Technological devices have become anthropomorphized in the domestic environment. Natural language processors (NLPs) such as Siri and Alexa are humanized to convince the user of their lifelikeness. However, the native language of NLPs is that of byte code and assembly code, an unspoken written language that is then translated into what the user perceives as a seemingly Human speech. The true language of the NLPs is the artificial language of the computer which is hidden behind the internal processes of such devices. To truly understand the native language and inner “thoughts” of voice translation software, we would need to transpose the stream of written code behind every action, every command.
‘5 SECONDS TO ANSWER’ is a Wikipedia based Natural Language Processor which follows the traditional, speech to text, text to speech software of the Siris and Alexas today. Upon prompting the interface with a question, 5 seconds later, the user receives the response to their inquiry in a human language. The following interfaces dehumanizes the Natural Language Processor by exposing its complexities and unheard monologue existant in every interaction with these devices.
‘278 SECONDS TO PRINT’ exposes the inner monologue of the Natural Language Processor, an unspoken computer language veiled behind the interface of the device. 13,470,381 lines of python code run in 5 seconds to enable the seemingly instantaneous operation of NLPs, like Siri, Alexa and in this case, 5 SECONDS TO ANSWER. The printing of code alters the internal workings of the program, changing the information bound paths from IO to CPU, in turn, streaming the unseen language of the NLP.
‘156 DAYS TO CHART’ maps the 13,470,381 lines of code streaming in 278 seconds within the Natural Language Processor. Each of the characters was, at one point in time, input by a human. By charting the 5 second interaction line by line, not only is the true language of the processor made visible, but it is also made comprehensible by the visualization of patterns and repetitions, tracing the computational ‘thought’ process of NLPs.