Skip to main content

Understanding Visual Abduction

The Need of the Eco-Cognitive Model

  • Conference paper
  • First Online:

Part of the book series: Studies in Applied Philosophy, Epistemology and Rational Ethics ((SAPERE,volume 20))

Abstract

The status of abduction is still controversial. When dealing with abductive reasoning misinterpretations and equivocations are common. What did Peirce mean when he considered abduction both a kind of inference and a kind of instinct or when he considered perception a kind of abduction? Does abduction involve only the generation of hypotheses or their evaluation too? Are the criteria for the best explanation in abductive reasoning epistemic, or pragmatic, or both? Does abduction preserve ignorance or extend truth or both? To study some of these conundrums and to better understand the concept of visual abduction, I think that an interdisciplinary effort is needed, at the same time fecundated by a wide philosophical analysis. To this aim I will take advantage of some reflections upon Peirce’s philosophy of abduction that I consider central to highlight the complexity of the concept, too often seen in the partial perspective of limited (even if tremendously epistemologically useful) formal and computational models. I will ponder over some seminal Peircean philosophical considerations concerning the entanglement of abduction, perception, and inference, which I consider are still important to current cognitive research. Peircean analysis helps us to better grasp how model-based, sentential, manipulative, and eco-cognitive aspects of abduction—I have introduced in my book Abductive Cognition (Magnani 2009)—have to be seen as intertwined, and indispensable for building an acceptable integrated model of visual abduction. Even if speculative, Peircean philosophical results on visual abduction certainly anticipate various tenets of recent cognitive research.

Abductive inference shades into perceptual judgment without any sharp line of demarcation between them.

Charles Sanders Peirce, Harvard Lectures on Pragmatism: Lecture VII, 1903.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    I have introduced the basic aspects of visual abduction in Magnani et al. (1994) and Magnani (1996).

  2. 2.

    Cf. Turrisi (1990). Other considerations on abduction and perception are given in Tiercelin (2005).

  3. 3.

    Cf. “Pragmatism as the logic of abduction” , in Peirce (1992–1998, pp. 227–241), the quotation is from footnote 12, pp. 531–532.

  4. 4.

    See below the Appendix: GW and AKM schemas of abduction.

  5. 5.

    On my eco-cognitive model (EC-model) of abduction cf. Magnani (2013).

  6. 6.

    It has to be said that some authors [for example Hoffmann (1999, p. 280)] contend that, in order to explain abduction as the process of forming an explanatory hypothesis within Peirce’s concept of “logic”, it is necessary to see both sides as coming together.

  7. 7.

    It is well-known that in later writings Peirce seems more inclined to see abduction as both insight and inference.

  8. 8.

    Stjernfelt (2007 ) provides a full analysis of the role of icons and diagrams in Peircean philosophical and semiotic approach, also taking into account the Husserlian tradition of phenomenology.

  9. 9.

    For example Kapitan (1997), Hoffmann (1999).

  10. 10.

    On the contrary, some authors [for example Hoffmann (1999, 2004), Paavola (2004 )] , find a central paradox in what (Frankfurt 1958, p. 594) clearly synthesized by saying “[...] that Peirce holds both that hypotheses are the products of a wonderful imaginative faculty in man and that they are product of a certain sort of logical inference”. Furthermore, some commentators seem to maintain that “creative” aspects of abduction would exclusively belong to the perceptual side, as I have already noted above.

  11. 11.

    Cf. the article “The proper treatment of hypotheses: a preliminary chapter, toward an examination of Hume’s argument against miracles, in its logic and in its history” [1901] [in Peirce (1966, p. 692)].

  12. 12.

    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).

  13. 13.

    On the knowledge enhancing role of abduction in guessing models in science cf. Magnani (2013).

  14. 14.

    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).

  15. 15.

    Cf. “The proper treatment of hypotheses: a preliminary chapter, toward an examination of Hume’s argument against miracles, in its logic and in its history” (1901) [in Peirce (1966, p. 692)].

  16. 16.

    Challenges to the modularity hypothesis are illustrated in Marcus (2006).

  17. 17.

