8 Conclusion: A Warning Against Paradigms
6
Convergence is sometimes described as the third revolution in the making on the life
sciences horizon. Briefly, this has important implications, more relevantly for the
public understanding of science and scientific change. First of all, it becomes amply
clear from the life sciences horizon that the scientific revolutions are rational in so far
as they must build upon the previous revolutions by a process of knowledge
resources dynamics. In the life sciences, the rationality of the third revolution can be
seen as strongly building upon the rationalities of the first and second revolutions
starting from 1953 and 1980s, respectively. Second, the epistemic communities, as
diverse as scientists, methodologists of science and innovators, among others, can
accelerate the processes of knowledge resources dynamics by working together at
the challenging frontiers of development, including the frontiers of problem and
theory-development in the sciences. Third, the sciences themselves can go into a
state of self-repair, a state of self-healing, only if they are not in fetters, confined
within ‘paradigms’ with ‘gate keepers’, and only if they are able to learn from their
past mistakes. As a corollary to this, notice that there are no so-called ‘paradigms’
(Kuhn 1962, 1970) or their ‘gate keepers’ to be found playing a key role either in
science or in scientific revolutions. What is remarkable and most important is that at
no stage of the third revolution of convergence in the life sciences horizon, and in
turn in the physical sciences, is there any indication of ‘Kuhn’s paradigms’ coming
into play, peripherally or centrally. Therefore, at least in the interests of public
understanding of science, we must say a final good bye to the myth of the
‘paradigms-driven science’ that Kuhn created in the name of the sociology of science
(Kuhn 1962, 1970). Fourth, it cannot be denied that there are many among the global
science communities and the STS communities who have been psychologically as
well as sociologically so much overwhelmed by Kuhn’s (1962, 1970) book ‘The
Structure of Scientific Revolutions’ that they are able to pretend to understand what
‘paradigms’ stand for but in truth do not understand anything about ‘paradigms’, nor
about the multiple senses in which one could use this notoriously ambiguous term
(Masterman 1970, Wittgenstein 1953). Perhaps, it is no exaggeration to warn that
‘paradigms’ are best suited for arrogant dictators and totalitarian regimes (Wynn
2015). Fifth, and finally, to avoid a takeover by technological totalitarianism, it is
imperative that the sciences join hands to accelerate knowledge resources dynamics.
It is urgent to create a culture of wisdom and a knowledge environment for
knowledge resources dynamics to bear fruit.
As is clear from the current state of development of the life sciences, the convergence
model is essentially discovery-driven. No surprise, if it is expected to take off vertically.
It is about how one scientific revolution within a scientific discipline successfully builds
upon the previous revolutions within that discipline, creating a potentially larger
knowledge environment for several disciplinary sciences, even without a previous
6
The main arguments are developed in Pandit (1982, 1991, 2010a, 2012a, 2014a, 2015c);
and Pandit and Dosch (2013).
154
G.L. Pandit
6
Convergence is sometimes described as the third revolution in the making on the life
sciences horizon. Briefly, this has important implications, more relevantly for the
public understanding of science and scientific change. First of all, it becomes amply
clear from the life sciences horizon that the scientific revolutions are rational in so far
as they must build upon the previous revolutions by a process of knowledge
resources dynamics. In the life sciences, the rationality of the third revolution can be
seen as strongly building upon the rationalities of the first and second revolutions
starting from 1953 and 1980s, respectively. Second, the epistemic communities, as
diverse as scientists, methodologists of science and innovators, among others, can
accelerate the processes of knowledge resources dynamics by working together at
the challenging frontiers of development, including the frontiers of problem and
theory-development in the sciences. Third, the sciences themselves can go into a
state of self-repair, a state of self-healing, only if they are not in fetters, confined
within ‘paradigms’ with ‘gate keepers’, and only if they are able to learn from their
past mistakes. As a corollary to this, notice that there are no so-called ‘paradigms’
(Kuhn 1962, 1970) or their ‘gate keepers’ to be found playing a key role either in
science or in scientific revolutions. What is remarkable and most important is that at
no stage of the third revolution of convergence in the life sciences horizon, and in
turn in the physical sciences, is there any indication of ‘Kuhn’s paradigms’ coming
into play, peripherally or centrally. Therefore, at least in the interests of public
understanding of science, we must say a final good bye to the myth of the
‘paradigms-driven science’ that Kuhn created in the name of the sociology of science
(Kuhn 1962, 1970). Fourth, it cannot be denied that there are many among the global
science communities and the STS communities who have been psychologically as
well as sociologically so much overwhelmed by Kuhn’s (1962, 1970) book ‘The
Structure of Scientific Revolutions’ that they are able to pretend to understand what
‘paradigms’ stand for but in truth do not understand anything about ‘paradigms’, nor
about the multiple senses in which one could use this notoriously ambiguous term
(Masterman 1970, Wittgenstein 1953). Perhaps, it is no exaggeration to warn that
‘paradigms’ are best suited for arrogant dictators and totalitarian regimes (Wynn
2015). Fifth, and finally, to avoid a takeover by technological totalitarianism, it is
imperative that the sciences join hands to accelerate knowledge resources dynamics.
It is urgent to create a culture of wisdom and a knowledge environment for
knowledge resources dynamics to bear fruit.
As is clear from the current state of development of the life sciences, the convergence
model is essentially discovery-driven. No surprise, if it is expected to take off vertically.
It is about how one scientific revolution within a scientific discipline successfully builds
upon the previous revolutions within that discipline, creating a potentially larger
knowledge environment for several disciplinary sciences, even without a previous
6
The main arguments are developed in Pandit (1982, 1991, 2010a, 2012a, 2014a, 2015c);
and Pandit and Dosch (2013).
154
G.L. Pandit