Assessment in Computer Science Education in the GenAI Era
Exploring the need to rethink assessment in computer science education in the Generative AI era.
Artificial Intelligence and Machine Learning
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We’re Reaping Just What We Sowed
The idea of computing using an abstract machine model that can grow during the execution of an algorithm leads to a theory of computation that is quite rich.
Artificial Intelligence Then and Now
Branding large language models as artificial intelligence primes customers to believe they have capabilities they lack.
Generative AI: A Master List Maker
There are surprising uses of Generative AI that aren’t what people have generally been thinking.
LLMs could give robots the ability to process open-ended, natural language commands to solve complex tasks.
Agricultural AI is trained to provide farmers with insight on when to plant and irrigate, and to warn of impending infestations and natural disasters such as droughts and floods.
Where Art and Tech Click: Algorithmic Photography
An algorithmic still image presents motion as colorful, impressionistic swirls against a static setting such as a sky, building, or cityscape.
Professionals must invest in continuous education to understand AI's potential, avoid pitfalls, and harness its benefits.
Technical Perspective: Can AI Keep Accessible Communication in the Picture?
Recent research explores how AI can use photos to support communication, especially for people with communication impairments.
The LiteLoad project is working to quantify the impact of poor connectivity in rural areas near the Great Smoky Mountains National Park, in Tennessee, as a testing ground.
Strengthening Security Throughout the ML/AI Lifecycle
Automation, audits, and access control are some of the ways to enhance security in ML systems.
Access to your production environment must be guarded jealously, even among your own team of developers.
Computation and Deliberation: The Ghost in the Habermas Machine
People interacting only with the Habermas Machine to develop policy neglect the relational and interpersonal dynamics crucial to democratic deliberation.
AI-Driven Code Review: Enhancing Developer Productivity and Code Quality
AI-driven code review tools use deep learning and natural language processing to understand coding patterns and offer suggestions.
Identifying Political Bias in AI
Findings suggest that no dataset is completely objective, even those carefully curated to be used as objectivity benchmarks.
Causal Inference Makes Sense of AI
Causal inference makes AI systems smarter by injecting real-world logic and cause-and-effect dynamics into decision-making.
Advanced Machine Learning Algorithms for HR Analytics
ML has revolutionized traditional HR processes through sophisticated classification algorithms that ensure precise, data-driven decision-making.
On Program Synthesis and Large Language Models
It is unreasonable to expect the generational powers of ChatGPT and similar software to provide a general tool for program synthesis.
Finding Roles in a Team with Generative AI
Generative AI can help an organization fill roles that are responsible for different parts of a project.
Controlling AI’s Growing Energy Needs
Lower-energy options are being sought to reduce the energy footprint of AI training.
The EU AI Act and the Wager on Trustworthy AI
The EU AI Act serves as a reminder for developers to always prioritize the well being of individuals and society as a whole.
Matarić would like machines to provide social, emotional, and psychological support to people, which makes accessibility a large, unsolved problem.
Shape the Future of Computing
ACM encourages its members to take a direct hand in shaping the future of the association. There are more ways than ever to get involved.
Get InvolvedCommunications of the ACM (CACM) is now a fully Open Access publication.
By opening CACM to the world, we hope to increase engagement among the broader computer science community and encourage non-members to discover the rich resources ACM has to offer.
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