ArticlePDF Available

What is Proof of Concept Research and how does it Generate Epistemic and Ethical Categories for Future Scientific Practice?



"Proof of concept" is a phrase frequently used in descriptions of research sought in program announcements, in experimental studies, and in the marketing of new technologies. It is often coupled with either a short definition or none at all, its meaning assumed to be fully understood. This is problematic. As a phrase with potential implications for research and technology, its assumed meaning requires some analysis to avoid it becoming a descriptive category that refers to all things scientifically exciting. I provide a short analysis of proof of concept research and offer an example of it within synthetic biology. I suggest that not only are there activities that circumscribe new epistemological categories but there are also associated normative ethical categories or principles linked to the research. I examine these and provide an outline for an alternative ethical account to describe these activities that I refer to as "extended agency ethics". This view is used to explain how the type of research described as proof of concept also provides an attendant proof of principle that is the result of decision-making that extends across practitioners, their tools, techniques, and the problem solving activities of other research groups.
1 23
Science and Engineering Ethics
ISSN 1353-3452
Sci Eng Ethics
DOI 10.1007/s11948-015-9654-0
What is Proof of Concept Research and
how does it Generate Epistemic and Ethical
Categories for Future Scientific Practice?
Catherine Elizabeth Kendig
1 23
Your article is protected by copyright and all
rights are held exclusively by Springer Science
+Business Media Dordrecht. This e-offprint
is for personal use only and shall not be self-
archived in electronic repositories. If you wish
to self-archive your article, please use the
accepted manuscript version for posting on
your own website. You may further deposit
the accepted manuscript version in any
repository, provided it is only made publicly
available 12 months after official publication
or later and provided acknowledgement is
given to the original source of publication
and a link is inserted to the published article
on Springer's website. The link must be
accompanied by the following text: "The final
publication is available at”.
What is Proof of Concept Research and how does it
Generate Epistemic and Ethical Categories for Future
Scientific Practice?
Catherine Elizabeth Kendig
Received: 28 September 2014 / Accepted: 14 May 2015
Springer Science+Business Media Dordrecht 2015
Abstract ‘Proof of concept’ is a phrase frequently used in descriptions of re-
search sought in program announcements, in experimental studies, and in the
marketing of new technologies. It is often coupled with either a short definition or
none at all, its meaning assumed to be fully understood. This is problematic. As a
phrase with potential implications for research and technology, its assumed meaning
requires some analysis to avoid it becoming a descriptive category that refers to all
things scientifically exciting. I provide a short analysis of proof of concept research
and offer an example of it within synthetic biology. I suggest that not only are there
activities that circumscribe new epistemological categories but there are also as-
sociated normative ethical categories or principles linked to the research. I examine
these and provide an outline for an alternative ethical account to describe these
activities that I refer to as ‘extended agency ethics’’. This view is used to explain
how the type of research described as proof of concept also provides an attendant
proof of principle that is the result of decision-making that extends across practi-
tioners, their tools, techniques, and the problem solving activities of other research
Keywords Epistemic categories Extended agency Normative ethics
Re-engineering Proof of principle Synthetic biology
& Catherine Elizabeth Kendig
Department of Philosophy and Religion, Missouri Western State University,
4525 Downs Drive, Saint Joseph, MO 64507, USA
Sci Eng Ethics
DOI 10.1007/s11948-015-9654-0
Author's personal copy
Although there has been much philosophical investigation into the disciplinary
foundations of synthetic biology, the diversity of knowledge-making distinctions,
methodologies, tools, and resultant products of these (cf. Morange 2009; O’Malley
et al. 2008; O’Malley 2009, 2010; Keller 2009; Stich 2006), articulation of the
meaning and ethical impacts of some key concepts used within it remain
unanalyzed. I focus on one of these: proof of concept.
‘Proof of concept’ is a phrase that has been used frequently in descriptions of the
type of research sought in program announcements from funding institutions;
project proposals; the dissemination of these investigative and experimental studies;
and in the marketing and patenting of new technologies.
However, the phrase is
often coupled with either a short definition or none at all, its meaning assumed to be
fully understood as research that establishes a prototype.
This is problematic. As a
phrase with potential implications for developing research, protocols, and techno-
logical applications, its assumed but embedded meaning requires some analysis to
avoid it becoming a descriptive category of research that refers to all things new and
scientifically exciting.
I ask and attempt to answer the question: what kind of knowledge does proof of
concept research provide? I provide a short analysis of what is proof of concept
research, offer an example of it, and map out the relevant relationships between
epistemic and ethical categories. I suggest that proof of concept research is
articulated in situ, through the activities of scientific investigation. I examine proof
of concept in one set of scientific practices—in the demarcation of new categories of
knowledge-making within synthetic biology. In the second half of the paper, I
contend that not only are there activities of demarcation that circumscribe new
epistemological categories but there are ethical categories that are circumscribed by
the activities of this research as well. In doing so, proof of concept implies the
research (or scientific experimental practices arising from it) described as such
provides a formative ethical as well as an epistemological foundation for future
experimentation and scientific practice. Following this analysis, I conclude with an
outline for a naturalistic epistemology and contextualist ethics for proof of concept
research. This includes a sketch of a role-based account of normative ethical
valuations that I refer to as ‘‘extended agency’’.
This account is intended to provide
a conception of proof of concept that makes sense of it as an epistemological,
metaphysical, and valuative notion. I claim that the type of research described as
proof of concept is extended across environments, agents, and other research
groups. Its epistemic status is variously situated in the use of tools, techniques, and
Despite its prominent use and description within synthetic biology and biological engineering, the
notion of proof of concept research is not restricted to these and has been used in other fields of research
as well.
One of the more lengthy definitions can be found in the National Science Foundation’s Program
Solicitation: Accelerating Innovation Research-Technology Translation from the Directorate for
Engineering, Industrial Innovation and Partnerships: ‘A proof-of-concept is the realization of a certain
method or idea to ascertain its scientific or technological parameters. A proof-of-concept should be
understood sufficiently so that potential application areas can be identified and a follow-on working
prototype designed.’ (National Science Foundation 2014, 14-569).
In this, I apply Clark’s (1995, 1998, 2010; and Clark and Chalmers 1998) extended mind thesis to
normative valuational claims in ethics.
C. E. Kendig
Author's personal copy
problem-solving endeavours of practitioners. Its natural metaphysics lies in its
category and discipline building activities. And it has normative and valuative
impact insofar as it demarcates boundaries of epistemic classes that affect behavior
and future research.
What Does It Mean to Say That Research Shows Proof of Concept?
In recent use, ‘proof of concept’ describes research in the beginning stages, at the
cutting edge of new applications or technologies, and is a buzzword used to mark
out scientific research as potentially extendable and/or scalable. It is often defined
within a particular context or field of study (e.g. synthetic biology, pharmacology,
biochemistry, business). My aim is to analyze the meaning of this phrase in practice.
According to the Oxford English Dictionary entry, ‘proof of concept’ is a noun
phrase attributable to ‘evidence (usually deriving from an experiment or pilot
project) demonstrating that a design concept, business idea, etc., is feasible’
(Oxford English Dictionary 2014).
But what does it mean to say that research shows proof of concept? Trying to
articulate what is meant by this phrase requires consideration of how we acquire
knowledge more generally and how we know it as knowledge. What is the concept
that underlies the research—and why is it important? Very generally, proof of
concept research presents a discovery about our knowledge of the world and the
structure of existence. The concept in ‘proof of concept’ appears to refer to any
idea that may apply to a class of phenomena. The proof seems to be a possibility
proof that is shown to obtain in experimental practice. It proves that the causal
connection hypothesized, structure proposed, function suggested, or methodological
approach taken in the research obtains in at least one actual case—in the test case.
The notion of proof of concept research is framed in terms of a particular kind of
research that aims to answer a question whose answer has wide applicability in areas
beyond that tested. In so doing, the research provides justification in practice of the
potential transportability of that research (e.g. the methodology used, process
described, pattern instantiated, prototypical application, intervention strategy
performed, model or diagrammatic represented). The research may represent a
suggested framework or organization of a particular biological structure, chemical
pathway, or architectural design. For instance, it may tell us something about how
biological systems work, how they function, by what mechanism, or what kinds of
things or entities could be produced given certain start up conditions or inputs.
Scientific Practice, Belief, and Categories of Knowledge-making
in Synthetic Biology
The recent focus on scientific practice within philosophy of science has turned
attention to the experimental activities of science rather than solely on scientific
theorizing (insofar as these are at all separable) (Hacking 1982). This shift, referred to
as the ‘practice turn’’, has provided answers, (or at least more informed lines of
What is Proof of Concept Research and how does it Generate
Author's personal copy
questioning), to some long-discussed epistemological problems within philosophy
(Chang 2004, 2007, 2009, 2011; Soler 2012; Soler et al. 2014, see also the Society for
Philosophy of Science in Practice 2014, and Kendig forthcoming). Philosophy of
science in practice challenges previous theory-first or theory-privileged approaches
that assume scientific practice is always causally subsequent, epistemologically
derivative, or fully prefigured by scientific theory. Positioned along these lines of
investigation, this paper takes practice itself to be the source of knowledge and in some
cases causally prior to, or the epistemological driver or source of, new advances.
