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Sanjana Gautam

Sanjana Gautam appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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4 published item(s)

preprint2026arXiv

What if AI systems weren't chatbots?

The rapid convergence of artificial intelligence (AI) toward conversational chatbot interfaces marks a critical moment for the industry. This paper argues that the chatbot paradigm is not a neutral interface choice, but a dominant sociotechnical configuration whose widespread adoption reshapes social, economic, legal, and environmental systems. We examine how treating AI primarily as conversational assistants has extensive structural downsides. We show how chatbot-based systems often fail to adequately meet user needs, particularly in complex or high-stakes contexts, while projecting confidence and authority. We further analyze how the normalization of chatbot-mediated interaction alters patterns of work, learning, and decision-making, contributing to deskilling, homogenization of knowledge, and shifting expectations of expertise. Finally, we examine broader societal effects, including labor displacement, concentration of economic power, and increased environmental costs driven by sustained investment in large-scale chatbot infrastructures. While acknowledging legitimate benefits, we argue that the current trajectory of AI development reflects specific value choices that prioritize conversational generality over domain specificity, accountability, and long-term social sustainability. We conclude by outlining alternative directions for AI development and governance that move beyond one-size-fits-all chatbots, emphasizing pluralistic system design, task-specific tools, and institutional safeguards to mitigate social and economic harm.

preprint2026arXiv

Who Owns Creativity and Who Does the Work? Trade-offs in LLM-Supported Research Ideation

LLM-based agents offer new potential to accelerate science and reshape research work. However, the quality of researcher contributions can vary significantly depending on human ability to steer agent behaviors. How can we best use these tools to augment scientific creativity without undermining aspects of contribution and ownership that drive research? To investigate this, we developed an agentic research ideation system integrating three roles -- Ideator, Writer, and Evaluator -- across three control levels -- Low, Medium, and Intensive. Our mixed-methods study with 54 researchers suggests three key findings in how LLM-based agents reshape scientific creativity: 1) perceived creativity support does not simply increase linearly with greater control; 2) human effort shifts from ideating to verifying ideas; and 3) ownership becomes a negotiated outcome between human and AI. Our findings suggest that LLM agent design should emphasize researcher empowerment, fostering a sense of ownership over strong ideas rather than reducing researchers to operating an automated AI-driven process.

preprint2022arXiv

In Alexa, We Trust. Or Do We? : An analysis of People's Perception of Privacy Policies

Smart home devices have found their way through people's homes as well as hearts. One such smart device is Amazon Alexa. Amazon Alexa is a voice-controlled application that is rapidly gaining popularity. Alexa was primarily used for checking weather forecasts, playing music, and controlling other devices. This paper tries to explore the extent to which people are aware of the privacy policies pertaining to the Amazon Alexa devices. We have evaluated behavioral change towards their interactions with the device post being aware of the adverse implications. Resulting knowledge will give researchers new avenues of research and interaction designers new insights into improving their systems.

preprint2022arXiv

Understanding Twitters behavior during the pandemic: Fake News and Fear

The outbreak of the SARS-CoV-2 novel coronavirus (COVID-19) has been accompanied by a large amount of misleading and false information about the virus, especially on social media. During the pandemic social media gained special interest as it went on to become an important medium of communication. This made the information being relayed on these platforms especially critical. In our work, we aim to explore the percentage of fake news being spread on Twitter as well as measure the sentiment of the public at the same time. We further study how the sentiment of fear is present among the public. In addition to that we compare the rate of spread of the virus per day with the rate of spread of fake news on Twitter. Our study is useful in establishing the role of Twitter, and social media, during a crisis, and more specifically during crisis management.