    A full treatment of the problem of perception both from a psychological and neural perspective is available in the recent (Raftopoulos 2009 ) . A recent rich volume that shows the semi-encapsulated character of perception as illustrated by recent cognitive science results is Albertazzi et al. (2011).

  18. 18.

    Evidence on the theory-ladenness of visual perception derived from case-studies in the history of science is illustrated in Brewer and Lambert (2001).

  19. 19.

    Cohn et al. (2002 ) propose a cognitive vision system based on abduction and qualitative spatio-temporal representations capable of interpreting the high level semantics of dynamic scenes. Banerjee (2006 ) presents a computational system able to manage events that are characterized by a large number of individual moving elements, either in pursuit of a goal in groups (as in military operations), or subject to underlying physical forces that group elements with similar motion (as in weather phenomena). Visualizing and reasoning about happenings in such domains are treated through a multilayered abductive inference framework where hypotheses largely flow upwards from raw data to a diagram, but there is also a top-down control that asks lower levels to supply alternatives if the higher level hypotheses are not deemed sufficiently coherent.

  20. 20.

    The example of a simple hypothetical organism equipped with two fins and two eyes (Szentagothai and Arbib 1975) can explain this link between perception and action in the case of vision: “The right eye was connected to the left fin by a neuron, and the left eye to the right fin. When a prey appears within the field of the right eye, a command is sent to the left fin to instruct it to move. The organism then turns towards the prey, and this orientation is maintained by bilateral activation until the prey is reached. Perception in this primitive organism is not distinct from action” (de Cheveigné 2006, pp. 253–254).

  21. 21.

    On this interplay and on the role of external representations as material anchors for conceptual blends see also the more recent (Hutchins 2005).

  22. 22.

    That is Gabbay and Woods Schema.

  23. 23.

    \(K^*\) 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.

  24. 24.

    I have shown in this article that, 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 my alternative EC-model model of abduction.

  25. 25.

    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 appendix. 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 et al. (2002 ) . A detailed illustration of the AKM schema is given in Magnani (2009, Chap. 2, Sect. 2.1.3).

  26. 26.

    The target has to be an explanation and K(H) bears \(R^{\textit{pres}}\) [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 ).

  27. 27.

    When abduction stops at line 10 (cf. the GW schema), the agent is not prepared to accept K(H), because of supposed adverse consequences.

  28. 28.

    “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) .

  29. 29.

    I have analyzed the role of abduction in coalition enforcement, as a cognitive tool of the so-called military intelligence in Magnani (2011) and, in the case of epistemic warfare, in Magnani (2012).

References

  • Albertazzi, L., van Tonder, G. J., & Vishwanath, D. (Eds.). (2011). Perception beyond inference: The information content of visual processes. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Aliseda, A. (1997). Seeking explanations: abduction in logic, philosophy of science and artificial intelligence. PhD thesis, Amsterdam: Institute for Logic, Language and Computation.

    Google Scholar 

  • Aliseda, A. (2006). Abductive reasoning. Logical investigations into discovery and explanation. Berlin: Springer.

    Google Scholar 

  • Anderson, D. R. (1987). Creativity and the philosophy of Charles S. Peirce. Oxford: Claredon Press.

    Book  Google Scholar 

  • Angius, N. (2013). Towards model-based abductive reasoning in automated software testing. Logic Journal of the IGPL, 21(6), 931–942.

    Article  Google Scholar 

  • Banerjee, B. (2006). A layered abductive inference framework for diagramming group motions. Logic Journal of the IGPL, 14(2), 363–378.

    Article  Google Scholar 

  • Brewer, W. F., & Lambert, B. L. (2001). The theory-ladenness of observation and the theory-ladenness of the rest of the scientific process. Philosophy of Science, 68, S176–S186 (Proceedings of the PSA 2000 Biennal Meeting).

    Google Scholar 

  • Churchland, P. M. (1988). Perceptual plasticity and theoretical neutrality: A reply to Jerry Fodor. Philosophy of Science, 55, 167–187.

    Article  Google Scholar 

  • Cohn, A. G., Magee, D. R., Galata, G., Hogg, D. C., & Hazarika, S. M. (2002). Towards an architecture for cognitive vision using qualitative spatio-temporal representations and abduction. In C. Freska, C. Habel, & K. F. Wender (Eds.), Spatial cognition III (pp. 232–248). Berlin: Springer.