This practice shift provides more than just a new frame within which to
understand the goings on of science. Looking at practice and the activities of which
it is composed yields answers to what makes justified beliefs justified. It suggests
that assessing whether a subject’s beliefs are justified requires looking at the
processes by which he or she forms beliefs. For proof of concept research, a subject
might use her engineering activities to judge whether her beliefs are justified or not.
Understood within this frame of practice, justification is not determined solely by
the subject’s self-reflective representational stance—the belief x is justified insofar
as it is based on intuitional experience by y (the subject) that x is true. Instead, in the
frame of practice, justified beliefs are formed through active intervening and
modification of devices and pathways, in the modelling and experimental
investigation, and in the engineering activities of researchers. Put another way,
the practices of scientists shape the categories of knowledge and change what makes
justified beliefs justified.
For example, three epistemological categories have been shaped by diverse
practices in synthetic biology (cf. Morange 2009; O’Malley et al. 2008; O’Malley
2009; Keller 2009). These categories demarcate diverse knowledge-making
distinctions that lead to different questions being asked, different methods used,
different knowledge acquired through these, and different products or outcomes.
The first of these categories is whole genome engineering. Craig Venter’s Synthetic
Genomics successful synthesis of an entire bacterial genome, Mycoplasma
mycoides JCVI-syn1.0, is the most well publicized example of this (Gibson et al.
2010; Hylton 2012). The second is the engineered construction of functional parts,
processes, pathways, devices, and systems (Brent 2004; Endy 2005; Haynes et al.
2008). The current attempts to modify metabolic pathways in bacteria, yeast, and
algae to generate biofuels are examples of this category (Kendig 2014a). The third
epistemological category is that of synthetic experimental evolution or protocell
creation (Erwin and Davidson 2009; Morange 2009). Synthetic biology research of
this type seeks to understand the process of evolution, biological organization, and
the nature of modularity.
To illuminate the role of proof of concept research in synthetic biology, I focus
on the second of the three epistemological categories outlined in the above: the
knowledge-making practices involved in the re-engineering of small devices,
pathways, and systems. Proof of concept research pursued within this category of
synthetic biology has produced experimental research that generates highly
transferrable knowledge, engineering principles, and know-how that has been used
in the conception and development of a wide range of products in a variety of
industries. It has been successful in the construction of microbial products which
C. E. Kendig
Author's personal copy
promise to offer cheaper pharmaceuticals such as the antimalarial synthetic drug
artemisinin, engineering microbes capable of cleaning up oil spills, and the
manufacture of biosensors that can detect the presence of toxic arsenic contamina-
tion in drinking water (Amyris Biotechnologies 2013; Kendig 2014a).
This kind of synthetic biology research concentrates on the design, manufacture,
and modification of new biomolecular parts and metabolic pathways using
engineering techniques and computational models. By employing knowledge of
operational pathways such as circuits, oscillators, and digital logic gates, it uses
these to understand, model, rewire, reprogram, and re-engineer biological networks
and modules. Standard biological parts with known functions are catalogued in a
number of registries (e.g. Massachusetts Institute of Technology Registry of
Standard Biological Parts). Biological parts can then be selected from the catalogue
and assembled in a variety of combinations to construct a system or pathway in a
chassis microbe such as E. coli.
Proof of Concept: Cyanobacteria Re-engineered for Potential Biofuel
The search for a chassis organism can itself amount to proof of concept research.
For example, multiple organisms have been utilized and tested in the pursuit of
finding a suitable microbe for research into the production of synthetic biofuels.
Cyanobacteria appear to be a promising candidates. Cyanobacteria, like Syne-
chocystic sp. PCC 6803, can provide a highly efficient organic system for producing
biofuels as they can convert solar energy, water, and carbon dioxide into biofuel
molecules (Wang et al. 2013).
Cyanobacteria are also thought to be particularly good candidates because they
possess naturally occurring biosynthetic pathways that produce alkanes (key
components of gasoline, diesel, and jet fuel). At present, research into the use of
cyanobacteria for synthetic biofuel production is still in the very early stages and
well behind that of algae research. However, research focused on reconfiguring
these to create an organism that produces alkanes/alkene at a rate that is double that
of the wild type has been shown to be possible. Synechocystis mutants have been
constructed that overexpress alkane biosynthetic genes. This research demonstrates
proof of concept for the potential use of cyanobacteria for biofuel production. If
their photosynthetic pathways were re-engineered, cyanobacteria may be able to
produce alkanes/alkenes at a highly efficient rate (Wang et al. 2013).
How might we best understand the range of experimental research to which this
cyanobacteria-based biofuel research applies as a proof of concept? The general
knowledge-making category that this research is a kind of is that of DNA-based
devices and systems. This epistemological category of synthetic biology research is
circumscribed by its own embedded practice metaphysics—one whose premise is
biological modularity. The premise of biological modularity is an ontological claim
that is borne out in the practice of this kind of research. We understand that the
biological world is modular because we can build a dry lab mathematical model and
then physically manipulate different parts of organisms in the wet lab in ways that
What is Proof of Concept Research and how does it Generate
Author's personal copy
would only work if there were discrete parts that were functionally interchangeable.
The actual interchangeability of functional parts is shown to be possible in practice
and exemplified through the use of different assembly methods (e.g. BioBrick
Assembly and Golden Gate assembly) and by the proliferation of devices built from
these (e.g. the bacterial biosensors, oscillators, and switches) used in industry as
well as the DNA-based devices built by student research teams in iGEM
competitions since 2003 (Knight 2003; Genome Consortium for Active Teaching
(GCAT) Synbio wiki 2013; Eckdahl et al. 2015).
To say that research in this category shows proof of concept means that the
causal hypotheses are possible. The proof is an experiment or set of experiments
that are intended to represent a test case for the hypothesized theoretical framework
(e.g. given input p, q is produced). If the test or exemplar experiment shows that p
produces q, it is dubbed proof that p can produce q. In doing so the experiment
affirms the hypothetical universal statement, ‘if p, then q’’, by showing that in at
least one case (A) given p, q is produced. The proof is at bottom a proof of
possibility by means of one actual case. Put another way, the proof of the
hypothetical model is in the putting into practice.
The claim that the research shows proof—that the metabolic pathway of
Synechocystis mutants can be engineered to produce biofuel—applies to the
category of all cyanobacteria with engineerable modules (or even all microbes)
whose metabolic pathways are similarly re-engineerable to overexpress alkane. The
range of the proof, (and the concept’s potential application), might best be
considered as all members of a kind functionally circumscribed by the category of
research being pursued—in this case organisms with engineerable modules suitable
to be manipulated by practitioners to produce biofuel.
Generally construed, the underlying assumption in the attribution of a claim that
any piece of experimental research shows proof of concept is: if it works here, it will
also works in all cases like this. In this way, proof of concept research is research
that is projectable—it suggests that if this obtains in the test cases then it will obtain
in other like cases. Simply stated, proof of concept research makes a claim that
extends over a category of like cases where like cases are those that exemplify the
same causal mechanisms, structure, distribution, process, degree of variability,
function, or other feature that is exemplified in the test cases.
Ethical Categorization: Lumpers and Splitters
I now move from discussing the meaning of proof of concept research and the
scalable and extendable epistemic categories that it circumscribes to investigating
how there might be new ethical categories that are also introduced with proof of
concept research. Ethical discussion surrounding synthetic biology has typically
suggested that the ethical issues that synthetic biology addresses are the same as
those in other emerging technologies—they are fundamentally contiguous with
those that have been and continue to be discussed (Preston 2008). In many of these,
the epistemological distinctions outlined above (cf. Morange 2009; O’Malley et al.
2008; O’Malley 2009, 2010; Keller 2009) are ignored altogether by what could be
C. E. Kendig
Author's personal copy
referred to by detractors of the view as ethical lumping. For instance, Christopher
Preston (2008) treats synthetic biology as a homogeneous field, disregarding the
distinctive modes of investigation of whole-genome engineering and small-device
construction when discussing ethical matters. Erik Parens, Josephine Johnston, and
Jacob Moses (2008, 2009) go further, proffering a general lumped view of ethics:
genetic engineering, nanotechnology, information technology and synthetic
biology are so intimately interconnected that it might not make sense to spend
much time making neat distinctions among them—at least for the sake of
thinking about the ethical questions (Parens et al. 2009: 11)
This lumped view of ethics, intended to be applicable to all emerging technologies,
is justified by the apparent similarity of issues between synthetic biology and other
emerging technologies. The authors suggest that a ‘further balkanization of
bioethics’’, or what I call ‘ethical splitting’’, is unneeded and should be avoided
(Parens, Johnston, and Moses 2008). This resistance to ethical splitting is expressed
throughout their work:
Several putatively distinct areas of emerging science and technology are
converging, making it ever less useful to try to draw clear borders among
them. As emerging technologies converge, it becomes clearer that the ethical
issues raised by these technologies are at core similar and familiar. It would be
a waste of resources to take up the ethical questions in parallel; i.e., it is not
profitable to invent a ‘new kind’ of ethics for each new technology. Instead,
we need to get better at productively engaging the familiar ethical questions
that cut across those emerging—and converging—technologies (Parens,
Johnston, and Moses 2009: 4).
