LEARNING
AI Safety: A Poisoned Chalice?
Helen Nissenbaum
- Year
- 2024
- Citations
- 1
- Access
- Open access
Abstract
We hear a lot about the awesome potential of AI—the achievements of reinforcement learning, the astonishing power of foundation models and generative AI. Amplifying the hype, AI Safety has emerged as its counterpoint. AI Safety, when I first encountered it, brought to mind autonomous vehicle crashes, nuclear meltdowns, killer drones, and robots-gone-haywire. Nowadays, I see a different, more aggressive intention as AI Safety has come to dominate the public agenda around AI, beyond the purely technical and economic.
Keywords
Art
Related papers
LEARNING
📊 8,465 cites
The Organization of Behavior
D. O. Hebb
2005
LEARNING
📊 7,678 cites
Fractional Brownian Motions, Fractional Noises and Applications
Benoît B. Mandelbrot, John W. Van Ness
1968
LEARNING
Open access📊 7,484 cites
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi, Jinglan Zhang, Amjad J. Humaidi +7 more
2021
LEARNING
📊 4,608 cites
A guide to deep learning in healthcare
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar +7 more
2018