I couldn’t resist dipping into this free course from the Google News Initiative, and what I found surprised me: eight short lessons that are available as PDFs.
The good news: The lessons are journalism-focused, and they provide a painless introduction to the subject. The bad news: This is not really a course or a class at all — although there is one quiz at the end. And you can get a certificate, for what it’s worth.
There’s a lot here that many journalists might not be aware of, and that’s a plus. You get a brief, clear description of Reuters’ News Tracer and Lynx Insight tools, both used in-house to help journalists discover new stories using social media or other data (Lesson 1). A report I recall hearing about — how automated real-estate stories brought significant new subscription revenue to a Swedish news publisher — is included in a quick summary of “robot reporting” (also Lesson 1).
Lesson 2 helpfully explains what machine learning is without getting into technical operations of the systems that do the “learning.” They don’t get into what training a model entails, but they make clear that once the model exists, it is used to make predictions. The predictions are not like what some tarot-card reader tells you but rather probability-based results that the model is able to produce, based on its prior training.
Noting that machine learning is a subset of the wider field called artificial intelligence is, of course, accurate. What is inaccurate is the definition “specific applications that use data to train a model to perform a given task independently and learn from experience.” They left out Q-learning, a type of reinforcement learning (a subset of machine learning), which does not use a model. It’s okay that they left it out, but they shouldn’t imply that all machine learning requires a trained model.
The explosion of machine learning and AI in the past 10 years is explained nicely and concisely in Lesson 2. The lesson also touches on misconceptions and confusion surrounding AI:
“The lack of an officially agreed definition, the legacy of science-fiction, and a general low level of literacy on AI-related topics are all contributing factors.”
—Lesson 2, Is Machine Learning the same thing as AI?
I’ll be looking at Lessons 3 and 4 tomorrow.
AI in Media and Society by Mindy McAdams is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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