Preparedness for a Dirty Bomb Attack in New York
“Is New York City adequately prepared for a ‘dirty bomb’ attack?” asked John Sudnik, a deputy chief at the New York Fire Department in a recent master’s thesis (pdf) on the prospects of a terrorist incident involving a radiological weapon.
In response to this question, the author provided an assessment of the threat, the consequences of an attack, and the possibilities of mitigating such consequences.
See “‘Dirty Bomb’ Attack: Assessing New York City’s Level of Preparedness from a First Responder’s Perspective” by John Sudnik, Naval Postgraduate School, March 2006.
These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
The evidence is clear: algorithmic pay-setting is established in app-based work, and payroll/timekeeping failures show how software can produce systemic wage harm at scale
While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.
When properly structured — with specific numeric targets, secured financial obligations, independent monitoring, and meaningful enforcement — CBAs transform data center deals into durable community partnerships.