Exploring Meinong’s Jungle and Beyond

Do all unicorns have snow-white fur?  Is the King of France wise?  What is the shape of a ‘round square’?  Or more generally, does it make sense to reason about non-existent or even impossible objects? What is the ontological status of these objects?  Standard philosophy and logic thought (represented by such spokespeople as Russell and Quine) subscribe to what could be termed the ‘Ontological Assumption’, which is the view that you can’t make true statements about entities that don’t exist (employing the conventional meaning of existence).  

 

Richard Sylvan, an Australian logician, philosopher, and fervent environmentalist (named ‘Richard Routley’ until 1984) offered a contrasting view.  In 1980, he published “Exploring Meinong’s Jungle and Beyond: an investigation of noneism and the theory of items”.   In this work, he extended the work of Alexius Meinong, a 19th century Austrian philosopher who had argued for a theory of objects in which it is possible to reason coherently about objects that don’t exist, or can’t exist.  

 

For example, some theses central to Meinong’s thought are:

 

Although Sylvan believed that Meinong was on the right track, he felt that there were certain paradoxes inherent in Meinong’s thought: “Meinong scarcely develops the logic of his theory of objects”, and so Sylvan was interested in applying the tools of non-classical logic to develop a version of ‘neo-Meinongism’ that he called ‘noneism’. For instance, he questioned both the need for the Law of Non-Contradiction and the Law of the Excluded Middle in order to develop a metaphysics that allows us to discuss the properties of such non-existent objects as unicorns and current Kings of France.

 

Unfortunately, “Exploring Meinong’s Jungle and Beyond” was one thousand pages long, and this forbidding length may have contributed to it being unfairly neglected after its original publication.  Sylvan was well aware of his tendency towards verbosity, quipping that the Jungle Book had an alternative use as “a cheap and excellent doorstop”.  However, through the efforts of editor Maureen Eckert, Sylvan’s work, long out of print, has been brought back in a more accessible format, in which the Jungle Book has been broken up into a four-volume set.  Volume 1 serves as an introduction - in addition to the first chapter of Sylvan’s original work, it offers a set of supplementary essays designed to provide additional context and perspective.  One of these essays, “Re-exploring Item Theory ”, was written by Sylvan himself in 1995, in which he reassesses both Meinong’s pioneering investigations and the Jungle Book’s original formulation of noneism.

 

Particularly intriguing to this reviewer was the final essay in Volume 1, where Filipio Casati speculates that Sylvan’s thought was heading towards a simplified, or ‘minimal’ Item Theory, in which every grammatically well-formed subject signifies an item/object, and every item has a ‘source’, which supplies all the information as to what it is like.  For example, the source for a fictional character is the text (or set of texts) that supplies its characterizing properties.

 

Who is the intended reader for this book? Certainly, the Jungle Book makes demands both mathematically and philosophically. Fortunately, the inclusion of the contributed essays in volume 1 helps a great deal in making Sylvan’s approach and worldview accessible and appealing to non-specialists. For those readers who want to delve even more deeply into his world, volumes 2 through 4 await.  

 

Richard Sylvan would be the first to admit that he was both ambitious and iconoclastic, and this four-volume set succeeds admirably in keeping his work alive for new generations to engage with.

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David Burke is a Principal Scientist at Galois, Inc. He leads the Machine Cognition research program which investigates techniques for integrating human decision-making with machine intelligence (and vice versa).   His research interests include techniques for reasoning under conditions of extreme uncertainty, game theory, and bio-inspired AI.  davidb@galois.com