DEPARTMENT: Cerf's up
Computer programs are being used to emulate humans to fool less-sophisticated programs into treating computer-generated actions as if they originate from a human. This is an important practical problem.
The publishing landscape is changing, and ACM with it. We take this opportunity to describe what ACM thinks about recent trends, recent changes, and the future.
DEPARTMENT: Vardi's insights
We cannot understand the current gender disparity in computing without understanding the history of women in computing. How did we lose the women in computing? They did not just leave; they were pushed out.
DEPARTMENT: Letters to the editor
Recent editorial policy seems to have let ACM morph into what I would call the left-leaning ACM.
DEPARTMENT: ACM's election
Meet the candidates who introduce their plans—and stands—for the Association.
DEPARTMENT: [email protected]
Edwin Torres considers the enduring value of code comments, while Walid Saba wonders if we have overreacted to the knowledge acquisition bottleneck.
Scientists are using DNA and RNA to build the world's tiniest robots and computing devices.
Functional programming languages automate many of the details underlying specific operations.
Researchers are exploring ways to put medical data to greater use while better protecting privacy.
COLUMN: Law and technology
Yes, with one big exception.
COLUMN: Privacy and security
Proposing a stronger foundation for an engineering discipline to support the design of secure systems.
Moving beyond self-selected computer science education in Switzerland.
Addressing the root causes of rapidly increasing software complexity.
Some thoughts on the way forward.
Expert-curated guides to the best of CS research.
Automated canarying quickens development, improves production safety, and helps prevent outages.
Praise matters just as much as money.
SECTION: Contributed articles
A teacher and students coding together make explicit the unwritten rules of programming.
The U.S. State Department's Internet Freedom agenda is being adapted to help them communicate without DNS and IP address filtering.
The data comes from multiple optimal sources in parallel, helping reduce addressing and data-acquisition latency.
SECTION: Review articles
Tracing 20 years of progress in making machines hear our emotions based on speech signal properties.
SECTION: Research highlights
"Never-Ending Learning" is the latest and one of the most compelling incarnations of Tom Mitchell and his collaborators' research investigating how to broaden the machine learning field.
In this paper we define more precisely the never-ending learning paradigm for machine learning, and present one case study: the Never-Ending Language Learner (NELL), which achieves a number of the desired properties of a never …
COLUMN: Last byte
When all online news and comment can be digitally manipulated, some might recall a more trustworthy way to spread the word.