Communications of the ACM
Refine your search:
From BLOG@CACM
Four Conversations About Human-Centric AI
I discuss the different conversations, their limits, and what we really need to be talking about.
From BLOG@CACM
Opportunities of Data Science Education
Considering the six new and exciting opportunities that data science presents.
From BLOG@CACM
Which Were the Most Influential Early Computers?
Considering early machines that had the greatest influence on the development of program-controlled computers.
From BLOG@CACM
Mitigating the Base-Rate Neglect Cognitive Bias in Data Science Education
How can machine learning educators help learners cope with the base rate neglect cognitive bias?
From BLOG@CACM
Was Ada Lovelace Actually the First Programmer?
Historical arguments for and against.
From BLOG@CACM
Communing on Computing
Conferences can renew our professional commitment and inspire thought on problems we face.
From BLOG@CACM
The Base-Rate Neglect Cognitive Bias in Data Science
Using Bayes' Theorem, the correct answer to both the medical diagnosis problem and to the lion classification question, can be calculated.
From BLOG@CACM
AI as (an Ersatz) Natural Science?
The emergence of large learned models is changing the nature of artificial intelligence research in fundamental ways.
From BLOG@CACM
Machine Learning: Out! Data Science: In!
We propose to stop teaching machine learning courses to populations whose core discipline is neither computer science nor mathematics and statistics.
From BLOG@CACM
Rethinking the CS Curriculum
I have noticed that there is a growing trend to dumb down the CS curriculum by removing mathematical topics.
From BLOG@CACM
Programming is For More than Engineering; Computer Science is About More than Building Things
Programming should be part of computing education curriculum, and take into account all the ways students will use computing.
From BLOG@CACM
Validity and Reliability in Data Science: An Interdisciplinary Perspective
We examine the essence of the components of data science, as well as their interrelations, from the educational perspective.
From BLOG@CACM
Biases in Author Recognition
When reading papers, we make simplifications and have assumptions about author roles and relative contributions.
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
Your Job Can Be Done Better By My Algorithm
In our rarefied world of university teaching and learning, which jobs can be replaced by algorithms?
From BLOG@CACM
Data Anonymization Using the Random Sum Method
The purpose of this blog post is to present an anonymization method that can be applied to the digital attributes of personal data.
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