My view can be seen as being in opposition to these. I suggest that emerging
technologies each present fundamentally new sets of ethical issues. Motivation for
this kind of context dependent ethics is grounded on a sentiment that ethical
categories track epistemological ones. This takes the earlier discussion of
philosophy of science in practice approach seriously. As discussion of the preceding
example in synthetic biology aimed to show, the experimentation performed in
proof of concept research leads to new epistemological categories that introduce
new questions, methods of investigation, and tools. I now suggest that this research
may also introduce new context dependent ethical issues that are endemic to each of
these categories.
Assuming continuity across new scientific fields, modes of investigation,
knowledge-making practices, and technologies following the ethical lumping
approach seems to ignore ethically relevant epistemological distinctions that are
non-contiguous with those of other fields of study. This general view is appropriate
if we consider our knowledge of ethics to be complete. The lumped view’s strength
is that it allows us to apply solutions from one set of ethical problems to solve
analogous ones in another. It provides a shortcut from problem to solution that
circumvents the need for exhaustive research in a new area or extensive ethical
discussion within it. We needn’t study the engineering practices necessary for small
DNA-based devices in synthetic biology to discover the dilemmas arising from it.
What is Proof of Concept Research and how does it Generate
Author's personal copy
We know what they are because they are just like those we’ve already resolved in
nanotechnology and genetic engineering. This transferability of ethical solutions is
desirable but may not be suitable for all problems arising within a particular field of
Ethical splitting may be preferable when new context specific problems need to
be addressed within the field. The suggestion muted here is that the circumscription
of new epistemic categories generates new ethical categories that may generate
novel ethical dilemmas. This role of category generation as framing the space of
knowledge has been widely discussed in terms of discipline-building. Categories of
knowledge demarcate the kinds of things that are the subject of study for that
discipline, e.g. the periodic table of elements, plate tectonics, and the Diagnostic and
Statistical Manual of Mental Disorders (DSM) (cf. Dupre
2006). Proof of concept
research, insofar as it has generated diverse knowledge-making categories has
created new subdisciplines of synthetic biology. Knowledge-making categories do
not just demarcate epistemic categories but can be thought of as having ethical
riders that are used to decide how we act towards something. Knowledge-making
can generate knowledge of what something is, how it works, as well as knowledge
of how to act. If our moral behaviour is informed by what kinds of things we are
interacting with, it may be our different knowledge-making approaches that may be
specifically relevant in making ethical valuations and moral distinctions.
What are Ethical Categories and Why Should We Care?
Proof of concept research has potential ethical as well as legal, social, and
environmental implications. Some of these can be witnessed in the attempts to
understand the nature of synthetic biology and recent discussions concerning how
we should treat the products of it (e.g. Association for molecular pathology V.
Myriad genetics, Inc, et al. 2013). The recent Supreme Court decision focused on
whether ‘products of nature’ be treated the same as ‘human-made’ inventions.
What was at issue was what kinds of these are patentable.
If products of nature are
of a different kind and belong to a different category than those products which are
made by humans then the reasons justifying the patentability of one do not
necessarily extend to the patentability of the other.
The questions I posed in the previous sections with regard to ethical splitting and
lumping and the generation of new ethical and epistemological categories are
prerequisite to resolving these and other ethical dilemmas. They provide knowledge
In 2014, the U.S. Patent and Trademark Office provided the Guidance For Determining Subject Matter
Eligibility Of Claims Reciting Or Involving Laws of Nature, Natural Phenomena and Natural Products
(Hirshfeld 2014). In this, a balancing test was suggested to decide whether a claim is ‘significantly
different’ from that which is made to be a judicial exception to patentability. That is, whether that which
is to be patented has been changed sufficiently to make it different from the naturally occurring
phenomena or product. But, of course, the decidability of ‘significantly different’’ is decidable only with
regard to knowledge of what it is different-from, or different-in-what-way to. Like the 2013 decision, this
assumes products of nature and products of humans are ontological distinct and arbitrable.
C. E. Kendig
Author's personal copy
of the ethical categories of biologically engineered products, how these ethical
categorizations come to be, and how should they be used.
In addition to the ethical, legal, and social impacts, public understanding of new
research (within synthetic biology in particular) is often mired with perceived
threats of what is unknown and uncontrollable. Recent articles, reports and
editorials express concern in terms of what is unnatural, and references to science
fiction such as Frankenstein, The Island of Dr. Moreau, GATTACA, untoward
environmental effects, super-species, eugenics, bioterrorism, and a general uncom-
fortability about scientists playing God or overstepping some ground or engineers
subverting evolution are commonplace. So too are general worries about
uncertainty, responsibility, and regulation, for instance:
The concern that humans might be overreaching when we create organisms
that never before existed can be a safety concern, but it also returns us to
disagreements about what is our proper role in the natural world (a debate
largely about non-physical harms or harms to well-being) (Parens et al.
Initially research within synthetic biology (as well as other kinds of bioengineering)
often enjoys favourable reports and reception by the public. This initial favourable
reception gives way to an uneasiness and elicits a kind of creepiness for some early
opponents (Colvin 2004; Marchant et al. 2010). Growing concern that something
(whatever it is) is not how it usually is, where it usually is, or doing what it usually
does. This unease is typically expressed in terms of the stuff’s unnaturalness.
The initial interest in bioengineering and then the feeling of general creepiness
has been described quite aptly as the ‘‘wow-to-yuck factor’’ (Colvin 2004; Marchant
et al. 2010). These intuitive aversions may come from the idea that these research
products are unnatural and what is unnatural is a threat to what is natural. That it is
unnatural is usually considered the ultimate justification for its immorality. The
creation and/or redesign of organic materials into synthetic organisms, components
and systems are considered intermediate entities. Barnes and Dupre
(2008) suggest
that it is their intermediate nature that leads to the ‘yuck’ response:
‘yuk’ is the routine, immediate, unrationalized response to dirt, but as
anthropologists stress, dirt is not a particular sort of matter, it is matter out of
place, matter that pollutes, matter that purely by virtue of where it is
encountered signifies disorder. The worm in the soup is yuk, not the worm in
the garden, and for some of us the same is true of the mud on the carpet; body
parts that would elicit no attention at their normal points of attachment may
induce repulsion and anxiety if encountered elsewhere; even health-giving
It should be noted that this concern is premised on a misunderstanding of the nature of being in two
ways. Novelty is endemic in both reproduction and development. That an organism never existed cannot
on its own be a source for concern as each new organism that comes into being (through either sexual or
asexual reproduction) never existed before and so is in some sense the first of its kind. Further, organisms
constantly change their cellular, epigenetic, and physiological makeup throughout their lifetime (cf.
Kendig 2014b).
What is Proof of Concept Research and how does it Generate
Author's personal copy
implantations of blood or bodily organs may engender analogous disquiet,
particularly if species transfer is involved (Barnes and Dupre
2008, 208).
Re-engineered biological parts for chassis microbes that produce new products, such
as the earlier case of a DNA device and pathway re-engineering, generate mixture
organisms insofar as they can include BioBricks derived from a number of different
organisms. Organisms which are redesigned are between various species. They
don’t neatly fit into our existing taxonomy of species. And so are threats to
biological order. The yuck factor may be considered an unpleasant aesthetic
response that encourages avoidance of species that are synthetically constructed
transgenic mosaics, hybrids, or chimeras.
These organisms may frustrate our moral
intuitions due to the potential liminality of their classification as wholes due to the
presence of parts of various origins belonging to different biological categories.
Ultimately, small DNA-based devices and systems synthetic biology is perceived as
being disruptive to natural order because the products of it go against a sense of
internal order of an organism belonging to a single categorization of species
classification. Synthetic organisms and parts are modifications that would be
considered to subvert their natural categorization insofar as they are considered
anomalous human made changes.
Knowledge of how we behave towards that
individual or product is frustrated because it crosses multiple epistemic (and moral)
Our responses to disorder and anomaly are strongly socially structuredthey
are elicited by threats to our dominant systems of classification and the
generally accepted ways of applying them. Structured in this way they are
protective of the existing institutional order (Barnes and Dupre
2008, 212).
These qualms about the classification of the products of human invention or
alteration are qualms that have ethical impacts. This leads us to questions that rely
on knowing what kind of thing something is and to what category they belong: how
do I know what something is? and how do I know how to act towards this thing,
individual, being, or product? Knowledge of what it is provides information to us
about how we are to behave towards it or in our relationship with it. Is it a moral
subject?, a moral object?, or something worthy of our moral consideration?
