Communications of the ACM
Can Generative AI Bots Be Trusted?
It will be a long road to learning how to use generative AI wisely.
From Communications of the ACM
The Parchment Path?
Is there ever a time when learning is not of value—for its own sake?
From Communications of the ACM
Conjoined Twins: Artificial Intelligence and the Invention of Computer Science
How artificial intelligence and computer science grew up together.
From Communications of the ACM
Trust Is Not Enough: Accuracy, Error, Randomness, and Accountability in an Algorithmic Society
Searching for improved algorithmic accountability.
From Communications of the ACM
Decentraland: The Alleged Decentralization of Blockchain Applications
Breaking down the blockchain.
From ACM Opinion
Vint Cerf on 3 Mistakes He Made in TCP/IP
The co-creator of the Internet’s protocols admits his crystal ball had a few cracks.
From Communications of the ACM
Updates, Threats, and Risk Management
Revisiting a recent column considering security updates.
From Communications of the ACM
Ethics as a Participatory and Iterative Process
Facilitating ethical reflection, inquiry, and deliberation.
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 Communications of the ACM
Cyber Efficiency and Cyber Resilience
Complementary objectives competing for the same resources.
From Communications of the ACM
Where Is the Research on Cryptographic Transition and Agility?
Gaps facing the industry as quantum safe algorithms move closer to standardization.
From Communications of the ACM
Contracting for Artificial Intelligence
Considering the promises and perils of contracting for the use of artificial intelligence tools and data.
From Communications of the ACM
Metrics for Success: Why and How to Evaluate Privacy Choice Usability
Assessing the usability of choice and consent mechanisms.
From Communications of the ACM
A Map for Innovation
Innovation is less elusive with the right navigational map.
From Communications of the ACM
The Premature Obituary of Programming
Why deep learning will not replace programming.
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