ACM Queue

Escaping the Quicksand: A Call to Arms

Computing needs better engineering feedback loops to build secure systems

AI test-and-debug development is increasing our technical debt, and vulnerability detection is making it ever easier to exploit it

queue.acm.org/doi/10.1145/38…

Kode Vicious

For I have no mouth…
… and I must scream.

Whatever hopes I had at the start of the process have been dashed. Either our software is completely broken, or no one in the room really understands the computer. Perhaps both.

queue.acm.org/doi/10.1145/38…

AI Coding Benchmarks Need Composition Cards:
Why the same model scores 70 percent and 6 percent, and what every benchmark should ship

The audit is cheap for public benchmarks and impossible for hidden ones without disclosure.

queue.acm.org/doi/10.1145/38…

How Does Generative AI Change the Algorithmic Fairness Problem?

In AI fairness, one size never fits all. With generative AI, one size may fit none, demanding fundamentally new approaches to evaluate and mitigate bias.

queue.acm.org/doi/10.1145/38…

Failure Is a Feature: Engineering Fault-Tolerant AI Agents

Treating LLM agents as distributed systems and borrowing 40 years of reliability engineering to make them work

Reliability, not capability, is the binding constraint on agents in production.

queue.acm.org/doi/10.1145/38…