Arguably, these kinds of questions are only answerable once we know what kind of
thing we are talking about. Put another way, once we know what it is, we start
thinking about how we should act towards it. Insofar as ethics is about how we
should behave towards others or ourselves, ethical engagement is always at least a
two-place relationship (x,y). This holds even if we are treating ourselves (or a part
of ourselves) as that entity with which our ethical consideration, or behaviour
It should be recognized that this aesthetic response is not one that is universally shared. There is a wide
variability of responses to these entities that goes largely unanalyzed in the discussion of the ‘yuck’
factor. The diversity of responses can be the result of one’s training, scientific discipline, or culture. The
upshot? Those moral intuitions perceived to follow from the aesthetic response of liminality-avoidance
are also not universally shared.
Of course the subverting of natural categories has had a long history in selective breeding in
agriculture, horticulture, and among pet breeders as well.
C. E. Kendig
Author's personal copy
towards, is in question. Knowledge of what x is enables us to then figure out how we
should behave towards x. If we know how we behave towards other things in the
same category as x, then we know how to behave towards x.
Epistemic Categories and Categories of Valuation
Epistemological categorization of the kinds of knowledge in synthetic biology
initially appears to be orthogonal to the normative or valuational claims used to
inform ethical behaviour or support moral considerations. But I suggest that the
epistemic notion of proof of concept research that is used to demarcate categories of
non-normative knowledge has a normative ethical analogue—a proof of principle
that supervenes upon it. Both articulate proofs that sanction different forms of
justified belief. But whereas the first delimits a range of scientific knowledge, the
second refers to the valuative and ethical implications arising from these. Proofs of
concept and proofs of principle demarcate different forms of knowledge, but they
share commonalities of origin and extension. Both are proofs formed through
experimental practices, both arise as the consequence of categorization, and both are
the result of forms of extended agency.
Proof of concept claims and the epistemic categories they demarcate make
differences in the various approaches, processes, or products used in a field. These
differences lead to different questions being asked, different methods used, different
knowledge acquired through these, and different outcomes (e.g. platform technolo-
gies, engineered pathways, or biomedical products). That is, they claim that what is
extendable is dependent on what category it belongs to. Research embeds
knowledge within a category. This knowledge can be either epistemological (proof
of concept) or ethical (proof of principle).
But how might we evaluate moral extendability and projectability? If relying on
aesthetic judgments like the yuck factor or avoidance of anti-technology just-so
stories as the basis for ethical judgments about synthetic biology is problematic,
does this mean we must unreflectively embrace all technology in order to avoid
being called a Luddite?
No. Insofar as proofs of principle are projectability claims,
both types of discourse require ethical speculation (cf. Nordmann 2007). The
difficulty is in deciding which speculated future possibilities can be grounds for
ethical decision-making and which cannot. It seems likely that adjudication of
permissible ethical speculation requires careful understanding of the research being
pursued rather than reliance on a broadly-conceived of all-or-nothing approach.
Although there may be some generalized ethical principles that apply across all
categories without regard to context, there seems to be evidence that some are
definable and knowable only within the narrow context of a particular category, (as
This is not to discount the role of thought experiments or the use of literary narratives (such as those
played out in science fiction). The later discussion of extended agency ethics would suggest that these
could play a role but their role would be shared with articulated network of agents involved within the
Doing so would be to assume a false dichotomy that suggests one must either be wholly for or wholly
against technology of all types.
What is Proof of Concept Research and how does it Generate
Author's personal copy
the discussion of the legitimacy or illegitimacy of ethical speculation suggests).
However, the absence of universality of at least some ethical claims runs counter to
many normative theories that base the determination of what is ethical and what is
not on the application of a particular rule or aim to judge what is moral in terms of
its universalizability. For instance, Immanuel Kant’s categorical imperative, Jeremy
Bentham’s hedonic calculus, John Stuart Mill’s principle of utility, and the Golden
Rule all provide universal rules that can be used to decide whether any behaviour or
action is morally right or wrong by applying that rule.
In these approaches, moral imperatives are revealed in the application of the
ethical theory to the situation or action. What underlies these rule-based approaches
is that ethical considerations flow from the theory to the action or practice of some
type of behaviour—not from the behaviour or thing to be given moral consideration.
Although not advocating the particular rule-based ethical theories mentioned in the
above, David Hume’s discussion in A Treatise of Human Nature speaks to the
inability to find value in the world and makes the observation that if ethics exists it
exists outside of the objects, relationships, or actions to which we ascribe morality
or immorality:
Take any action that you think is vicious examine it in all respects, and try
to find what is the matter of fact, or real existence about it that you call evil or
vice you will never find it, till you examine your own self in the matter and
find a sentiment of disapproval, which arises in you, toward this action. Here
you will find a matter of fact; but it is the object of feeling, not of reason
(Hume 1740).
For Hume, ethical judgments are judgments of approval (approbative) or
disapproval (disapprovative). They are moral sentiments. His claim is that the
objects, actions, and relationships of the world have no intrinsic value. His approach
is based on an empiricist view of the mind. The valuation of a thing, action, or entity
is something that only lies in us and is the result of moral contemplation. This view
suggests that empirical investigations on their own are not sufficient to resolve
ethical dilemmas.
Another justification for the impermissibility of assuming ethical prescriptions
and valuations can be read-off empirical descriptions is that if we do so we commit
a category mistake.
Thinking that value can be found merely in the accurate
empirical description of objects, actions, and relationships in the world confuses
what is the case with what ought to be the case. That is, it misappropriates the
answer to the what is it-question as the answer to the how should it be-question.
Simply put, these impermissibility claims say that ethical reasoning cannot be
derived from empirical investigations. But what do these claims commit us to
avoiding? Is it a commitment to the strict orthogonality of epistemic and moral
reasoning? Does it eliminate the possibility of objective moral judgments in ethics?
In the remaining sections, I suggest it does not.
This is usually discussed in the context of the inadmissibility of claiming an ought from an is (the
naturalistic fallacy).
C. E. Kendig
Author's personal copy
An easy solution to this problem would be to suggest that proof of principle may
imply different moral prescriptions on what we should or should not do. Our
responsibility of action may be to consider possible future consequences of a
particular or general situation (based on a kind of act or rule-based utilitarianism). It
could also be in considering what a moral agent should do based on reflecting on
what a fair or just person would do—that is, someone that exemplifies a just
character (virtue ethics). The first of these approaches could be understood as
invoking a duty of reasonable attentiveness to possible future impacts of the
research. The second, a kind of ethics of care that is displayed as a trait of character.
A third option, an after-the-fact or ‘backward looking’ judgment of whether the
course of action was morally correct (see Doorn 2012). Proof of principle may
require not just consideration after-the-fact or consideration of possible future
consequences using deontological or consequentialist approaches to ethics, but may
also require agent-based virtue approaches. Consideration of which approach, (or
which combination of approaches), may be determined with regard to the particulars
of the research activities undertaken. How this works will be fleshed out in the
remaining sections.
Extended Agency Ethics
The context-driven alternative that I suggest can be described as a naturalistic agent-based
approach to ethics. Because this view relies on the extended-mind thesis in cognitive
science (Clark 1995; Clark and Chalmers 1998), I refer to it as ‘extended agency’’.
According to the extended mind thesis, thinking is not exclusively something that
happens in the brain, it is something that is spatiotemporally extended (Clark and
Chalmers 1998; Clark 2010). Mind includes brain but also includes tools used to aid
thinking (e.g. language, culture, pencils, calculators, search engines, mobile phone
apps, and other people). Knowledge is not just epistemologically embedded according
to this view, but it shapes and is reciprocally shaped by our experiences in the world:
we use intelligence to structure our environment so that we can succeed with
less intelligenceit is the human brain plus these chunks of external
scaffolding that finally constitutes the smart, rational inference engine that we
call mind (Clark 1998, 180).
I use this extended mind thesis to suggest how ethical decision making is
ineliminably connected to the research practiced in groups. Normative ethical
evaluations are the result of loops of ethical reflectiveness that—in a multi-agent
system—construct the grounds for objective knowledge through intersubjective
ethical judgements.
Simply put, normative ethical evaluations rely on what people think, what they
do, how they do it, and how they communicate it to others. These evaluations are
dependent on the epistemic capabilities of individuals multiply instantiated in
systems of practice. The systems of practice include human agents, but also their
physical manipulations (e.g. measuring, weighing, running gels), mathematical
modelling, proxied or remote tool use, objects of study (e.g. chassis organisms,
What is Proof of Concept Research and how does it Generate
Author's personal copy
BioBricks), and the extended social communities that they work within (e.g.
research networks that span multiple institutions, iGEM competitions, international
research networks).
Extended agency ethics does not assume that intentionality is the sole domain of
the brain nor that the body merely follows through with what the brain tells it to do.
Instead, agency is not restricted to brain or limited by the boundary of the individual
human organism’s skin. It can extend to the social research network one participates
within with its requisite values and practices. Extended agency provides a
conception of proof of principle that attempts to make sense of it as research that
is extended across both environments and agents and consists of epistemological,
metaphysical, and evaluative judgments.
So, what would a normative ethical decision-making process look like using
extended agency ethics? In pursuing research to find a suitable organism to be used
as a chassis for biofuel production, a team of researchers would use knowledge
acquired from the related areas of research outputs of projects focussing on
cyanobacteria, algae, and metabolism. They may use this broad investigative
approach to narrow down the range of possible candidates for a chassis organism.
