This there is a dependency on time to

This claim suggests that for knowledge to be
robust there is a necessity for consensus and disagreement to interplay. The
first question that emerges from this claim is the definition of robust. The
validity or acceptance of certain knowledge (if it is on a global scale) can
determine its robustness. This claim also relies on the reciprocation between
consensus and disagreement that can strengthen knowledge into becoming robust.

However, robust knowledge has proven to be existent even without a dispute.

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This leads to the first knowledge question: what measures the extent to which
knowledge may be robust if knowledge is era dependent? In my essay, I will
suggest that time has a more significant influence on knowledge and the way in
which it is perceived, whilst considering the interplay of consensus and
disagreement as well. Within the Natural Sciences, consensus and disagreement
are what create stimuli for a conclusion to be made. In history, however, there
is a dependency on time to determine the robustness of knowledge, whereas the
consensus and disagreement are factors that define historical events.


the Natural Sciences, robust knowledge has been (and can be) reached through
both consensus and disagreement. With the advancements in technology,
previously accepted knowledge had been disputed upon until robust knowledge was
reached. This implies that to have reached robust knowledge there was a
deliberate modification to the choice of treatment, underscoring the possible presence
of disagreement. Does this suggest that robust knowledge can only be reached if
there is a deliberate abandonment of a conventional approach? An example where
previous knowledge was threatened to reach robust knowledge was with the
implementation of hematopoietic stem cells as a treatment for HIV. The Berlin
Patient, Timothy Ray Brown, was diagnosed with HIV in 1995. He received the
hematopoietic stem cell transplant from Dr. Gero Hütter in 2007-2008.

This transplant was unique because it contained a mutated CCR5 receptor, which
is usually where HIV enters the cell if there is a functional CCR5. Three
months after the transplant, Brown’s HIV levels had plummeted; instead, his T
cells (immune cells) had increased. The Berlin Patient has been off of
antiretroviral therapy to this day and is considered cured. The debate
surrounding this case originates from whether Brown has been cured to sterile
point, or whether the treatment has only provided a functional cure. In 2012 9 billions
of his cells had been analyzed and only 2 bits of HIV genetic material were
identified, suggesting he may relapse. However, this groundbreaking advancement
in HIV research and treatment has allowed for 6 more individuals to be
seemingly cured from the virus. This example has allowed for ID specialists to
conclude that treatment regarding viruses must be personalized. The treatment
was disputed, but the findings from the therapy were applied to a global scale,
which allows their conclusion to be expressed as robust knowledge.

Additionally, the conclusion ID specialists have made was done through
inductive reasoning, where a single patient’s case has been applicable to
providing a cure for HIV. This led me to question whether robust knowledge is
actually only an advancement from previously accepted knowledge and expressed
as “robust” due to its regard as more applicable to a global scale? However,
this knowledge question implies that knowledge can only be determined as “robust”
within a specific time period, as it will inevitably be developed and expanded.


Artificial Intelligence, a branch of computer science that is focused on the
creation of machines capable of processing like humans, has been accredited as
robust knowledge after decades of disputation. Edward Feigenbaum’s
creation of the expert systems marked the first successful form of AI software.

Expert systems capably handle and analyze uncertain information, and provide
decisions based on an input. This branch of AI has been applied to the medical,
commercial, financial, and agricultural field. Within the realm of medicine,
MYCIN has been a backward chaining expert system that identifies pathogens and
recommends antibiotics based on the patient’s body. Additionally, this AI
system is also capable of identifying unknown organic compounds (e.g. Dendral).

The expert system’s high success rate is incomparable to that of the Stanford
medical school members when it was experimented in the 1980s. This new method
of diagnosing was proposed following a transition in AI, from Symbolic AI to
knowledge based AI systems that were implemented and imitated processes of
human cognitions to a greater extent. The expert systems persisted to making
errors that caused widespread disagreement with the use of AI softwares. It was
only until after the AI Winter, a period in the ’90s where it had been
stigmatized following a total collapse, that a new surge of AI software began
to be implemented in the 2010s. Presently, there are AI softwares that have
succeeded and are assimilated into various domains, but they do not retain the
potential they were expected to. AI softwares have become, in some fields, a
necessity to allow for functioning programs, highlighting that it has become
robust knowledge. To claim that AI softwares are robust knowledge suggests that
the robustness had been determined by time: there being numerous periods in the
20th century where AI seemed unobtainable reflects the mobility of knowledge,
suggesting that what is claimed as robust today may change in a decade’s time.

