I think three more interesting possible explanations are that (1) philosophers are more methodologically skeptical than other humanities, (2) philosophers have long integrated computational methods in their work and so don’t need a revolution, and (3) the practice of philosophy is somehow more bound to traditional text-based approaches than other humanities. The first answer has some appeal, but other methodological revolutions such as X-Phi seem to be thriving, at least as measured by disciplinary footprint (though perhaps we as a discipline can only process one methodological revolution at a time). Tony Beavers explored the second answer in his presentation (available online–http://badhumanist.blogspot.com/2013/03/computational-philosophy-its-place-in.html). I think there’s certainly something to this answer, though philosophers tend to underestimate the rich tradition of “humanities computing” that exists in other humanities like English, History, and the Classics.

The third explanation is also interesting and probably the most significant, I think, though I suspect we’re just suffering from a collective failure of imagination. Graduate training in philosophy so relies upon heavy reading loads and perfection of the art of the term paper that it can seem inevitable that textual dialectic is essential to the practice of philosophy. When we compare the familiar methods of reading and writing to some of the more recent computational methods and visualizations, the former can seem a transparent window on philosophical truth and the latter comparatively opaque and bewildering. But surely the art of reading and writing text is itself merely another technology, and there is no essential link between traditional text-based methods and philosophical truth. As Tony’s presentation noted, there are scads of interesting ways to apply computational techniques to philosophical problems. And many more wait on the horizon for someone who can combine a deep familiarity with philosophical problems with methodological creativity (and also with, let’s be honest, a heavy dose of professional risk).

Moving forward, you’re quite right to note that machines appear to lack the kind of intelligence required to solve philosophical problems. But that’s not what’s proposed by any melding of DH and Philosophy that I’m aware of. A different approach would be to use computers to help us see patterns, argument forms, implications, or comparisons that are philosophically relevant, but that would be difficult or impossible to appreciate unaided. This is how DH typically works in other disciplines; in digital history projects, computational methods don’t interpret history for the historians, but rather lay out the patterns of history in a way that makes richer interpretations possible. In digital philosophy, it will still be up to us to interpret any patterns we find and say why they matter to truth, justice, beauty, consciousness, life, meaning, etc.; but if you go through the examples in the presentations, I think you’ll find that the idea that computers can help us make philosophical progress is not as far-fetched as it might have initially seemed.