Communications of the ACM
Dilemma of the Artificial Intelligence Regulatory Landscape
Navigating the complex and varying AI regulatory landscape.
From Communications of the ACM
Data Platforms and Network Effects
How data-network effects create opportunities and inflate expectations.
From ACM Opinion
AI Needs Pragmatists and Blue-Sky Visionaries
For humanity's brightest future, the blue-sky, lofty thinkers in AI need the help of the muddy-boots pragmatists.
From ACM Opinion
Designing to Avoid Worst-Case Outcomes
Interaction designer Jonathan Shariat discusses harmful software design.
From ACM Opinion
Linguistics and the Development of NLP
An interview with Christopher Manning, director of the Stanford University AI Lab and an associate director of Stanford's Human-Centered Artificial Intelligence...
From ACM Opinion
How AI Could Accidentally Extinguish Humankind
Humanity is not prepared for artificial superintelligence right now.
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
Blowing Up the Internet...to Protect Kids Online
Framed as a bill to protect kids online, the California Age Appropriate Design Code Act would radically reshape the Internet—and harm both kids and adults.
From ACM Opinion
Supercomputer Emulator: AI's New Role in Science
Chris Bishop, Microsoft's head of AI4Science, sees machine learning partially supplanting simulation.
From ACM Opinion
'The New Generation of Computer Scientist Wants to Benefit Society'
Professor Jim Kurose discusses the type of science computing researchers are focusing on and the future of the field.
From ACM News
We Need to Talk About How Good AI Is Getting
We are in a golden age of progress in artificial intelligence, and it is time to start taking its potential and risks seriously.
From ACM Opinion
Software Can Do Better than 'Male,' 'Female,' and 'Other'
Providing more-expansive gender options is not a difficult coding problem.
From ACM Opinion
Interpretable Machine Learning
A conversation with Been Kim, staff research scientist at Google Brain.
From Communications of the ACM
On the Model of Computation: Counterpoint: Parallel Programming Wall and Multicore Software Spiral: Denial Hence Crisis
Parallel programming wall and multicore software spiral: Denial hence crisis.
From Communications of the ACM
On the Model of Computation: Point: We Must Extend Our Model of Computation to Account for Cost and Location
We must extend our model of computation to account for cost and location.
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
Can Neural Networks Learn Better than Human Neurons?
When AI programmers stop trying to copy the human neuron, neural networks make much better progress.
From ACM Opinion
Meta's Message Encryption Was Built to Fail
Chat between a teen and her mom about an alleged abortion helped police build their case.
From ACM Opinion
How to Solve AI's 'Common-Sense' Problem
AI systems without common sense will make mistakes when they reach the limits of where they've been trained.
From ACM Opinion