They may initially investigate the current algae research and the metabolic pathway
of the highly familiar, well-researched green algae, Chlamydomonas reinhardtii.
Knowledge of the successes and problems associated with the reengineering of
algae as a source of biofuel may lead to the choice of a cyanobacteria instead. Once
a chassis is selected, they may focus attention on the synthetic construction of
pathways that overexpress alkane biosynthetic genes. Following this, they may
begin the task of generating stocks of the newly reengineered form of Synechocystic
sp. In order to plan the most efficient scale-up ventures, economists as well as
microbiologists may be contracted. Once enough product is produced, they may
outsource some beta tests to chemical engineers for kinematic viscosity analysis of
the cyanobacteria-based biofuel product. They may request assistance in testing
combustibility from colleagues specializing in physical chemistry. Limitations on
what can be known and what can be done may come from the reciprocal knowledge
exchanged through these interactions. The normative ethical decisions and
projectable outcomes (in terms of both proofs of concept and proofs of principle)
are obtained through and by these interactions. Knowledge of the organism being
used, the marketability of the product, the scale of production, and the social and
environmental impacts are all linked to the particular organism used. That is, the
ethics of biofuel production varies depending on the organism used, the scaling
applied, the prospects for environmental controls, expected social effects, and
impact on world economics. Extended agency ethics describes the integrated
approach to ethical decision making as one that requires careful consideration of
integrated research and technological activities in order to reasonably predict
possible outcomes. Ethical decisions concerning the potential use of Synechocystic-
based biofuel is not something that comes as purely either backward looking
assessment or forward speculation.
The determination of what should be done is not something that can be judged
solely on the basis of weighing up consequences of action, nor on the basis of rule-
following—categorical or otherwise. Instead, ethical considerations—such as the
C. E. Kendig
Author's personal copy
permissibility of the development of some new technology (e.g. cyanobacterial-
based biofuels)—are determined according to the current research, the experiential
data amassed, the practitioners’ knowledge-making activities, and the potential for
scaling up production of the biofuel products by industry. This means that the locus
of normative agency and intentionality is distributed across the activities of research
groups, tools, and the development of products.
Extended agency provides an externalist view of justification. Justification for
beliefs come not from the mind-inside-the-head version of internalism (as some set
of brain-bounded intuitionism or reflective perception). Instead, a form of active
externalism that distributes cognition and agency across spatiotemporal research
practices is suggested to explain the nature of proof of concept research. The ability
to form research questions and pursue this kind of research depends on aspects of
the technosocial environment in a way that is constitutive in the structuring of the
research as knowledge producing and as extendable as a proof.
Any objects or persons can be reasonably thought of in terms of disassembly
and reassembly; no ‘natural’ architectures constrain system designThe
entire universe of objects that can be known scientifically must be formulated
as problems in communications engineering or theories of the text. Both are
cyborg semiologies (Haraway 1985/2006, 129).
Technologies and scientific discourses can be partially understood as
formalizations, i.e., as frozen moments, of the fluid social interactions
constituting them, but they should also be viewed as instruments for enforcing
meaning. The boundary is permeable between tool and myth, instrument and
concept, historical systems of social relations and historical anatomies of
possible bodies, including objects of knowledge (Haraway 1985/2006, 130).
Extended agency radically revises what makes justified beliefs justified. Justifi-
cation can be on the basis of reflection on mental states, but according to extended
agency, what is taken to be mental is not restricted to the brain but instead goes beyond
the skull and can extend to tools, practices, processes, and other researchers and
research groups. Both epistemic credit and ethical culpability are distributed notions
that extend beyond the individual human agent. If the extended mind thesis is taking
seriously, mental states (usually restricted to the brain by internalist evidentialists) are
extended not only beyond the brain and skin of the individual but to include other
spatiotemporally distinct biological, technological, and socially extended entities.
With this extended cognition, a requisite extended agency and normative ethics based
on this actively externalist theory of evidence follows.
Extended Agency as a Role-based Ethics
Extended agency can be understood to be a kind of role-based approach to ethics
that demarcates categories of valuation analogous to those epistemic categories
(outlined in the first half of this paper). That is, to act in a role is to act according to
This could be seen as a new application of Robert Wilson’s (2004, 2005) social manifestation thesis.
What is Proof of Concept Research and how does it Generate
Author's personal copy
a category of activity or to follow a model or prototypic way of acting. It may be
profitably understood as being akin to an Aristotelian notion of virtue or a context-
driven valuation. The intimacy of epistemic and ethical knowing is explicitly
articulated by a number of virtue ethicists (see in particular Swanton’s 2003, 249
‘virtues as prototypes’’). Instead of understanding morality as being based on a set
of rules, this approach takes virtues to be frameworks. These frameworks are built
from interactions and in-practice experience that both shapes and is shaped by future
interactions in the world (Swanton 2003, 279). Christine Swanton’s ‘virtues as
prototypes’ can be seen as a more restricted version of my extended agency ethics.
Whereas Swanton limits knowledge of the world to agent-based interactions, I
extend it further to include agent-object based interactions. That is, interactions
between humans but also between humans and their objects of investigation are
permitted (cf. Haraway 1985; Wimsatt 2007).
Epistemological categories do not map directly onto those of ethics, but they are
informative in ways that shapes future behaviour. Ethical categories rely on the
epistemological categories insofar as they introduce groupings of organisms, parts,
pathways, or products with similar roles. Moral roles like epistemic roles are
extendable. Whereas epistemic categories shape disciplines and demarcate diverse
knowledge-making distinctions, these collaterally formed role categories that
scaffold normative value attributions. Knowing the role something plays means we
know what valuation to attribute to it which in turn guides our behaviour. We know
how to treat it because we know what kind of role it plays within the process,
procedure, or conceptual framework. Assessment of permissible behaviour is
contextually embedded insofar as it depends on extended agency across a system of
practices. It is decidable given the technological options present, the problems
posed, the policies, protocols, and social infrastructure.
In the foregoing, I have answered the question initially posed in the title and at the
beginning of this paper: what is proof of concept research and how does it generate
epistemic and ethical categories for future experimentation and scientific practice in
synthetic biology? I began the first half of the paper by characterizing proof of
concept research as providing transferable knowledge-making categories through
the activities of scientific investigation. Simply stated, I suggested that proof of
concept research is research that is framed in terms of a particular kind of research
that provides justification in practice of the potential transportability of knowledge
acquired through the experimental test case.
Following this characterization, I explained how this works using an example of
cyanobacteria re-engineered for potential biofuel production. This approach
emphasized the role of scientific practice as central to the generation of categories
of knowledge. I suggested that this practice shift changes what makes justified
beliefs justified—if we focus on practice, we can understand justified beliefs as
being formed through active intervening and modification of devices and pathways
and in the engineering activities of researchers. The upshot? Proof of concept claims
C. E. Kendig
Author's personal copy
and the epistemic categories they demarcate make differences in the various
approaches, processes, or products of a field. These differences lead to different
questions being asked, different methods used, different knowledge acquired
through these, and different outcomes.
In the second half, I argued that there was not just an epistemic notion of proof of
concept research, but that there is also a normative ethical analogue—a proof of
principle. Both proofs are formed through experimental practices and both arise as
the consequence of categorization. I then outlined a role-based account of normative
ethical valuations that I referred to as ‘extended agency ethics’’. Returning to the
example of synthetic biofuel research, I illustrated what this ethical alternative
would look like in situ. The aim of this paper was to articulate the meaning and use
of proof of concept in practice—a project that has so far been missing in the
literature on synthetic biology research and the philosophy thereof. In characterizing
the epistemological and ethical impact such research has, and in proposing an
account of extended agency ethics to better describe the transferrable categories of
knowledge-making and ethical decision making activities that are generated by it,
this research lays a foundation upon which other philosophical work articulating the
meaning and scope of proof of concept and proof of principle activities may be
Acknowledgments Research for this project was funded by the National Science Foundation Division
of Molecular and Cellular Biosciences (MCB), BIOMAPS: Modular Programmed Evolution of Bacteria
for Optimization of Metabolic Pathways, Grant No. MCB-1329350, Research Opportunity Award: ‘‘How
synthetic biology reconfigures biological and bioethical categories’’, Amendment No. 001, Proposal No.
Amyris Biotechnologies (2013). Company website at:
BreakthroughScience. Accessed 15 March 2013.
Association for molecular pathology, V. Myriad genetics, Inc., et al. (2013). Certiorari to the United
States court of appeals for the federal circuit. No. 12–398. Argued 15 April 2013—decided 13 June
Barnes, B., & Dupre
, J. (2008). Genomes and what to make of them. Chicago: University of Chicago
Brent, R. (2004). A partnership between biology and engineering. Nature Biotechnology, 22, 1211–1214.
Chang, H. (2004). Inventing temperature: measurement and scientific progress. New York: Oxford
University Press.
Chang, H. (2007). The myth of the boiling point.
