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 Communications of the ACM
Building Machine Learning Models Like Open Source Software
Proposing a community-based system for model development.
From Communications of the ACM
Software Engineering of Machine Learning Systems
Seeking to make machine learning more dependable.
From Communications of the ACM
Ethical AI is Not about AI
The equation Ethics + AI = Ethical AI is questionable.
From Communications of the ACM
The Elephant in the Room
It is time to get the POSIX elephant off our necks.
From ACM Opinion
What's Next for Quantum Computing?
Companies are moving away from setting qubit records in favor of practical hardware and long-term goals.
From Communications of the ACM
The AI Ethicist's Dirty Hands Problem
Attempting to balance sometimes-conflicting interests.
From Communications of the ACM
The End of Programming
The end of classical computer science is coming, and most of us are dinosaurs waiting for the meteor to hit.
From Communications of the ACM
Are Software Updates Useless against Advanced Persistent Threats?
Considering the conundrum of software updates.
From Communications of the ACM
From Quantum Computing to Quantum Communications
Attempting to disentangle mechanical principles.
From ACM Opinion
The False Promise of America's CHIPS Act
It is doubtful that large subsidies and government management will keep U.S. chip makers on top.
From Communications of the ACM
Building a New Economy: Data, AI, and Web3
How distributed technologies could return more control to users.
From Communications of the ACM
Can Universities Combat the 'Wrong Kind of AI'?
Seeking an artificial intelligence reset.
From Communications of the ACM
The Four Horsemen of an Ailing Software Project
Don't let the pale rider catch you with an exception.
From Communications of the ACM
The Context Problem in Artificial Intelligence
The artificial intelligence design challenge of teaming humans and machines is difficult because machines cannot read the context of use.
From ACM Opinion
Scientists Increasingly Cannot Explain How AI Works
AI researchers are warning developers to focus more on how and why a system produces certain results than the fact that the system can accurately and rapidly produce...
From ACM Opinion
AI in Medicine Is Overhyped
AI models for healthcare that predict disease are not as accurate as reports might suggest.
From ACM Opinion
AI Model Transferability in Healthcare: A Sociotechnical Perspective
To realize the promised benefits of applying AI and ML models at scale, a roadmap of the challenges and potential solutions to sociotechnical transferability is...
From Communications of the ACM
Rethinking Silicon Valley: Stewart Brand's Lost Journal
Discovering a hidden chapter in computing history.
From Communications of the ACM