Does this not imply that knowledge cannot ever be claimed as robust due to the
motion of time? However, what determines AI’s robustness is its practical
applicability in our daily lives, such as Siri and Netflix. AI’s inability to
have reached the potential it was expected to do is shifting: intuitive
frameworks are being achieved, accompanied by greater disagreement regarding
the ethics behind the cognitive machines. In turn, this suggests that robust
knowledge will be attained, to a certain extent, with the progresses that will
be made.


in history there have been events that have been able to influence what was
once considered as robust knowledge. For instance, the Soviet-Afghan war 1979
managed to revolutionize the way in which Islam was interpreted. Prior to the
invasion, the Communist People’s Democratic Party of Afghanistan took
power after a coup and initiated radical modernizations to the society. These
progressive measures were extremely unpopular among traditionalists, resulting
in conflict. Soviet troops had entered Afghanistan following a newly
established pro-Soviet regime in an attempt to stabilize the climate. However,
the post-war climate had been completely reformed. Measures were taken to
re-traditionalize the society by reverting to a fundamentalist conception of
Islam. The Soviet interference justified radicalism, determining the reaction
in Afghanistan and favoring the victory of the extremists. However, Saudi
Arabia had been born under an even more radical form of Islam, 50 years prior
to Soviet interference. Yet, due to widespread dissatisfaction with the
political systems in various countries, such as Pakistan and Iran, a more
radical Islam became dominant. What defines various Middle Eastern countries’ political systems (as of today) is
what can be interpreted as robust knowledge, which had been achieved through
the prevalence of disagreement within societies. For example, Khomeini’s
Iranian Revolution (1979) can be defined as a reaction against the oppressive
and arguably non-Muslim Shah regime. The deliberate implementation of Islamism,
an Islamic resurgence, was conceived by Westerners as radicalism/extremism. Through
the revolution, Iran had established the Sharia Law, replacing the previously
laic State. Iran’s revolution triggered other nations such as Algeria, to alter
their judicial systems and implement the Sharia Law. Due to this drastic shift
in a political system, societies were transformed, and the status that has been
upheld following the revolution is considered robust knowledge. Does this
suggest that in history the determination of robust knowledge is heavily
reliant on time? Regardless of disagreement, as seen in Algeria where there was
no revolution, can robust knowledge be accredited if a newly implemented
political system has been reached legitimately and remains constituting over a
long period of time? Moreover, under these assumptions, the suggestion can be
made that the recent Catalonian declaration of independence, following an
illegal and illegitimate vote, cannot be considered as robust knowledge. To be
claimed as robust, knowledge is relatively independent to factors of consensus
and disagreement; rather, it is time that seems to play an essential role.

another example that regards time as the determining factor for something to be
considered as robust knowledge is the economic and political system of
Capitalism. The era of the free market has prevailed globally and it defines an
extremely significant number of nations. Some exceptions include Cuba, North
Korea and China. These powerful nations have all adopted a Communist system of
social organization. However, the attempts to impose Communism in many nations
had failed and following the fall of the Berlin Wall (1989), East Germany’s
Communist ideology eclipsed, and so had the radical attempts to implement it.

Overall, Capitalism’s prevalence and resilience in most of the world’s
economies may justify its robustness.


conclusion, the claim that states that robust knowledge requires both consensus
and disagreement is only valid to a certain extent. As seen from the areas of
knowledge of History and the Natural Sciences, there is a significant
indication that time is a greater determinant for the robustness of certain
knowledge. Nevertheless, time also has its limitations due to there not being
an explicit indication of the amount of time needed for a scientific discovery
or political system to be judged as robust.