Chat-Hi: Exploring Indian National Identity Through Machine-Generated Text

Situated at the crossroads of computational politics and intellectual history, article abstracted here interrogates Chat-Hi:, prototype an interactive art installation using a natural language processing model trained on large database speeches by Indian prime ministers since 1946. Machine learning (ML)–powered, Chat-Hi: generates analytically intelligible answers to viewers’ questions, such as: What is idea India? The media acts as conversational archive, gazing medium interpretive layer [1]. It fosters playful, intimate, relational modes historical attention [2], inviting participants actualize past through present political social questioning. Building existing accounts inclusive modernist endeavor makers postcolonial India, we interpret Chat-Hi:’s output revisit argument contrasting Jawaharlal Nehru’s emphasis diversity with Narendra Modi’s stress unity. Far from being anecdotal, this finding subtly signals majoritarian turn democracy.With help its human-machine question-answers digital interface, concerned afterlives figures, facetiously enjoining them topical puzzle: Through interpellations sort addressed uses automated text generation figures convoke into our turbulent times. We aim interrupt presentism [3] formulate answers, look for analogies [4] and—maybe—gather courage act authoritative “specters” [5]. Despite fuzziness modelgenerated texts, insist usefulness these specters in facilitating interpretation identification shifts representation nationhood.The contrast between Prime Minister (PM) (1946–1964) PM (2014–) focus unity outputs strong indication that gradual deepening Hindu nationalist project durably amends statesponsored India. Modi his synthetic avatar reflects long-standing ideology harmony advocated movement, which gives primacy consolidated fold over celebration multiplicity religious community identities. Machine-generated affirms, instance: “The reason culture cohesion society, just doing research, I could clearly understand processes.” contrary epitomizes nationalism based normative belief [6] what be represented people not majority but more abstract collective bound principle secular inclusiveness. This analysis finds echoes Shiv Visvanathan’s study India’s modernity: “[Modi] erased cosmopolitan India nation state, rejecting pluralism predictability uniformity, univocality patriotism. Republic Nehru sought plurality” [7]. two shows there are least ideas conversing past, can appear us clearly.The further discusses epistemic status “human” insights derived machine learning–generated content. start presenting didactic potential particular ability transmit emotions ideas. Following this, outline five methodological aids approach inquiry. facilitates indeed fresh encounter, thematic focus, comparability, confirmation interactivity.The reader’s exposure computer-generated content triggers renewed attention, partly attempt dispel ambiguity authenticity writing. Because puzzle, surprise tension feelings central abductive reasoning [8] research designs [9], they subject reader encounter [10] characters Ministers Atal Bihari Vajpayee or Chandra Shekhar. speculative scrutiny provides rich feedback, stimulating conversations archival machine-generated Such iterative veers away policy-oriented predicaments, focusing instead insights. Second, enables all answer same question, thus offering thematically coherent analyst. Responses possibly might venture various domains, referring country’s foreign policy issues, will ultimately give clues about ideological views nationalism. structured offers possibility comparing speakers, contrastive salient ideational well stylistic traits among them. Indeed, ML do exist vacuum assessed light original texts. intertextual adjusted descriptive analysis, ease lexical patterns speakers given textual dataset.