Communications of the ACM
Innovation Is Overrated: A Provocation
Digital innovation is not working in the interest of the whole of society. It is time to radically rethink its purpose without…
From ACM Opinion
The Researcher Who Would Teach Machines to Be Fair
Princeton computer scientist Arvind Narayanan uses quantitative methods to expose and correct the misuse of quantitative methods.
From ACM Opinion
Machines Learn Better if We Teach Them the Basics
A wave of research improves reinforcement learning algorithms by pre-training them as if they were human.
From ACM Opinion
The Computer Scientist Who Is Boosting Privacy on the Internet
Harry Halpin has helped create a new kind of network that might enable more private Internet conversations.
From ACM Opinion
The AI Researcher Giving Her Field Its Bitter Medicine
Anima Anandkumar wants computer scientists to move beyond the matrix, among other challenges.
From ACM Opinion
The Computer Scientist Challenging AI to Learn Better
Christopher Kanan is building algorithms that can continuously learn over time—the way people do.
From ACM Opinion
How to Write Software with Mathematical Perfection
Leslie Lamport revolutionized how computers talk to each other, and now he's working on how engineers talk to their machines.
From ACM Opinion
Anne Carpenter: Her Machine Learning Tools Pull Insights from Cell Images
Computational biologist brings the power of machine learning to researchers seeking answers in mountains of cell images
From ACM Opinion
What Makes Quantum Computing So Hard to Explain?
To understand what quantum computers can do—and what they can’t—avoid falling for overly simple explanations.
From ACM Opinion
Charlie Marcus Knows That Quantum Facts Aren't Complicated
The secret to making a qubit for future quantum computers might depend on knowing how to tie knots in unusual materials, argues quantum physicist Charlie Marcus...
From ACM Opinion
Professor Advocates Taking AI Research Back to Its Roots
To build a general artificial intelligence, we may need to know more about our own minds, argues computer scientist Melanie Mitchell.
From ACM Opinion
Prepping for a Flood of Heavenly Bodies
This is a story of getting the good out of the bad, said Mario Jurić.
From ACM Opinion
To Build Truly Intelligent Machines, Teach Them Cause and Effect
Artificial intelligence owes a lot of its smarts to Judea Pearl.
From ACM Opinion
A Revealer of Secrets in the Data of Life and the niverse
In statistics, abstract math meets real life. To find meaning in unruly sets of raw numbers, statisticians like Donald Richards first look for associations: statistical...
From ACM Opinion
New Brain Maps With nmatched Detail May Change Neuroscience
Sitting at the desk in his lower campus office at Cold Spring Harbor Laboratory, the neuroscientist Tony Zador turned his computer monitor toward me to show off...
From ACM Opinion
Wanted: More Data, the Dirtier the Better
To distill a clear message from growing piles of unruly genomics data, researchers often turn to meta-analysis—a tried-and-true statistical procedure for combining...
From ACM Opinion
Is Alphago Really Such a Big Deal?
In 1997, IBM's Deep Blue system defeated the world chess champion, Garry Kasparov.
From ACM Opinion
Searching For the Algorithms nderlying Life
To the computer scientist Leslie Valiant, "machine learning" is redundant.
From ACM Opinion
Big Data's Mathematical Mysteries
At a dinner I attended some years ago, the distinguished differential geometer Eugenio Calabi volunteered to me his tongue-in-cheek distinction between pure and...
From ACM Opinion
The Physical Origin of niversal Computing
Imagine you're shopping for a new car, and the salesperson says, "Did you know, this car doesn't just drive on the road."
From ACM Opinion
Decoding the Remarkable Algorithms of Ants
Ants are capable of remarkable feats of coordination.12