Abstract
Abduction is a procedure in which something that lacks classical explanatory epistemic virtue can be accepted because it has virtue of another kind: (Gabbay and Woods 2005) contend (GW-Schema) that abduction presents an ignorance-preserving or (ignorance-mitigating) character.
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Notes
- 1.
As I already noted in the preface, a considerable part of the recent academic literature refers the word epistemology to the whole area of cognitive reasoned activities. In this book I adopt its classical intended meaning, which is only referred to scientific cognition.
- 2.
In (Magnani et al. 2016) two types of ignorance are illustrated. They are defined in the dynamic interplay with the two types of abduction, selective and creative (cf. below Sect. 1.2). The first type of ignorance is set within the limits of the agent’s cognitive environment and it is grounded on her own central information, which corresponds to the agent’s topics of expertise and usual employment; she can easily reach them and her ignorance about them is minimal. This type of ignorance involves the part of illusion about the actual knowledge the agent has on her field of expertise. The second type of ignorance concerns peripheral information, which corresponds to what is still within the agent’s cognitive system but that is not in her dominion of expertise, or that she is broadly ignorant about. This kind of ignorance does necessitate more than the agent’s ordinary expertise in order to be understood: it requires more patience and resources to be integrated with the central information. In order to abduce inside this kind of ignorance it becomes necessary to change the eco-cognitive system of the agent and enhancing it with the perspective that even in a zone with peripheral information there still are plenty useful chances to discover.
- 3.
\(K^*\) is an accessible successor of K to the degree that an agent has the know-how to construct it in a timely way; i.e., in ways that are of service in the attainment of targets linked to K. For example if I want to know how to spell “accommodate”, and have forgotten, then my target can’t be hit on the basis of K, what I now know. But I might go to my study and consult the dictionary. This is \(K^*\). It solves a problem originally linked to K .
- 4.
That is Gabbay and Woods Schema .
- 5.
In the case of inner processes in organic agents, this sub-process— here explicitly modeled thanks to a formal schema—is considerably implicit, and so also linked to unconscious ways of inferring, or even, in Peircean terms, to the activity of the instinct (Peirce 1931–1958, 8.223) and of what Galileo called the lume naturale (Peirce 1931–1958, 6.477), that is the innate fair for guessing right. This and other cognitive aspects can be better illustrated thanks to the alternative eco-cognitive model (EC-Model) of abduction I will sketch below, Sect. 1.2.
- 6.
The classical schematic representation of abduction is expressed by what (Gabbay and Woods 2005) call AKM-schema, which is contrasted to their own (GW-schema), which I am just explaining in this subsection. For A they refer to Aliseda (1997; 2006), for K to Kowalski (1979), Kuipers (1999), and Kakas et al. (1993), for M to Magnani (2001) and Meheus (Meheus et al. 2002). A detailed illustration of the AKM schema is given in (Magnani 2009, Chap. 2, Sect. 2.1.3).
- 7.
The target has to be an explanation and K(H) bears \(R^{pres}\) [that is the relation of presumptive attainment] to T only if there is a proposition V and a consequence relation \(\looparrowright \) such that \(K(H) \looparrowright V\), where V represents a payoff proposition for T. In turn, in this schema explanations are interpreted in consequentialist terms. If E is an explanans and \(E'\) an explanandum the first explains the second only if (some authors further contend if and only if) the first implies the second. It is obvious to add that the AKM schema embeds a D-N (deductive-nomological) interpretation of explanation, as I have already stressed in (Magnani 2001, p. 39).
- 8.
When abduction stops at line 10. (cf. the GW-schema), the agent is not prepared to accept K(H), because of supposed adverse consequences.
- 9.
Hintikka usefully notes (see also below p. 12), and I agree with him, that Peirce was right in denying the role of “naked” induction in forming new hypotheses. At the same time he warns us about the use of the word induction in the case of the testing of hypotheses: “[...] I do not think that it is instructive to call such reasoning inductive, but this is a merely terminological matter” (Hintikka 2007, p. 55). I myself I am referring here to tests as instrumental/empirical “inductive” ones, in the spirit of Peircean special use of the word induction that Hintikka stigmatizes. Of course, in the case of human agents and in a perspective about “testing” I am not endorsing here, tests might be considered some sorts of mental assessment, such as for example the coherence of an abduction, a test in which no physical actions are involved. If such assessments are informed by knowledge gained by a thinker through previous experience, then those mental assessments take the character of implicit inductions, here intended in the classical sense of the term.
- 10.
“The action of thought is excited by the irritation of doubt, and ceases when belief is attained; so that the production of belief is the sole function of thought” (Peirce 1987, p. 261) .
- 11.
