Can Knowledge Be Translated (by a Machine)?

Abstract

This paper takes up the important questions whether (i) machines—by means of software—can translate texts, thereby imitating translations made by humans, and (ii) publications in the fields of scientific domains and engineering can be translated by machines to an almost perfect level. This paper examines some issues in this context, among them the question if software can be compared with the minds processed by human brains, if machines handle information or something else, if knowledge is found in software (including some deliberations on what knowledge is), and if the latest software developments are what they declare. This paper concludes that machines may assist translators but that they will not, by principle, be able to reach an almost perfect level. Accordingly the specific aim (I shall not label it objective) is to point to theoretical and analytic (parsing) obstacles to the idea that machines can produce acceptable translations in all contexts. I demonstrate that certain combinations of words will present systems with insurmountable challenges; challenges which also present human translators with questions that have almost unattainable answers. Therefore I object to the huge amount of money spent on software development for systems with that objective. I also point to the option of developing more relevant alternatives, including simpler solutions. If you ask for new insights—like you would do when perusing a research paper in order to update your professional frame of reference—there are, basically, no new insights in this theoretical scientific article. I just make it transparent what all linguists know, i.e., that in the field of machines handling language, less focus should be on what electronic systems can, or cannot, do and more focus on what details in language, and languages, will make certain kinds of handling particularly arduous; to the verge of being insurmountable.