The dominant computational privacy paradigm rooted in individualist, Western liberal traditions is structurally inadequate for protecting Maori people, the Indigenous population of New Zealand. Maori privacy is fundamentally collective in nature: it covers genealogical records, traditional knowledge systems, culturally treasured resources, and the shared dignity of extended family groups (whanau), sub-tribes (hapu), and tribes (iwi). This article argues that contemporary computational systems including artificial intelligence (AI), biometric recognition platforms, cloud-based data storage, and algorithmic decision-making tools embed design assumptions that structurally exclude Maori privacy interests. Drawing on more than 30 years of practitioner experience and grounded in Maori customary law, cultural protocols, and the Treaty of Waitangi (New Zealand’s founding constitutional document), this article identifies five critical failure modes in current computational architectures and proposes an Indigenous led framework for redesigning privacy into systems at source. It provides technical specifications for implementing collective privacy across three system classes: identity and access management, AI training pipelines, and cloud storage architectures. The article further engages with communitarian and postcolonial traditions within Western privacy theory, situates the analysis within science and technology studies (STS) and critical data studies scholarship, and grounds the five failure modes in documented case evidence. The findings have broad implications for any computational system operating in jurisdictions with Indigenous populations covered by treaty or constitutional obligations.