Accessed Sept 2010 and Accessed 23 April 2011.
Chang, H. (2009). Philosophy as complementary science. The Philosophers’ Magazine 40. http://www. Accessed 31 Oct 2010.
Chang, H. (2011). How historical experiments can improve scientific knowledge and science education:
The cases of boiling water and electrochemistry. Science & Education, 20, 317–341.
Clark, A. (1995). I am John’s brain. Journal of Consciousness Studies, 2(2), 144–148.
Clark, A. (1998). Being there: Putting brain, body, and world together again. Cambridge: MIT Press.
Clark, A. (2010). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford: Oxford
University Press.
Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58, 7–19.
Colvin, V. (2004). Regulation? Wait for standardization, commercialization. The Environmental Forum.
What is Proof of Concept Research and how does it Generate
Author's personal copy
Doorn, N. (2012). Responsibility ascriptions in technology development and engineering: Three
perspectives. Science and Engineering Ethics, 18(1), 69–90.
, J. (2006). Humans and other animals. Oxford: Clarendon Press.
Eckdahl, T. T., Campbell, A. M., Heyer, L. J., Poet, J. L., Blauch, D. N., Snyder, N. L., et al. (2015).
Programmed evolution for optimization of orthogonal metabolic output in bacteria. PLoS ONE,
10(2), e0118322. doi:10.1371/journal.pone.0118322.
Endy, D. (2005). Foundations for engineering biology. Nature, 438(24), 449–453.
Erwin, D., & Davidson, E. (2009). The evolution of hierarchical gene regulatory networks. Nature
Reviews Genetics, 10, 141–148.
Genome Consortium for Active Teaching (GCAT) (2013). GGAJET: Golden gate assembly junction
evaluation tool. Accessed 6 Aug 2014.
Gibson, D., Glass, J., Lartigue, C., Noskov, V., Chuang, R.-Y., Algire, M., et al. (2010). Creation of a
bacterial cell controlled by a chemically synthesized genome. Science, 2/329(5987), 52–56.
Hacking, I. (1982). Experimentation and scientific realism. Philosophical Topics, 13(1), 71–87.
Haraway, D. (1985/2006). A Cyborg Manifesto: Science, technology, and socialist-feminism in the late
20th century. In J. Weiss et al. (Eds.), The international handbook of virtual learning environments
(pp. 117–158). Netherlands: Springer.
Haynes, K., Broderick, M., Brown, A., Butner, T., Dickson, J., Harden, W., et al. (2008). Engineering
bacteria to solve the burnt pancake problem. Journal of Biological Engineering, 2(8), 1–12.
Hirshfeld, A. (2014). Guidance for determining subject matter eligibility of claims reciting or involving
laws of nature, natural phenomena and natural products. Alexandria, VA: U.S. Patent and
trademark office (March 4, 2014)
pdf. Accessed 5/3/2015.
Hume, D. (1740/1938). An abstract of a treatise of human nature. Cambridge: Cambridge University
Hylton, W. (2012). Craig Venter’s bugs might save the world. The New York Times, 06-03-12.
Keller, E. F. (2009). Knowledge as making, making as knowing: The many lives of synthetic biology.
Biological Theory, 4(4), 333–339.
Kendig, C. (2014a). Synthetic biology and biofuels. In P. B. Thompson & D. M. Kaplan (Eds.),
Encyclopedia of food and agricultural ethics (pp. 1695–1703). Dordrecht: Springer.
Kendig, C. (2014b). Towards a multidimensional metaconception of species. Ratio, 27(2), 155–172.
Kendig, C. (Ed.) (forthcoming). Natural kinds and classification in scientific practice. London: Routledge.
Knight, T. (2003). Idempotent vector design for standard assembly of biobricks. MIT synthetic biology
working group.
Marchant, G., Meyer, A., & Scanlon, M. (2010). Integrating social and ethical concerns into regulatory
decision-making for emerging technologies. Minnesota Journal of Law, Science, and Technology,
11(1), 345–363.
Morange, M. (2009). Synthetic biology: A bridge between functional and evolutionary biology.
Biological Theory, 4(4), 368–377.
National Science Foundation (2014). Program solicitation: Accelerating innovation research-technology
translation. Directorate for engineering, industrial innovation and partnerships. NSF 14-569. http:// Accessed 3 Dec 2014.
Nordmann, A. (2007). If and then: A critique of speculative nanoethics. Nanoethics, 1, 31–46.
O’Malley, M. (2009). Making knowledge in synthetic biology: Design meets kludge. Biological Theory,
4(4), 378–389.
O’Malley, M. (2010). Exploration, iterativity, and kludging in synthetic biology. Comptes Rendus
Chimie, 14, 406–412.
O’Malley, M., Powell, A., Davies, J., & Calvert, J. (2008). Knowledge-making distinctions in synthetic
biology. BioEssays, 30, 57–65.
Oxford English Dictionary (2014). Proof of concept. Accessed 19 Sept 2014.
Parens, E., Johnston, J., & Moses, J. (2008). Do we need ‘synthetic bioethics?’’. Science, 321, 1449.
Parens, E., Johnston, J. & Moses, J. (2009). Ethical issues in synthetic biology. SYNBIO 3. New York:
Hastings Center. Accessed 10
Sept 2014.
Preston, C. (2008). Synthetic biology: Drawing a line in Darwin’s sand. Environmental Values, 17,
Society for Philosophy of Science in Practice (2014). Website homepage: http://www.philosophy- Accessed 25 Sept 2014.
C. E. Kendig
Author's personal copy
Soler, L. (Ed.) (2012). Characterizing the robustness of science: After the practice turn in philosophy of
science. Volume 292 Boston Studies in the Philosophy of Science, New York: Springer Verlag
Science Business Media.
Soler, L., Zwart, S., Lynch, M., & Israel-Jost, V. (Eds.). (2014). Science after the practice turn in the
philosophy, history, and social studies of science. London: Routledge.
Stich, S. (2006). Is morality an elegant machine or a kludge? Journal of Cognition and Culture, 6,
Swanton, C. (2003). Virtue ethics: A pluralistic view. Oxford: Oxford University Press.
Wang, W., Liu, X., & Lu, X. (2013). Engineering cyanobacteria to improve photosynthetic production of
alka(e)nes. Biotechnology for Biofuels, 6, 69.
69. Accessed 1/11/2013.
Wilson, R. (2004). Boundaries of the mind: the individual in the fragile sciences: Cognition. New York:
Cambridge University Press.
Wilson, R. (2005). Collective memory, group minds, and the extended mind thesis. Cognitive Processing,
6(4), 227–236.
Wimsatt, W. (2007). Re-engineering philosophy for limited beings: Piecewise approximations to reality.
Cambridge: Harvard University Press.
What is Proof of Concept Research and how does it Generate
Author's personal copy
... The term proof of concept has several definitions and practices based on domains. PoC is a common practice in several disciplines, PoC activities have been studied in several fields, both scientific and corporate (Kendig, 2015). ...
... proof of concept research is defined by (Kendig, 2015) as "a research that is framed in terms of a particular kind of research that provides justification in practice of the potential transportability of knowledge acquired through the experimental test case". The justification is associated with the knowledge transportability. ...
University-Industry Collaboration (UIC) is seen as essential engine of local economic development, where it helps in accelerating the process of innovation through the collaboration. This collaboration goes through different stages, from basic research to Proof of Concept to commercialization activities. However, the upstream part of the process is under-researched, little is known about initiating and establishing the collaboration and then conducting the operational activities such as generating, consolidating and testing ideas in order to build proofs of concepts. The purpose of this study is to explore and systematically describe the relevant characteristics of different aspect of the early stage development UIC from initial conditions to eventual outcomes. The in-depth analysis of multiple collaboration aspects will then be used to develop a comprehensive framework encompassing various components of the UIC at different stages. This a qualitative study, started by conducting a systematic literature review to identify UIC collaboration’s factors that lead to initiating the UIC. The identified factors were considered as the predetermined themes for conducting semi-structure interviews to describe the early stage development collaboration in depth. Data collection was in four different engineering schools of Grenoble INP (Institut d'ingénierie et de management de l'Université Grenoble Alpes) and eleven companies based on industrial projects collaborations. The collected data was processed using NVIVO through an iteration process and two coding cycles.The contribution of this study is related to three main parts: Characterizing UIC, UIC conceptual framework and Evaluating UIC. First part of the contribution, rich description of the relevant characteristics of multiple aspects of the early stage development UIC. Second part of the main contribution of this study, we developed a UIC framework based on three stages: “before the collaboration”, “during the collaboration” and “after the collaboration”. Each stage includes different components of the collaboration. Third part of the contribution, we developed a measurement system that evaluates the progress as well as the success of the collaboration. This measurement system is based on three sets of Key Performance Indicators (KPIs), each set corresponds to a stage of the collaboration. The sets are a combination of quantitative and qualitative KPIs. The measurement system and the KPIs sets were validated through two projects. Despite the broader applicability of the proposed tool (framework and performance measurement), however the purpose of this tool in this study is to improve the effectiveness of UIC. It is a twofold purpose:-The framework will help to guide building university-industry relation by guiding the actors at different stages while considering various elements in each stage.-Evaluating the progress as well as the success of the collaboration taking into considerations the different factors that might have positive or negative impact on the collaboration.