    Google Scholar 

  • de Cheveigné, A. (2006). Hearing, action, and space. In D. Andler, Y. Ogawa, M. Okada, & S. Watanabe (Eds.), Reasoning and cognition (pp. 253–264). Tokyo: Keio University Press.

    Google Scholar 

  • Fodor, J. (1984). Observation reconsidered. Philosophy of Science, 51, 23–43. Reprinted in [Goldman, 1993, pp. 119–139].

    Google Scholar 

  • Frankfurt, H. (1958). Peirce’s notion of abduction. Journal of Philosophy, 55, 593–397.

    Article  Google Scholar 

  • Gabbay, D. M., & Woods, J. (2008). The reach of abduction. Vol. 2 of A practical logic of cognitive systems. Amsterdam: North-Holland.

    Google Scholar 

  • Goldman, A. I. (Ed.). (1993). Readings in philosophy and cognitive science. Cambridge, MA: Cambridge University Press.

    Google Scholar 

  • Gooding, D. (1996). Creative rationality: Towards an abductive model of scientific change. Philosophica, 58(2), 73–102.

    Google Scholar 

  • Hoffmann, M. H. G. (1999). Problems with Peirce’s concept of abduction. Foundations of Science, 4(3), 271–305.

    Article  Google Scholar 

  • Hoffmann, M. H. G. (2004). How to get it. Diagrammatic reasoning as a tool for knowledge development and its pragmatic dimension. Foundations of Science, 9, 285–305.

    Article  Google Scholar 

  • Hutchins, E. (1995). Cognition in the wild. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Hutchins, E. (2005). Material anchors for conceptual blends. Journal of Pragmatics, 37, 1555–1577.

    Article  Google Scholar 

  • Kakas, A., Kowalski, R. A., & Toni, F. (1993). Abductive logic programming. Journal of Logic and Computation, 2(6), 719–770.

    Article  Google Scholar 

  • Kant, I. (1929). Critique of pure reason. London: MacMillan (Kemp Smith, N. Trans., originally published 1787, reprint 1998).

    Google Scholar 

  • Kapitan, T. (1997). Peirce and the structure of abductive inference. In N. Houser, D. D. Roberts, & J. van Evra (Eds.), Studies in the logic of Charles Sanders Peirce (pp. 477–496). Bloomington and Indianapolis: Indiana University Press.

    Google Scholar 

  • Kowalski, R. A. (1979). Logic for problem solving. New York: Elsevier.

    Google Scholar 

  • Kuipers, T. A. F. (1999). Abduction aiming at empirical progress of even truth approximation leading to a challenge for computational modelling. Foundations of Science, 4, 307–323.

    Article  Google Scholar 

  • Mackonis, A. (2013). Inference to the best explanation, coherence and other explanatory virtues. Synthese, 190, 975–995.

    Article  Google Scholar 

  • Magnani, L. (1996). Visual abduction: Philosophical problems and perspectives. Comment to R. Lindsay, Genralizing from diagrams, In AAAI Spring Symposium (pp. 21–24). Stanford, CA: American Association for Artificial Intelligence.

    Google Scholar 

  • Magnani, L. (2001). Abduction, reason, and science. Processes of discovery and explanation. New York: Kluwer Academic/Plenum Publishers.

    Book  Google Scholar 

  • Magnani, L. (2009). Abductive cognition. The epistemological and eco-cognitive dimensions of hypothetical reasoning. Heidelberg/Berlin: Springer.

    Google Scholar 

  • Magnani, L. (2011). Understanding violence. The interwining of morality, religion, and violence: A philosophical stance. Heidelberg/Berlin: Springer.

    Google Scholar 

  • Magnani, L. (2012). Scientific models are not fictions. Model-based science as epistemic warfare. In L. Magnani, & P. Li (Eds.), Philosophy and cognitive science. Western and eastern studies (pp. 1–38). Heidelberg/Berlin: Springer.