By illustrating abductive/inductive reasoning of preservice elementary majors on patterns that consist of figural and numerical cues in learning elementary mathematics Rivera and Rossi Becker monitor the subsequent role of induction. In performing the abductive task to the general form/hypothesis the subjects referred to the fact they immediately saw a relationship among the drawn cues in terms of relational similarity “[...] within classes in which the focus was not on the individual clues in a class per se but on a possible invariant relational structure that was perceived between and, thus, projected onto the cues” (Rivera and Rossi Becker 2007, p. 151). Through the follow-up inductive stage of generalizations the subjects tested the hypotheses just examining extensions (new particular cases beyond what was available at the beginning of the reasoning process). This process was also able to show subjects’s disconfirmation capacities: they acknowledged their mistakes in generating a bad induction, which had to be abandoned, in so far as they were checked as insufficient in fully capturing in symbolic terms a general attribute that would yield the total number of toothpicks in new generated cues.
- 12.
I have proposed the dichotomic distinction between selective and creative abduction in (Magnani 2001) . In the same book I have illustrated the so-called Select and Test Model (ST-model) . It is an epistemological model of medical reasoning, which can be described in terms of the classical notions of abduction, deduction and induction; it describes the different roles played by such basic inference types in developing various kinds of medical reasoning (diagnosis, therapy planning, monitoring). The model is consistent with the Peircean view about the various stages of scientific inquiry in terms of “hypothesis” generation (abduction), deduction (prediction), and induction. The model has been used to implement medical knowledge-based systems of medical reasoning in artificial intelligence (AI) .
- 13.
A rich treatment of the basic “paraconsistent” logical perspectives concerning abduction and the role of inconsistencies is contained in (Carnielli 2006).
- 14.
On instrumental and explanatory abduction see (Magnani 2009, Chap. 2): examples of the non-explanatory features of abduction are present in logic and mathematical reasoning. Chapter 2 of the quoted book gives an analysis of how the importance of non-explanatory abduction in logical and mathematical reasoning is clearly even if implicitly envisaged by Gödel . Furthermore, physics often aims at discovering physical dependencies which can be considered explanatorily undetermined. In this case abduction exhibits an instrumental aspect. Below in Chap. 3, Sect. 3.1 I contend that this character is sometimes related to the conventional nature of the involved scientific hypotheses.
- 15.
In general we cannot be sure that our guessed hypotheses are plausible (even if we know that looking for plausibility is a human good and wise heuristic), indeed an implausible hypothesis can later on result plausible. Moreover, when a hypothesis solves the problem at hand, this is enough as to count as solution of the abductive problem (even if, not necessarily a good solution or the best solution). If we want to preserve the property of plausibility, at most we can say that in some cases it is just potential, given the time-dependency I have just indicated. In Sect. 6.2.2 of Chap. 6 I will describe that, for example, the strange Cartesian hypothesis of a plenum vortices made of particles, destroyed by the Newtonian concept of action at distance, later on appeared fully compatible with the Einsteinian framework.
- 16.
In fact, for Peirce “[...] the perceptual judgments, are to be regarded as an extreme case of abductive inference” (Peirce 1931–1958, 5.181).
- 17.
A relatively recent cognitive research related to artificial intelligence (AI) presents a formal theory of robot perception as a form of abduction, so reclaiming the rational relevance of the speculative anticipation furnished by Peirce, cf. (Shanahan 2005).
- 18.
It is interesting to note that recent research on Model Checking in the area of AST (Automated Software Testing) takes advantage of this eco-cognitive perspective, involving the manipulative character of model-based abduction in the practice of adapting, abstracting, and refining models that do not provide successful predictions. Cf. (Angius 2013) .
- 19.
Some acknowledgment of the general contextual character of these kinds of criteria, and a good illustration of the role of coherence, unification, explanatory depth, simplicity, and empirical adequacy in the current literature on scientific abductive best explanation, is given in (Mackonis 2013).
- 20.
I have illustrated the role of abduction in military intelligence in (Magnani 2011, Chap. 2), where I have extendedly treated the relationship between cognition, morality, and violence .
- 21.
- 22.
Peirce makes reference to this “flash” in connection to abduction in perceptual judgments (see above footnote 16).
- 23.
A logical system is monotonic if the function Theo that relates every set of wffs to the set of their theorems holds the following property: for every set of premises S and for every set of premises \(S'\), \(S \subseteq S' \) implies Theo(\(S) \subseteq \) Theo(\(S')\). Traditional deductive logics are always monotonic: intuitively, adding new premises (axioms) will never invalidate old conclusions. In a nonmonotonic system, when axioms, or premises, increase, their theorems do not (Ginsberg 1987; Lukaszewicz 1970; Magnani and Gennari 1997). Following this deductive nonmonotonic view of abduction, we can stress the fact that in actual abductive medical reasoning, when we increase symptoms and patients’ data [premises], we are compelled to abandon previously derived plausible diagnostic hypotheses [theorems].