... The use of all these tools results in the creation of the so-called proof of concept (PoC), which is a method associated with scientific experimental practices that certifies the feasibility and practical potential of the solution. Unlike the prototype, the PoC demonstrates that the product can be developed, whereas the prototype merely shows how it can be developed [24,25]. ...
Full-text available
Purpose of Review This paper presents some approaches and techniques for translating an idea or research into clinical practice, considering the innovation development process. Recent Findings Innovative tools have been a key solution for healthcare problems, such as musculoskeletal disorders, which represent a great economic burden and are among the leading causes of disability. There has been an increase in publications on this topic, but there has been no analysis of the process of innovation development. This review describes the innovation phases for translating an idea or research into clinical practice, considering the stages of discovering the opportunity, innovation creation, project specification, technology development, and innovation launch. Summary An analysis of the innovation development process to translate an idea or research into clinical practice, including concepts, approaches, and techniques that shows the “why”, “how”, and “what” of innovation.
... This proof of concept, 25 descriptive pre/post clinical study included four evaluation time points: at baseline (presession 1), immediate (postsession 1 and postsession 2), and short-term (before the second session) treatment. One of the most complex aspects of manual therapy is determining optimal dosage. ...
Full-text available
Background: Objectives of soft tissue mobilization applied to cesarean section (C-section) scars are to decrease stiffness and to reduce pain. Research investigating these effects is lacking. Materials and methods: The authors conducted a descriptive, exploratory, proof-of-concept clinical study. Women aged 18 to 40 years who had undergone at least one C-section were recruited. A trained osteopath performed standardized mobilization of the C-section scar once a week for 2 weeks. Scar quality and pain characteristics, viscoelastic properties, pressure pain thresholds, and tactile pressure thresholds were measured before and after each session. Paired Student's t-tests and Friedman's test with Dunn-Bonferroni adjustment were performed to assess the immediate and short-term effects of mobilizations. Kendall's W and Cohen's d were calculated to determine effect sizes over the short term. Simple bootstrapped bias-corrected and accelerated 95% median confidence intervals were computed. Results: Thirty-two participants completed the study. The Patient and Observer Scar Assessment Scale questionnaire revealed differences with small and moderate effects for stiffness (p = 0.021, d = 0.43), relief (p < 0.001, d = 0.28), surface area (p = 0.040, d = 0.36), flexibility (p = 0.007, d = 0.52), and participant opinion (p = 0.001, d = 0.62). Mobilizations increased elasticity (p < 0.001, W = 0.11), decreased stiffness (p < 0.001, W = 0.30), and improved pressure pain thresholds (p < 0.001, W = 0.10) of the C-section, with small to moderate effects. The results also showed decreased tone and mechanical stress relaxation time, as well as increased tactile pressure thresholds at the different measurement times (p < 0.05), but trivial effect sizes (W < 0.10). Creep showed trivial effect and no significant difference (p = 0.09). Conclusion: This study showed that two sessions of mobilization of C-section scar might have a beneficial effect on some viscoelastic properties of the C-section as well as on pain. Some variables of interest useful for future empirical studies are highlighted. ClinicalTrial. Gov NCT04320355.
... In the Oxford English Dictionary, a PoC is broadly defined as "evidence (usually deriving from an experiment or pilot project) demonstrating that a design concept, business idea, etc., is feasible" ( [26], p. 737). On a more abstract level, a PoC can be understood as a research practice aiming to generate new knowledge through experimental tests [27]. From a different angle, PoC activities aim to broaden problem understanding and provide space for scientific activities to create new knowledge that informs further design decisions, hence contribute to the future feasibility of a solution [25]. ...
... By adopting the "Proof of Concept" concept, the main objective is to highlight an approach that allows the framework and study of investments' viability in the digital transformation of companies. The Proof of Concept's adoption aimed to present a practical model that could be adopted and used in the present case to validate its usefulness and practical application (Kendig, 2016). The need for the digital transformation of companies, particularly in the book sector, is a must nowadays. ...
Full-text available
Research purpose. Through the adoption of the concept of the Proof of Concept, the main objective of this work is to highlight the approach that allows the framework and study of the viability of investments in the digital transformation of companies. The research focuses on the publishing sector and, mainly, on one of the largest publishing groups in Portugal and focuses on the strategic decision, due to the covid-19 pandemic situation, to adopt a Warehouse Management System to increase productivity, competitiveness, and sustainability of the company under study. Due to the need for confinement, publishers saw their sales drop drastically and the option of e-commerce implied the need for adjustments in the organizational dynamics associated with the distribution of products. The research/paper goal is to show the viability of investments in the digital transformation of companies in order to enlarge their efficiency and effectiveness.
... We implemented a Proof of Concept (PoC) (Kendig, 2016) using GraphFrames to demonstrate the feasibility of our ap proach and to show its usefulness under following aspects: the processing of Model2GraphFrame outputs, the partition ing of graphs contained in the GraphFrame, connectivity among model elements in a set of GraphFrames, and the ex ecution of model transformation using the GraphFrames. ...
Full-text available
Datacentric (Dc) approaches are being used for data processing in several application domains, such as distributed systems, natural language processing, and others. There are different data processing frameworks that ease the task of parallel and distributed data processing. However, there are few research approaches studying on how to execute model manipulation operations, as model transformations models on such frameworks. In addition, it is often necessary to provide extraction of XMIbased formats into possibly distributed models. In this paper, we present a Model2GraphFrame operation to extract a model in a modeling technical space into the Apache Spark framework and its GraphFrame supported format. It generates GraphFrame from the input models, which can be used for partitioning and processing model operations. We used two model partitioning strategies: based on subgraphs, and clustering. The approach allows to perform model analysis applying operations on the generated graphs, as well as Model Transformations (MT). The proof of concept results such as model2GraphFrame, GraphFrame partitioning, GraphFrame connectivity, and GraphFrame model transformations indicate that our Model Extraction can be used in various application domains since it enables the specification of analytical expressions on graphs. Furthermore, its model graph elements are used in model transformations on a scalable platform.
... It was conceptualized as a proof-of-concept study intended to assess the preliminary efficacy of a digital, videogame-like, cognitive stimulation therapy, as well as its safety and engagement. Proof-of-concept trials are useful in the framework of novel drugs and devices, so knowledge regarding their administration (eg, dosing, user instructions) may be acquired in small samples in order to develop larger clinical trials [51,52]. ...
Full-text available
Background Cognitive stimulation therapy appears to show promising results in the rehabilitation of impaired cognitive processes in attention deficit hyperactivity disorder. Objective Encouraged by this evidence and the ever-increasing use of technology and artificial intelligence for therapeutic purposes, we examined whether cognitive stimulation therapy implemented on a mobile device and controlled by an artificial intelligence engine can be effective in the neurocognitive rehabilitation of these patients. Methods In this randomized study, 29 child participants (25 males) underwent training with a smart, digital, cognitive stimulation program (KAD_SCL_01) or with 3 commercial video games for 12 weeks, 3 days a week, 15 minutes a day. Participants completed a neuropsychological assessment and a preintervention and postintervention magnetoencephalography study in a resting state with their eyes closed. In addition, information on clinical symptoms was collected from the child´s legal guardians. Results In line with our main hypothesis, we found evidence that smart, digital, cognitive treatment results in improvements in inhibitory control performance. Improvements were also found in visuospatial working memory performance and in the cognitive flexibility, working memory, and behavior and general executive functioning behavioral clinical indexes in this group of participants. Finally, the improvements found in inhibitory control were related to increases in alpha-band power in all participants in the posterior regions, including 2 default mode network regions of the interest: the bilateral precuneus and the bilateral posterior cingulate cortex. However, only the participants who underwent cognitive stimulation intervention (KAD_SCL_01) showed a significant increase in this relationship. Conclusions The results seem to indicate that smart, digital treatment can be effective in the inhibitory control and visuospatial working memory rehabilitation in patients with attention deficit hyperactivity disorder. Furthermore, the relation of the inhibitory control with alpha-band power changes could mean that these changes are a product of plasticity mechanisms or changes in the neuromodulatory dynamics. Trial Registration ISRCTN Registry ISRCTN71041318;
This paper introduces a tool designed to mitigate a longstanding challenge to developing social anthropological theories of ritual – how to generate enough comparable case studies for rigorously testing the predictive strength and generalizability of the theory under scrutiny. Our “constitutive relevance of models” (CRoM) test identifies structural continuities between anthropological and psychological theoretical models of ritual phenomena that would justify sharing some analytical tools between models. With this test, anthropologists can in certain cases draw on a psychological theory construct’s superior empirical tractability to more efficiently identify instances of ritual phenomena that are suitable for developing and testing their own anthropological models. To demonstrate, we apply a CRoM test to validate the use of a construct developed under a psychological theory of ritual, Lawson and McCauley’s “ritual form hypothesis,” to search for case studies suitable for assessing the theoretical claims that anthropologist Roy Rappaport made for “highly sacred” rituals.