    Google Scholar 

  • Magnani, L. (2013). Is abduction ignorance-preserving? Conventions, models, and fictions in science. Logic Journal of the IGPL, 21(6), 882–914.

    Article  Google Scholar 

  • Magnani, L., Civita, S., & Previde Massara, G. (1994). Visual cognition and cognitive modeling. In V. Cantoni (Ed.), Human and machine vision: Analogies and divergences (pp. 229–243). New York: Plenum Publishers.

    Google Scholar 

  • Marcus, G. F. (2006). Cognitive architecture and descent with modification. Cognition, 101, 443–465.

    Google Scholar 

  • Meheus, J., Verhoeven, L., Van Dyck, M., & Provijn, D. (2002). Ampliative adaptive logics and the foundation of logic-based approaches to abduction. In L. Magnani, N. J. Nersessian, & C. Pizzi (Eds.), Logical and computational aspects of model-based reasoning (pp. 39–71). Dordrecht: Kluwer Academic Publishers.

    Chapter  Google Scholar 

  • Paavola, S. (2004). Abduction through grammar, critic and methodeutic. Transactions of the Charles S. Peirce Society, 40(2), 245–270.

    Google Scholar 

  • Peirce, C. S. (1931–1958). Collected papers of Charles Sanders Peirce. Harvard University Press, Cambridge, MA. vols. 1–6, Hartshorne, C. and Weiss, P., (Eds.); vols. 7–8, Burks, A. W., (Ed.), 1931–1958.

    Google Scholar 

  • Peirce, C. S. (1966). The Charles S. Peirce papers: Manuscript collection in the houghton library. Worcester, MA: The University of Massachusetts Press. Annotated Catalogue of the Papers of Charles S. Peirce. Numbered according to Richard S. Robin. Available in the Peirce Microfilm edition. Pagination: CSP = Peirce / ISP = Institute for Studies in Pragmaticism.

    Google Scholar 

  • Peirce, C. S. (1976). The new elements of mathematics by Charles Sanders Peirce (Vols. I–IV). The Hague-Paris/Atlantic Higlands, NJ: Mouton/Humanities Press (edited by C. Eisele).

    Google Scholar 

  • Peirce, C. S. (1986). Pragmatism as a principle and method of right thinking. The 1903 Harvard lectures on pragmatism. Albany, NY: State University of New York Press. Ed. by Turrisi, P. A., and Peirce, C. S. Lectures on Pragmatism, Cambridge, MA, March 26–May 17, 1903. Reprinted in [Peirce, 1992–1998, II, pp. 133–241].

    Google Scholar 

  • Peirce, C. S. (1987). Historical perspectives on Peirce logic of science: A history of science (Vols. I–II). Berlin: Mouton. (edited by C. Eisele).

    Google Scholar 

  • Peirce, C. S. (1992–1998). The essential Peirce. Selected philosophical writings. Indiana University Press, Bloomington and Indianapolis, 1992–1998. Vol. 1 (1867–1893), Ed. by Houser, N. and Kloesel, C., vol. 2 (1893–1913) Ed. by the Peirce Edition Project.

    Google Scholar 

  • Raftopoulos, A. (2001a). Is perception informationally encapsulated? The issue of theory-ladenness of perception. Cognitive Science, 25, 423–451.

    Google Scholar 

  • Raftopoulos, A. (2001b). Reentrant pathways and the theory-ladenness of perception. Philosophy of Science, 68, S187–S189 (Proceedings of PSA 2000 Biennal Meeting).

    Google Scholar 

  • Raftopoulos, A. (2009). Cognition and perception. How do psychology and neural science inform philosophy? Cambridge, MA: The MIT Press.

    Google Scholar 

  • Roberts, L. D. (2004). The relation of children’s early word acquisition to abduction. Foundations of Science, 9(3), 307–320.

    Article  Google Scholar 

  • Shanahan, M. (2005). Perception as abduction: Turning sensory data into meaningful representation. Cognitive Science, 29, 103–134.

    Article  Google Scholar 

  • Stjernfelt, F. (2007). Diagrammatology, ontology, and semiotics. An investigation on the borderlines of phenomenology. Berlin/New York: Springer.

