Health systems worldwide are facing unprecedented pressure due to changing demographics, emerging diseases, administrative demands, dwindling workforce, mortality and morbidity, and changing demands and expectations in information technology [1, 2]. Meanwhile, the needs and expectations of patients are increasing and getting ever complicated [1, 3]. The global health system is thus, forced to leverage every opportunity, including artificial intelligence (AI), to provide care that is consistent with patients’ needs and values [4, 5]. As expected, AI has become an obvious and central theme in the global narrative due to its enormous potential of impacting the healthcare system positively. AI in this context should be construed as capability of computers to performing tasks similar to those performed by humans even in healthcare [6, 7]. This includes the ability to reason, discover and extrapolate meanings, or learn from previous experiences to achieve goals artificially [4].
The term AI is vast, and it seems there is no consensus yet on what truly constitutes AI, a term credited to Sir John McCarthy since 1956 [8, 9]. AI is not one single type of technology, but many different types of computerised systems (hardware and software) that require large datasets to realise its full potential [10, 11]. AI tools have emerged as promising technology in healthcare with diverse applications, including diagnostic, therapeutic, preventive, rehabilitative, restorative, and regenerative capacity [10]. In recent times, deep learning algorithms are deployed in Computed Tomography for colon cancer detection, and in mammography for breast cancer diagnosis [1, 12]. AI tools are also applied in chest radiography in pulmonary nodules detection, Magnetic Resonance Imaging for brain tumour segmentation and detection of neurologic disorders, such as Alzheimer’s disease [12]. The successes pertaining to the use of AI in healthcare seems promising, if not great already, but caution is needed.
There is the need for moderation in the celebrations and expectations of the capabilities of AI tools in healthcare, because they also present threats yet to be fully unravelled [6, 13]. So far, there are serious concerns that AI tools could threaten patients’ privacy and autonomy [2, 11]. Moreover, widespread adoption and use of AI tools in healthcare is confounded by factors like lack of standardised patients’ data, inadequate curated datasets, and lack of robust legal regime to clearly define standards of professional practice for AI tools [11]. Additionally, socio-cultural differences, lack of government commitment, proliferation of AI-savvy persons with malicious intents, irregular supply of electric power, and poverty are but a few of the many factors that go against the potential of AI tools in healthcare [14]. For instance, algorithms on which AI tools operate can be weaponised to perpetuate discrimination based on race, age, gender, sexual identity, socio-cultural background, social status, and political identity [15, 16]. Notwithstanding their immense capabilities, AI tools are but a means to an end and not an end in themselves.
Patients have trust in their caregivers and expect that their best interest are served at all times. Resources, both human and non-human, used in the healthcare industry have but only one objective “to address the health needs of the public” [3, 9]. Admittedly, there is no perfect health system because they are prone to medical errors, and patients are fully aware of this. However, the concerns of patients are that, when medical errors occur, they should not be due to deliberate action or inaction, rather due to bad luck or unforeseen circumstances [3]. Therefore, there should be adequate regulations in place to protect patients from negligence, malice, and avoidable mistakes from AI tools. The constant quest for quality care affirms the fundamental ethicomoral and legal obligations on caregivers of nonmaleficence and to act in the best interest of patients [3, 17].
Caregivers are further obligated by the principle of beneficence to deploy their actions in a manner that benefit the patient. The reality however is that, instances of avoidable mistakes abound in healthcare [3, 16]. Particularly, upon the emergence of AI, the debate about the perceived adverse events of AI use on patients has increased [16], given rise to a number of questions. For instance, what constitutes professional negligence of AI tools in healthcare? Who takes responsibility for the commissions and omissions of AI tools in healthcare? What remedies accrue to patients who suffer serious adverse events from care provided by AI tools? What are the implications of using AI tools in healthcare on insurance policies of patients? To what extent is an AI tool developer liable for the actions and inactions of these intelligent machines? What constitutes informed consent when AI tools provide care to patients? In the event of conflicting decisions between AI tools and clinicians, which would hold sway? Obviously, a lot more research including reviews are needed to clearly and confidently respond to these and several other nagging questions. Despite considerable research globally on AI, majority of these research have been done in non-clinical settings [18, 19]. For instance, randomised controlled studies, the gold standard in medicine, are yet to provide further and better evidence on how AI adversely impacts patients [19].
It is also difficult to demonstrate how the deployment of AI tools in healthcare is contributing to Sustainable Development Goals (SGDs) 3.8, 11.7, and 16. For instance, SDG 11.7 provides for universal access to safe, inclusive and accessible public spaces, especially for women and children, older persons and persons with disabilities [20]. Moreover, SDG 3.8 calls for the realisation of universal health coverage, including access to quality essential healthcare services and essential medicines and vaccines for all. Also, SDG 16 advocates for peaceful, inclusive, and just societies for all and also build effective, accountable and inclusive institutions at all levels [20]. Will usage of AI tools in their present situations help achieve these SGDs by 2030 or otherwise? Therefore, this review maps evidence on perceived threats by AI tools in healthcare on patients’ rights and safety, between January 1, 2010 to September 30, 2023.