Results 141 to 150 of about 41,578 (284)
Adversaries Can Misuse Combinations of Safe Models [PDF]
arXivDevelopers try to evaluate whether an AI system can be misused by adversaries before releasing it; for example, they might test whether a model enables cyberoffense, user manipulation, or bioterrorism. In this work, we show that individually testing models for misuse is inadequate; adversaries can misuse combinations of models even when each individual
arxiv
Biowarfare, bioterrorism and biocrime: A historical overview on microbial harmful applications
Forensic Science International, 2020 Manuela Oliveira +4 more
semanticscholar +1 more source
Mpox Detection Advanced: Rapid Epidemic Response Through Synthetic Data [PDF]
arXivRapid development of disease detection models using computer vision is crucial in responding to medical emergencies, such as epidemics or bioterrorism events. Traditional data collection methods are often too slow in these scenarios, requiring innovative approaches for quick, reliable model generation from minimal data.
arxiv
On Regulating Downstream AI Developers [PDF]
arXivFoundation models - models trained on broad data that can be adapted to a wide range of downstream tasks - can pose significant risks, ranging from intimate image abuse, cyberattacks, to bioterrorism. To reduce these risks, policymakers are starting to impose obligations on the developers of these models.
arxiv
Survey of chief livestock officials regarding bioterrorism preparedness in the United States [PDF]
, 2000 Ann Fitzpatrick, Jeff B. Bender
openalex +1 more source
Biosecurity: A 21st Century Challenge [PDF]
, 2005 Based on a review of key reports and experts' opinions, summarizes the debate over "dual-use" technologies and the various approaches to controlling biosecurity risk.
M. J. Zuckerman
core
Health and security challenges of the 21st century: Bioterrorism [PDF]
ABC: časopis urgentne medicine, 2016 Microorganisms and diseases caused by them are one of the major health challenges and considering their possible consequences (medical, social, psychological, economic) represent one of the biggest security risks of the 21st century. This is confirmed by
Ristanović Elizabeta
doaj
SynthVision -- Harnessing Minimal Input for Maximal Output in Computer Vision Models using Synthetic Image data [PDF]
arXivRapid development of disease detection computer vision models is vital in response to urgent medical crises like epidemics or events of bioterrorism. However, traditional data gathering methods are too slow for these scenarios necessitating innovative approaches to generate reliable models quickly from minimal data.
arxiv