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Artificial Intelligence in Health Health workforces’ algorithmic literacy

in a changed information landscape that humans have interest in societal impacts.” 9,p.4 Engaging in dialogue about
to learn to navigate anew. Within health workforce issues related to ethical uses and data privacy, university
2,3
education, learning to navigate the algorithmic/AI-driven partnerships, and data governance principles is critical to
systems is a must, given the increasing use of AI algorithmic encourage adoption of the AI technologies with care to
solutions in clinical practice. Yet, healthcare professionals serve health workforce education. 12,13
are generally not trained to cope with the proliferation of Global higher education institutions are now facing a
AI technology in their fields. In addition, with the rapid challenge within the health workforce education curricula
4
advancement of AI, research is lagging behind in helping that is complex, multifaceted, and has no ready solutions.
health workforce educators understand what they need AI, unlike other technological advancements, is unique
to advance their own AI algorithmic literacy, and how to in that it is constantly changing and therefore adoption
incorporate AI algorithmic literacy within global health of specific tools for health workforce education has to be
workforce education. Our previous AI in global health analyzed in context for further action on a continuous basis.
workforce education research proposed a community Due to the multifaceted nature of the challenge, potential
of practice (CoP) model for engaging stakeholders from changes in curricula to integrate algorithmic literacy
across disciplines to advance AI algorithmic literacy. necessitate breaking down disciplinary silos, especially
5
In this paper, we focus on the curricular considerations ones that may exist between health workforce education
related to AI algorithmic literacy at the organizational and and the computer science departments. We are therefore
individual levels. proposing an algorithmic/AI literacy framework designed

2. Why the need for an AI/algorithmic for adaptive change within organizations beginning with
an individual’s self-awareness and an examination of their
literacy framework (ALF)? Why does knowledge and skills within their professional context
this need to be done for global health to determine organizational readiness and determine
workforce education? the adaptive actions needed to move the organizational

AI Algorithmic literacy has been defined as, “the capacity priorities forward.
and opportunity to be aware of both the presence and In the following section, we describe the ALF for
impact of algorithmically driven systems and to crystalize global health workforce education. Because the framework
this understanding into a strategic use of these systems to emphasizes readiness, it can be used across different
accomplish said goals.” 6,p.339-343 Algorithmic literacy addresses contexts and therefore meets the needs of the individuals
“basic competencies to know and understand, use and apply, and organizations where they are at.
as well as evaluate and create AI,” 7,p.9 and therefore equips one
with “the functioning, and the consequences of algorithms’ 3. Algorithmic/AI literacy framework for
use.” 8,p.1 Health workforce educators and trainees that are global health workforce education
“without algorithmic awareness may be disadvantaged ALF builds on work that we conducted in relation to the
by missing out on important information that is not adoption of eLearning in resource-constrained settings,
14
prioritized for them.” 9,p.12 Those with more advanced levels that enables organizations to examine where they are and
of algorithmic literacy “have an understanding of the impact where they want to go across five areas: infrastructure and
of algorithm-based systems,” and therefore have a higher support systems, institutional support, Information and
advantage in this era of generative AI boom for shaping a Communications Technology (ICT) technical expertise,
sustainable and equitable generative AI-augmented global student engagement, and faculty engagement. With the
health workforce curriculum. 10 spread of AI, we have expanded the eLearning model
With the advancements in computing, generative AI to include analytics technical expertise (ATE), which
has become possible and shows up in our digital everyday provides insights on how AI works and how it can be used
life in apps such as ChatGPT, Dalle-E, GROK, and by those who are not experts in data science and computer
8
Gemini, which are used to generate new content, including science. Having such expertise within an organization
audio, code, images, text, simulations, and videos. The enables organizational readiness to tackle the complexities
11
algorithms used, however, even if generated by humans, of how we learn and work with AI now and in the future.
“are generally invisible – often referred to as “black box”
constructs, as they are not evident in user interfaces and 3.1. Organizational readiness parameters: Assessing
their code is usually not made public,” 9,p.12 and “tackling the factors that influence an organization’s readiness
challenge presented by AI algorithms, demands not only Figure 1 shows the key components within a funnel (the
technical sophistication, but also an understanding of and organization) for assessing organizational readiness

Volume 2 Issue 2 (2025) 42 doi: 10.36922/aih.4903