Communications of the ACM
DEPARTMENT: From the President
DEPARTMENT: Cerf's Up
DEPARTMENT: Letters to the Editor
DEPARTMENT: BLOG@CACM
COLUMN: News
SECTION: Education
COLUMN: Kode Vicious
COLUMN: Computing Ethics
COLUMN: Viewpoint
SECTION: Practice
SECTION: Contributed Articles
SECTION: Review Articles
SECTION: Research Highlights
COLUMN: Last Byte
To the Members of ACM
This is an update on the efforts of the ACM Executive Committee and Council to draft a longer-term strategic plan for our organization.DEPARTMENT: Cerf's Up
On QR Codes and Safety
The QR code, a convenient mechanism for delivering digital information to a reader, does not come with any human-readable way to ascertain safety. You have no way to tell whether it is potentially malicious.DEPARTMENT: Letters to the Editor
Neighborhood Watch
Vinton G. Cerf wonders "whether there is any possibility of establishing 'watcher networks'" in his October 2022 Communications "Cerf's Up" column. Philip K. Dick describes this problem in his story The Minority Report.DEPARTMENT: BLOG@CACM
What is Data Science?
Koby Mike and Orit Hazzan consider why multiple definitions are needed to pin down data science.COLUMN: News
Post-Quantum Cryptography
Cryptographers seek algorithms quantum computers cannot break.Computational Linguistics Finds Its Voice
Advances in artificial intelligence permit computers to converse with humans in seemingly realistic ways.Can AI Demonstrate Creativity?
When fed a sufficient amount of training data, artificial intelligence techniques can be used to generate new ideas in several different ways. Is that creativity?SECTION: Education
Four Ways to Add Active Learning to Computing Courses
How active-learning techniques can benefit students in computing courses.COLUMN: Kode Vicious
The Elephant in the Room
It is time to get the POSIX elephant off our necks.COLUMN: Computing Ethics
Ethical AI is Not about AI
The equation Ethics + AI = Ethical AI is questionable.COLUMN: Viewpoint
Software Engineering of Machine Learning Systems
Seeking to make machine learning more dependable.Building Machine Learning Models Like Open Source Software
Proposing a community-based system for model development.The Premature Obituary of Programming
Why deep learning will not replace programming.An Analysis of Black Faculty in CS Research Departments
Exploring Black faculty at computer science research departments where Ph.D. programs exist.SECTION: Practice
From Zero to 100
Demystifying zero trust and its implications on enterprise people, process, and technology.The Arrival of Zero Trust: What Does it Mean?
A discussion of zero-trust enterprise efforts in cybersecurity.SECTION: Contributed Articles
Extracting the Essential Simplicity of the Internet
Looking past inessential complexities to explain the Internet's simple yet daring design.(Re)Use of Research Results (Is Rampant)
Prior pessimism about reuse in software engineering research may have been a result of using the wrong methods to measure the wrong things.HPC Forecast: Cloudy and Uncertain
An examination of how the technology landscape has changed and possible future directions for HPC operations and innovation.SECTION: Review Articles
The Lean Data Scientist: Recent Advances Toward Overcoming the Data Bottleneck
A taxonomy of the methods used to obtain quality datasets enhances existing resources.SECTION: Research Highlights
Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning
"Proving Data-Poisoning Robustness in Decision Trees," by Samuel Drews et al., addresses the challenge of processing an intractably large set of trained models when enumeration is infeasible in a clean, beautiful, and elegant …Proving Data-Poisoning Robustness in Decision Trees
We present a sound verification technique based on abstract interpretation and implement it in a tool called Antidote, which abstractly trains decision trees for an intractably large space of possible poisoned datasets.COLUMN: Last Byte