Background The prevalence of radicular defects after root canal instrumentation is unresolved. This study used micro-CT to assess the relationship between the formation of radicular defects and chemo-mechanical instrumentation in a cadaver model. Methods Maxillary and mandibular molars (n=24) were sectioned from cadaver specimens as a tissue block containing the teeth, alveolar bone and attached mucogingival tissues. After a baseline micro-CT scan (13.45 μm), the specimens were distributed into 3 groups (n=8 molars): Reciproc®, ProTaper Next™ and Mtwo®. Micro-CT scans of each specimen were obtained after access, glide path and preparation with each instrument. The pre-operative and final post-operative micro-CT cross-sectional images of the roots were screened by two blinded examiners to identify any pre-existing and new radicular defects. Pre-existing and new radicular defects were examined histologically. Results Overall, 16 pre-existing radicular defects were identified in 12 of the 24 molars (50%). Most of these were cemental tears (87.5%), and not true dentinal microcracks. New dentinal microcracks were observed in the post-operative micro-CT scans of only 3 canals (3.9%; 3/77). However, only one of these defects was found to be present histologically. Conclusions Within the limitations of the study, chemo-mechanical instrumentation did not routinely promote the formation of radicular defects.
Classic maturity models require one or more trained assessors interacting with interviewees from the organization. This is a very rigorous and therefore costly process. In this paper we have developed the opposite; a relevant-focused and problem-based approach that can be used to generate improvement advice. We start out from the observation that trained assessors often observe symptoms when they enter an organization and find that there is an intuitive correlation with the given recommendations. We then developed a framework of symptoms and underlying problems using a technique called cognitive mapping. This framework was then used in a large organization to derive recommendations based on symptoms. This proof-of-concept seemed to work quite well. We present our framework and discuss how it can be implemented as an online tool. Further we identify several ways our approach can be further researched.
Full-text available
This edited volume of 13 new essays aims to turn past discussions of natural kinds on their head. Instead of presenting a metaphysical view of kinds based largely on an unempirical vantage point, it pursues questions of kindedness which take the use of kinds and activities of kinding in practice as significant in the articulation of them as kinds. It brings philosophical study of current and historical episodes and case studies from various scientific disciplines to bear on natural kinds as traditionally conceived of within metaphysics. Focusing on these practices reveals the different knowledge-producing activities of kinding and processes involved in natural kind use, generation, and discovery. An esteemed group of contributors who are specialists in their field use diverse empirically responsive approaches to explore the nature of kindhood using detailed case studies that exemplify kinding in use. Each chapter is written specifically for this volume and engages with the activities of kinding across a variety of disciplines. Chapters address the nature of kinds, kindhood, kinding, and kind-making in linguistics, chemical classification, neuroscience, gene and protein classification, colour theory in applied mathematics, homology in comparative biology, sex and gender identity theory, memory research, race, extended cognition, symbolic algebra, cartography, and geographic information science. The volume seeks to open up an as-yet unexplored area within the emerging field of philosophy of science in practice, and constitutes a valuable addition to the philosophy and history of science, technology, engineering, and mathematics. Contributions from a diverse group of established and junior scholars in the fields of Philosophy and History and Philosophy of Science including Hasok Chang, Jordi Cat, Sally Haslanger, Joyce C. Havstad Catherine Kendig, Bernhard Nickel, Josipa Petrunic, Samuli Pöyhönen, Thomas A. C. Reydon, Quayshawn Spencer, Jackie Sullivan, Michael Wheeler, and Rasmus Grønfeldt Winther. Preface by John Dupré.
Full-text available
Synthetic biology is a field of research that concentrates on the design, construction, and modification of new biomolecular parts and metabolic pathways using engineering techniques and computational models. By employing knowledge of operational pathways from engineering and mathematics such as circuits, oscillators, and digital logic gates, it uses these to understand, model, rewire, and reprogram biological networks and modules. Standard biological parts with known functions are catalogued in a number of registries (e.g. Massachusetts Institute of Technology Registry of Standard Biological Parts). Biological parts can then be selected from the catalogue and assembled in a variety of combinations to construct a system or pathway in a microbe. Through the innovative re-engineering of biological circuits and the optimization of certain metabolic pathways, biological modules can be designed to reprogram organisms to produce products or behaviors. Synthetic biology is what is known as a “platform technology”. That is, it generates highly transferrable theoretical models, engineering principles, and know-how that can be applied to create potential products in a wide variety of industries. Proponents suggest that applications of synthetic biology may be able to provide scientific and engineered solutions to a multitude of worldwide problems from health to energy. Synthetic biology research has already been successful in constructing microbial products which promise to offer cheaper pharmaceuticals such as the antimalarial synthetic drug artemisinin, engineered microbes capable of cleaning up oil spills, and the engineering of biosensors that can detect the presence of high concentrations of arsenic in drinking water. One of the potential benefits of synthetic biology research is in its application to biofuel production. It is this application which is the focus of this entry. The term “biofuel” has referred generally to all liquid fuels that are sourced from plant or plant byproducts and are used for energy necessary for transportation vehicles (Thompson 2012). Biofuels that are produced using synthetic biological techniques re-engineer microbes into biofuel factories are a subset of these. This chapter entry begins with a short historical background that focuses on initial ethical support and justification for synthetic biofuel research, the impact of this research on public discussion of synthetic biology, and the distinction between it and genetic engineering. The distinction between first and second generation biofuels is introduced. This is followed by a survey of current research innovations using various microbial factories, including: bacteria, yeast, and oil (oleaginous) algae. Ethical considerations associated with synthetic biology research in general and its application to biofuel production in particular will be reviewed. General responses by opponents of all forms of synthetic biology include the claim that this type of technology aims to “play God” and that the unnaturalness of it intervenes in the natural world in ways that are unethical and should therefore be avoided. This justification has been used to attempt to restrict or stop new approaches to biofuel technology that aim to control and co-opt natural selection in order to produce a stable product. Proponents of this synthetic re-engineering suggest that these ethical concerns are unfounded. Synthetic biology merely extends the mechanisms by which artificial selection can be controlled and modified beyond traditional approaches to selective breeding. Ethical considerations that apply specifically to synthetic biofuel research and technology include issues in the design, construction, implementation, marketable production, and assessment of synthetic biofuel production when compared to food crop biomass-based biofuels. Motivations for synthetic applications that focus on the growing concerns over the high cost of production of crop biomass produced biofuels and the subsequent food shortages that followed, widely framed in terms of the food versus fuel debate will be discussed. In addition to these, the ethical issues surrounding the potential impact on human health and the environment consequences of intentional and accidental release of synthetic products of biofuel research will also be covered. Ethical discussion surrounding synthetic biology and biofuels is, like the research and technology itself, still emerging. An outline of the current efforts of commissions and consortia set up in the United States and the United Kingdom that have promoted the scientifically informed open exchange of ideas between scientists and the public on ethical issues relating to synthetic biology research and application are discussed.
Full-text available
Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields – evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation.
Where are the borders of mind and where does the rest of the world begin? There are two standard answers possible: Some philosophers argue that these borders are defined by our scull and skin. Everything outside the body is also outside the mind. The others argue that the meanings of our words "simply are not in our heads" and insist that this meaning externalism applies also to the mind. The authors are suggesting a third position, i.e. quite another form of externalism. Their so called active externalism implies an active involvement of the background in controlling the cognitive processes.
This book offers a comprehensive virtue ethics that breaks from the tradition of eudaimonistic virtue ethics. In developing a pluralistic view, it shows how different 'modes of moral response' such as love, respect, appreciation, and creativity are all central to the virtuous response and thereby to ethics. It offers virtue ethical accounts of the good life, objectivity, rightness, demandingness, and moral epistemology.
Where does the mind begin and end? Robert Wilson establishes the foundations for the view that the mind extends beyond the boundary of the individual. He blends traditional philosophical analysis, cognitive science, and the history of psychology and the human sciences. Wilson then develops novel accounts of mental representation and consciousness, discussing a range of other issues, such as nativism and the idea of group minds. Boundaries of the Mind re-evaluates the place of the individual in the cognitive, biological and social sciences (what Wilson calls the fragile sciences) with an emphasis on cognition. The book will appeal to a broad range of professionals and students in philosophy, psychology, cognitive science, and the history of the behavioral and human sciences. Robert A. Wilson is professor of philosophy at the University of Alberta. He is author or editor of five other books, including the award-winning The MIT Encyclopedia of the Cognitive Sciences (MIT Press, 1999).
In the 1980s, philosophical, historical and social studies of science underwent a change which later evolved into a turn to practice. Analysts of science were asked to pay attention to scientific practices in meticulous detail and along multiple dimensions, including the material, social and psychological. Following this turn, the interest in scientific practices continued to increase and had an indelible influence in the various fields of science studies. No doubt, the practice turn changed our conceptions and approaches of science, but what did it really teach us? What does it mean to study scientific practices? What are the general lessons, implications, and new challenges?.