From machine knowledge and knowledge management to a unified
human-machine theory: proposal for conceptual model
Authors: Teodoro Dantas Sartori Jeanfrank 
Published: February 2023

Academic research in Knowledge and knowledge management tends to focus
on issues related to producing, storing, organizing, sharing, and retrieving
data, information, and knowledge for and from humans, and on how to make use
of machines for those and other related purposes. Therefore, hardware and
software are usually seen more as support and means but, as technology
exponentially evolves, there are already many machine learning algorithms,
artificial intelligence, and other resources where it is hard for a human
mind to fully comprehend the rationale behind its outcomes, results,
predictions, processing, or decisions taken, even though they might be shown
to be precise and of high quality. There are theoretical e technical efforts
to address it, such as the concept of Explainable AI, but it is conceivable
that knowledge from machines may not be, in the present or in the future,
both efficient and adequately translatable to traditional
human-comprehensive knowledge. That knowledge might one day be only usable
by other machines in a yet unknown approach of knowledge sharing between
them, in a specific way designed for them and perhaps, in the future, also
by them: a machine perspective of knowledge and knowledge management. In
addition, machine knowledge may not be available only in the explicit form
but also in a manner somehow analog to human tacit knowledge, as for
instance, a given AI may acquire a rationale that is beyond what its stored
bytes can express. That might be also evidence of a context in which perhaps
it may be only able to be socialized between machines, in a tacit to tacit
“transfer”, not with nor for humans. Furthermore, keeping machine knowledge
secure might be far more complex than mere data storage security and policy,
as a simple copy of those data may be insufficient for representing and
recovering a previously developed machine knowledge, implying that
traditional information management is no longer enough. Much is still needed
to advance on the topic of machine knowledge, as an approach to data,
information, and knowledge from and for machines is needed, in what could be
called machine knowledge management (MKM). But that is not the final step
needed, as from these machine knowledge and knowledge management concepts
emerge the need for a unified theory with human counterparts, that addresses
the complex aspects of coexistence and interactions of both clusters of
knowledge, with implications for Human-Autonomy Teaming (HAT), and how both
can work together in the present and future challenges. Therefore, the aim
of this research is to advance toward the proposal of a theoretical model
for machine knowledge and knowledge management, on how that can be
integrated with the analog human versions in a unified human-machine model,
and what might play the mediator role. Subsidiarily, it also discusses the
need for a standardized and expanded concept of information and knowledge
consistent with that model. Finally, topics are proposed for future research
agenda. To achieve these research goals, the main methodologies adopted were
the literature review and the grounded theory.