    Google Scholar 

  • Szentagothai, J., & Arbib, M. A. (1975). Conceptual models of neural organization. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Thagard, P. (1988). Computational philosophy of science. Cambridge, MA: The MIT Press.

    Google Scholar 

  • Thagard, P. (2005). How does the brain form hypotheses? Towards a neurologically realistic computational model of explanation. In P. Thagard, P. Langley, L. Magnani, & C. Shunn, (Eds.), Symposium “Generating explanatory hypotheses: mind, computer, brain, and world”. Cognitive Science Society. Proceedings of the 27th International Cognitive Science Conference, CD-Rom, Stresa, Italy.

    Google Scholar 

  • Thagard, P. (2007). Abductive inference: From philosophical analysis to neural mechanisms. In A. Feeney & E. Heit (Eds.), Inductive reasoning: experimental developmental, and computational approaches (pp. 226–247). Cambridge: Cambridge University Press.

    Google Scholar 

  • Tiercelin, C. (2005). Abduction and the semiotic of perception. Semiotica, 153(1/4), 389–412.

    Google Scholar 

  • Turrisi, P. A. (1990). Peirce’s logic of discovery: Abduction and the universal categories. Transactions of the Charles S. Peirce Society, 26, 465–497.

    Google Scholar 

  • Woods, J. (2009). Ignorance, inference and proof: Abductive logic meets the criminal law. In G. Tuzet, & D. Canale (Eds.), The rules of inference: Inferentialism in law and philosophy (pp. 151–185), Milan, Egea: Bocconi University.

    Google Scholar 

  • Woods, J. (2011). Recent developments in abductive logic. Studies in History and Philosophy of Science, 42(1), 240–244 (Essay Review of L. Magnani, Abductive Cognition: The Epistemologic and Eco-Cognitive Dimensions of Hypothetical Reasoning, Heidelberg/Berlin:Springer, 2009)

    Google Scholar 

  • Woods, J. (2013). Errors of reasoning. Naturalizing the logic of inference. London: College Publications.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lorenzo Magnani .

Editor information

Editors and Affiliations

Appendix: GW and AKM Schemas of Abduction

Appendix: GW and AKM Schemas of Abduction

I have already said that the GW-modelFootnote 22 does a good job in modeling the ignorance-preserving character of abduction and—I am convinced—in designing the correct intellectual framework we should adopt especially when dealing with the problem of abduction as an inference to the best hypothesis/explanation. Following Gabbay and Wood’s contention, it is clear that “[...] abduction is a procedure in which something that lacks epistemic virtue is accepted because it has virtue of another kind” (Gabbay and Woods 2005, p. 62).

For example: “Let S be the standard that you are not able to meet (e.g., that of mathematical proof). It is possible that there is a lesser epistemic standard \(S'\) (e.g., having reason to believe) that you do meet” (Woods 2013, p. 370). Focusing attention on this cognitive aspect of abduction, and adopting a logical framework centered on practical agents, Gabbay and Woods (2005 ) contend that abduction (basically seen as a scant-resource strategy, which proceeds in absence of knowledge) presents an ignorance-preserving (or, better, an ignorance mitigating) character. Of course “[...] it is not at all necessary, or frequent, that the abducer be wholly in the dark, that his ignorance be total. It needs not be the case, and typically isn’t, that the abducer’s choice of a hypothesis is a blind guess, or that nothing positive can be said of it beyond the role it plays in the subjunctive attainment of the abducer’s original target (although sometimes this is precisely so)” (Woods 2013, p. 249). In this perspective, abductive reasoning is a response to an ignorance-problem: one has an ignorance-problem when one has a cognitive target that cannot be attained on the basis of what one currently knows. Ignorance problems trigger one or other of three responses. In the first case, one overcomes one’s ignorance by attaining some additional knowledge (subduance). In the second instance, one yields to one’s ignorance (at least for the time being) (surrender). In the third instance, one abduces (Woods 2013, Chap. 11) and so has some positive basis for new action even if in the presence of the constitutive ignorance.

