I used ChatGPT, Gemini, and Perplexity to research a gnarly NYC rent situation. Here's what I learned.

New York City is notorious for its high rent prices, alongside the inevitabilities of death and taxes. While AI may not have a solution for the first two, it has proven to be an invaluable resource for navigating complex rental situations. Residing in a former superintendent-occupied apartment within a prewar co-op in Manhattan, I initially signed a market-rate lease, only to discover later that my unit might be classified as 'rent-stabilized.' This classification is significant in New York, as it can limit how much landlords can increase rent based on specific criteria. Upon investigating, I found that my apartment had a history of being registered as rent-stabilized since the 1980s, with no clear record of deregulation. This led me to question whether I could still benefit from rent stabilization protections against potential steep rent hikes in the future. With traditional search methods yielding little clarity, I turned to AI tools for assistance. By uploading a photo of my apartment's rent-registration history, I sought guidance from ChatGPT. It analyzed the document and indicated that such situations are typically reviewed by the New York State Division of Housing and Community Renewal, the body responsible for enforcing rent stabilization laws in the city. Curious about the reliability of its responses, I asked ChatGPT for its sources. It cited relevant sections of the rent-stabilization code and various court rulings. To verify the information, I also consulted Perplexity and Google Gemini. While all three AI tools arrived at similar overarching conclusions, they varied in their logical processes and citation methods. I found Gemini, in particular, to be the most cautious in its assertions, which increased my trust in its responses. However, I encountered inaccuracies from all three systems. Notably, Gemini once referenced a non-existent legal case, but promptly corrected itself when I pointed it out. This prompted me to rigorously challenge the AI-generated conclusions, even role-playing as a landlord to present counterarguments that could be made against my rent-stabilized claim. Ultimately, I hit a barrier in my research, as all three AI tools maintained that my circumstances warranted further inquiry by the DHCR. This prompted me to seek a professional opinion from a housing attorney, which cost me $35 through the New York Bar Association's referral service. After reviewing my documents, the attorney concurred that pursuing a rent-overcharge complaint was a sensible step. The process is still underway, and no final decision has been made yet. While my case may be unique, it underscores the potential of AI in unraveling complex legal matters and the importance of seeking professional advice in navigating the intricacies of New York's rental regulations.