- 24.
Instinct is of course in part conscious: it is “always partially controlled by the deliberate exercise of imagination and reflection” (Peirce 1931–1958, 7.381).
- 25.
I have described perception as abduction in the Sect. 1.2 above.
- 26.
Cognitive anthropologist Atran advocated a similar view about a century later, arguing in his Cognitive Foundations of Natural History that the evolution of religion and pre-scientific forms of knowledge into fully-blown science could be accounted for just recurring to the concepts of culture and cognition, understanding the latter as “the internal structure of ideas by which the world is conceptualized” (Atran 1990, p. 3). Peirce’s philosophical speculations have been recently corroborated by a growing interest in folk science, that is in the study of uneducated expectations about natural aspects such as biology, mechanics, psychology, physiology and so on. Berlin and his colleagues pioneered the exploration of folkbiological expectations across different cultures (Berlin et al. 1973) . The existence of folk science does not make the case for the actuality of a lume naturale predisposing humans towards Truth, but for the reality of a penchant (which is also at the level of perception) towards truthfulness: (Keil 2010) argues that the success of science partially comes from “the ways in which scientists learn to leverage understandings in other minds and to outsource explanatory work through sophisticated methods of deference and simplification of complex systems,” (p. 826) but such ways of relying on other people’s knowledge in order to achieve better approximations of the truth about a matter are actually preexistent in laypeople and children.
- 27.
Cf. Arisbe Website, http://www.cspeirce.com/menu/library/bycsp/l75/ver1/l75v1-01.htm. The passage comes from MS L75 Logic, regarded as semeiotic (The Carnegie application of 1902).
- 28.
- 29.
- 30.
This is not a view that conflicts with the idea of God’s creation of human instinct: it is instead meant on this basis, that we can add, with Peirce, the theistic hypothesis, if desired.
- 31.
Of course this conclusion does not mean that artifacts like computers do not or cannot perform abductions. The recent history of artificial intelligence (AI) in building systems able to perform diagnoses and creativity clearly illustrates this point.
- 32.
In (Magnani 2011, Sect. 6.5) I addressed the related problem of what I call “moral epistemology” (which comprehends the intrinsic “morality of sound reasoning” and is concerned with a somehow moral “commitment to the truth”), supposed to be clever in a pure way and able to foster good moral outcomes for everyone.
- 33.
When established hypotheses are attacked scientists are compelled to respond to an endless wave of unnecessary and unhelpful objections and demands and an atmosphere is created in which scientists fear to address certain topics and/or to defend hypotheses. In these cases they can unfortunately adopt a weaker epistemic attitude than the one they would have implemented in a more serene eco-cognitive environment: a situation of what I call epistemic irresponsibility can arise (cf. below Chap. 8 of this book). .
- 34.
- 35.
(Douglas 2000, p. 578) usefully adds that there is inductive risk not only in accepting a hypothesis but also a related risk when accepting methodologies, data, and interpretations.
- 36.
Scientists working on a particular program have moral reasons for taking into account the most relevant societal consequences of their research and for attempting to weaken the harmful outcomes that it might have. Moreover, scientists have to be aware of scientific situations in which available information and knowledge are too uncertain or insufficient. Of course, not always scientists can dominate the situation by themselves: in these cases it can be “harmful or impracticable for scientists to respond to this uncertainty by withholding their judgment or supplying only minimally interpreted data to decision makers”(Elliott 2010) .
- 37.
On the several ways in which “the product defense industry” ambiguously exploits scientific (and pseudoscientific) arguments to undermine public health protections, corrupt the scientific record, and mislead the public cf. (Michaels 2008) . More details about the current dangers which human creative abduction and scientific cognition are facing with are illustrated below in Chap. 8, this book.
- 38.
- 39.
In my research I often emphasized the role of gossip. Dunbar (2004) originally gives scientific cognitive dignity to gossip explaining it in the framework of the so-called “social brain hypothesis”. Posited in the late 1980s, this hypothesis contends that the relatively large brains of human beings and other primates reflect the computational demands of complex social systems and not just the need to process information of ecological relevance. Cf. also the recent (Magnani 2011) and (Bertolotti and Magnani 2014) .
- 40.
In essence, the idea holds that human beings often can and even should be treated as “things”, and that in the process they become “respected as things” that had been ascribed more value than some people. We must reappropriate the instrumental and moral values that people have lavished on external things and objects, which I contend is central to reconfiguring human dignity in our technological world.
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Magnani, L. (2017). Enhancing Knowledge. In: The Abductive Structure of Scientific Creativity. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 37. Springer, Cham. https://doi.org/10.1007/978-3-319-59256-5_1
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