Communications of the ACM
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From BLOG@CACM
Ethics and Equity in AI for Collaborative Learning
In designing collaborative learning, design AI features using realistic examples of students’ learning; support teachers' awareness; develop students' sense of...
From BLOG@CACM
Stop Judging AI Using Human Exams
Computer scientists should inform the public that human tests are not a valid way to judge the quality of an AI model, nor a good way to compare AI models to human...
From BLOG@CACM
ChatGPT for Provost!
Three to five years from now, we won’t be talking about what ChatGPT can or can’t do, but we could be talking about how ChatGPT brought us all together, and the...
From BLOG@CACM
The ChatAlgebra Educational Revolution
We need a ChatAlgebra revolution to reduce the gatekeeping role of the traditional Algebra course, to ameliorate the student suffering associated with the traditional...
From BLOG@CACM
How Scripting Misses the Mark
Scripting languages promise easy automation but prove difficult to learn. Let's stop focusing on simplified syntax and instead focus on understandability and learnability...
From BLOG@CACM
R&D or r&d: What's the Difference?
Research produces generalized knowledge; Development produces generalized functionality. Not all efforts that use research skills or that use development skills...
From BLOG@CACM
AI or Intelligence Augmentation for Education?
Applications of artificial intelligence to education are spreading and intensifying, but we have the acronym backwards. Building ethical, equitable applications...
From BLOG@CACM
Why Focus on Technologies for Human Learning?
By choosing human learning as a topic area, computer scientists can contribute to major societal challenges, win grants in additional programs, and tackle new computer...
From BLOG@CACM