identified and mitigated since AI technology has enormous capability to threaten patient preference, safety, and privacy. Current policy and ethical guidelines for AI technology are lagging the progress AI has made in the healthcare field. Using AI in healthcare rises many ethical and privacy dilemmas, however among those have very high concern are, patient privacy and confidentiality that parsing out the boundaries between the physician’s and machine’s role in patient care [3]. Therefore, for trustworthy AI application in healthcare, it is required to accomplish some requirement such as transparency, privacy and data governance, environmental and societal well-being and privacy and data governance.

Legal

To develop robust and efficient AI applications for health care, it is needed to develop policies and legal strategies that carefully consider the multiple dimensions of the integration process, and this require for multidisciplinary efforts to coordinate, validate, and monitor the development and integration of AI tools in the healthcare. Legal strategies and regulations must consider various aspect such as privacy and security risks, liability, employment and labor considerations, data protection and privacy and effectiveness. However, putting such regulation will face many obstacles due to the dilemma of AI in healthcare and the number institutions that will involve in creating such regulations.

Conclusions

The development and implementation of AI in healthcare is highly required to address the ongoing shortage in practitioners and to also improve the healthcare systems by making use of the advantages provided by AI. However, involving data in the implementation of such technology in the healthcare sector rises many challenges such as security, ethics, legal and privacy. These challenges can be addressed by developing AI tools for security, while following various requirement for ethics and privacy, and putting regulations to address the legal aspects.