From this perspective the general form of an abductive inference can be symbolically rendered as follows. Let \(\alpha \) be a proposition with respect to which you have an ignorance problem. Putting T for the agent’s epistemic target with respect to the proposition \(\alpha \) at any given time, K for his knowledge-base at that time, \(K^*\) for an immediate accessible successor-base of K that lies within the agent’s means to produce in a timely way,Footnote 23 R as the attainment relation for T, \(\rightsquigarrow \) as the subjunctive conditional relation, H as the agent’s hypothesis, K(H) as the revision of K upon the addition of H, C(H) denotes the conjecture of H and \(H^c\) its activation. The general structure of abduction can be illustrated as follows (GW-schema):

1. \(T!\alpha \)

[setting of T as an epistemic target with respect to a proposition \(\alpha \)]

2. \(\lnot (R(K,T)\)

[fact]

3. \(\lnot (R(K^*,T)\)

[fact]

4. \(H \not \in K\)

[fact]

5. \(H \not \in K^*\)

[fact]

6. \(\lnot R(H,T)\)

[fact]

7. \(\lnot R(K(H),T)\)

[fact]

8. If H \(\rightsquigarrow \) R(K(H), T)

[fact]

9. H meets further conditions \(S_1, ....S_n\)

[fact]

10. Therefore, C(H)

[sub-conclusion, 1-9]

11. Therefore, \(H^c\)

[conclusion, 1-10]

It is easy to see that the distinctive epistemic feature of abduction is captured by the schema. It is a given that H is not in the agent’s knowledge-set. Nor is it in its immediate successor. Since H is not in K, then the revision of K by H is not a knowledge-successor set to K. Even so, \(H \rightsquigarrow (K(H),T\)) . So we have an ignorance-preservation, as required [cf. (Woods 2013, p. 370)] .

[Note: Basically, line 9. indicates that H has no more plausible or relevant rival constituting a greater degree of subjunctive attainment. Characterizing the \(S_i\) is the most difficult problem for abductive cognition, given the fact that in general there are many possible candidate hypotheses. It involves for instance the consistency and minimality constraints.Footnote 24 These constraints correspond to the lines 4 and 5 of the standard AKM schema of abduction,Footnote 25 which is illustrated as follows:

1. E

2. \(K \not \looparrowright E \)

3. \(H \not \looparrowright E \)

4. K(H) is consistent

5. K(H) is minimal

6. \(K(H) \looparrowright E \)

7. Therefore, H.

(Gabbay and Woods 2005, pp. 48–49)

where of course the conclusion operator \(\looparrowright \) cannot be classically interpreted].Footnote 26

Finally, in the GW-schema C(H) is read “It is justified (or reasonable) to conjecture that H” and \(H^c\) is its activation, as the basis for planned “actions”.

In sum, in the GW-schema T cannot be attained on the basis of K. Neither can it be attained on the basis of any successor \(K^*\) of K that the agent knows then and there how to construct. H is not in K: H is a hypothesis that when reconciled to K produces an updated K(H). H is such that if it were true, then K(H) would attain T. The problem is that H is only hypothesized, so that the truth is not assured. Accordingly Gabbay and Woods contend that K(H) presumptively attains T. That is, having hypothesized that H, the agent just “presumes” that his target is now attained. Given the fact that presumptive attainment is not attainment, the agent’s abduction must be considered as preserving the ignorance that already gave rise to her (or its, in the case for example of a machine) initial ignorance-problem. Accordingly, abduction does not have to be considered the “solution” of an ignorance problem, but rather a response to it, in which the agent reaches presumptive attainment rather than actual attainment. C(H) expresses the conclusion that it follows from the facts of the schema that H is a worthy object of conjecture. It is important to note that in order to solve a problem it is not necessary that an agent actually conjectures a hypothesis, but it is necessary that she states that the hypothesis is worthy of conjecture.

