acm-header
Sign In

Communications of the ACM

BLOG@CACM


bg-corner

Why Is It Hard to Define Data Science?
From BLOG@CACM

Why Is It Hard to Define Data Science?

Data science can be described as a science, as a research paradigm, as a research method, as a discipline, as a workflow, and as a profession.

The Process-Object Duality in Computer Science and Data Science Education
From BLOG@CACM

The Process-Object Duality in Computer Science and Data Science Education

The process-object duality has several educational implications for the design of teaching and learning processes.

Three Risks Facing Higher Education
From BLOG@CACM

Three Risks Facing Higher Education

The implications of COVID-19 for risk management in higher education.

Reflections on the AI Bill of Rights Blueprint
From BLOG@CACM

Reflections on the AI Bill of Rights Blueprint

The White House Office of Science and Technology Policy has released a "Blueprint for an AI Bill of Rights." I reflect on this milestone document in the context...

Four Conversations About Human-Centric AI
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.

Not Your Grandmother's Textbook Exercise
From BLOG@CACM

Not Your Grandmother's Textbook Exercise

Sarcasm, where you least expected it.

Opportunities of Data Science Education
From BLOG@CACM

Opportunities of Data Science Education

Considering the six new and exciting opportunities that data science presents.

Which Were the Most Influential Early Computers?
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.

The Legacy of Barry Boehm
From BLOG@CACM

The Legacy of Barry Boehm

One of the founders of software engineering as we know it.

Mitigating the Base-Rate Neglect Cognitive Bias in Data Science Education
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?

Was Ada Lovelace Actually the First Programmer?
From BLOG@CACM

Was Ada Lovelace Actually the First Programmer?

Historical arguments for and against.

Communing on Computing
From BLOG@CACM

Communing on Computing

 Conferences can renew our professional commitment and inspire thought on problems we face.

The Base-Rate Neglect Cognitive Bias in Data Science
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.

AI as (an Ersatz) Natural Science?
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.

Machine Learning: Out! Data Science: In!
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.

Rethinking the CS Curriculum
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.

Programming is For More than Engineering; Computer Science is About More than Building Things
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.

Validity and Reliability in Data Science: An Interdisciplinary Perspective
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.

Biases in Author Recognition
From BLOG@CACM

Biases in Author Recognition

When reading papers, we make simplifications and have assumptions about author roles and relative contributions.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account