Finally, considering H justified to conjecture is not equivalent to considering it justified to accept/activate it and eventually to send H to experimental trial. \(H^c\) denotes the decision to release H for further premissory work in the domain of enquiry in which the original ignorance-problem arose, that is the activation of H as a positive cognitive basis for action. Woods usefully observes:

There are lots of cases in which abduction stops at line 10, that is, with the conjecture of the hypothesis in question but not its activation. When this happens, the reasoning that generates the conjecture does not constitute a positive basis for new action, that is, for acting on that hypothesis. Call these abductions partial as opposed to full. Peirce has drawn our attention to an important subclass of partial abductions. These are cases in which the conjecture of H is followed by a decision to submit it to experimental test. Now, to be sure, doing this is an action. It is an action involving H but it is not a case of acting on it. In a full abduction, H is activated by being released for inferential work in the domain of enquiry within which the ignorance-problem arose in the first place. In the Peircean cases, what counts is that H is withheld from such work. Of course, if H goes on to test favourably, it may then be released for subsequent inferential engagement (Woods 2009, p. 255 ).

We have to remember that this process of evaluation and so of activation of the hypothesis, is not abductive, but inductive, as Peirce contended. Woods adds: “Now it is quite true that epistemologists of a certain risk-averse bent might be drawn to the admonition that partial abduction is as good as abduction ever gets and that complete abduction, inference-activation and all, is a mistake that leaves any action prompted by it without an adequate rational grounding. This is not an unserious objection, but I have no time to give it its due here. Suffice it to say that there are real-life contexts of reasoning in which such conservatism is given short shrift, in fact is ignored altogether. One of these contexts is the criminal trial at common law” (Woods 2009, p. 255 ).

In the framework of the GW-schema it cannot be said that testability is intrinsic to abduction, such as it is instead maintained in the case of some passages of Peirce’s writings.Footnote 27 This activity of testing, I repeat, which in turn involves degrees of risk proportioned to the strength of the conjecture, is strictly cognitive/epistemic and inductive in itself, for example an experimental test, and it is an intermediate step to release the abduced hypothesis for inferential work in the domain of enquiry within which the ignorance-problem arose in the first place.

Through abduction the basic ignorance—that does not have to be considered total “ignorance”—is neither solved nor left intact: it is an ignorance-preserving accommodation of the problem at hand, which “mitigates” the initial cognitive “irritation” (Peirce says “the irritation of doubt”).Footnote 28 As I have already stressed, in a defeasible way, further action can be triggered either to find further abductions or to “solve” the ignorance problem, possibly leading to what the “received view” has called the inference to the best explanation (IBE).

It is clear that in the framework of the GW-schema the inference to the best explanation— if considered as a truth conferring achievement justified by the empirical approval—cannot be a case of abduction, because abductive inference is constitutively ignorance-preserving. In this perspective the inference to the best explanation involves the generalizing and evaluating role of induction. Of course it can be said that the requests of originary thinking are related to the depth of the abducer’s ignorance.

In Magnani (2013) I have extensively analyzed and criticized the ignorance-preserving character of abduction, taking advantage of my eco-cognitive model (EC-model) of abduction and of three examples taken from the areas of both philosophy and epistemology. Indeed, through abduction, knowledge can be enhanced, even when abduction is not considered an inference to the best explanation in the classical sense of the expression, that is an inference necessarily characterized by an empirical evaluation phase, or an inductive phase, as Peirce called it. Hence, abduction is not always ignorance-preserving, but also knowledge enhancing.

Finally, let us reiterate a passage taken from Woods’ quotation above: “There are lots of cases in which abduction stops at line 10, that is, with the conjecture of the hypothesis in question but not its activation. When this happens, the reasoning that generates the conjecture does not constitute a positive basis for new action, that is, for acting on that hypothesis”. We do not have to forget that, as I have illustrated in Magnani (2013) and in the present article, various ways of positively enhancing knowledge are occurring also in the case of evidentially inert abductions (perception, instinct, scientific models, etc.), and very often a human abductive guess is activated and becomes a basis for action even if it has provided absolutely unreliable—if seen in the light of positive rational criteria of acceptation—knowledge. This is the case for example of the role of abductive guesses in the so-called fallacious and other kinds of reasoning, where the simple struggle that is occurring at the level of the so-called coalition enforcement is at stake.Footnote 29

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Magnani, L. (2015). Understanding Visual Abduction. In: Magnani, L., Li, P., Park, W. (eds) Philosophy and Cognitive Science II. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-18479-1_7

Download citation

Publish with us

Policies and ethics