{"id":1271,"date":"2022-10-02T17:16:34","date_gmt":"2022-10-02T21:16:34","guid":{"rendered":"https:\/\/www.macloo.com\/ai\/?p=1271"},"modified":"2022-10-02T17:16:34","modified_gmt":"2022-10-02T21:16:34","slug":"what-journalists-get-wrong-about-ai","status":"publish","type":"post","link":"https:\/\/www.macloo.com\/ai\/2022\/10\/02\/what-journalists-get-wrong-about-ai\/","title":{"rendered":"What journalists get wrong about AI"},"content":{"rendered":"\n

Sayash Kapoor and Arvind Narayanan are writing a book about AI. The title is AI Snake Oil<\/em>. They’ve been writing a Substack newsletter about it, and on Sept. 30 they published a post titled Eighteen pitfalls to beware of in AI journalism<\/a>. Narayanan is a computer science professor at Princeton, and Kapoor is a former software engineer at Facebook and current Ph.D. student at Princeton.<\/p>\n\n\n\n

“There is seldom enough space in a news article to explain how performance numbers like accuracy are calculated for a given application or what they represent. Including numbers like \u201890% accuracy\u2019 in the body of the article without specifying how these numbers are calculated can misinform readers …”<\/p>\u2014Kapoor and Narayanan<\/cite><\/blockquote>\n\n\n\n

They made a checklist, in PDF format<\/a>, to accompany the post. The list is based on their analysis of more than 50 articles from five major publications: The New York Times,<\/em> CNN, the Financial Times,<\/em> TechCrunch, and VentureBeat. In the Substack post, they linked to three annotated examples<\/strong> \u2014 one each from The New York Times,<\/em> CNN, and the Financial Times<\/em>. The annotated articles are quite interesting and could form a base for great discussions in a journalism class. (Note, in the checklist, the authors over-rely on one<\/em> article from The New York Times<\/em> for examples.)<\/p>\n\n\n\n

Their goals: The public should be able to detect hype about AI when it appears in the media, and their list of pitfalls could “help journalists avoid them.”<\/p>\n\n\n\n

“News articles often cite academic studies to substantiate their claims. Unfortunately, there is often a gap between the claims made based on an academic study and what the study reports.”<\/p>\u2014Kapoor and Narayanan<\/cite><\/blockquote>\n\n\n\n

Kapoor and Narayanan have been paying attention to the conversations around journalism and AI. One example is their link to How to report effectively on artificial intelligence<\/a>, a post published in 2021 by the JournalismAI<\/a> group at the London School of Economics and Political Science.<\/p>\n\n\n\n

I was pleased to read this post because it neatly categorizes and defines many things that have been bothering me in news coverage of AI breakthroughs, products, and even ethical concerns. <\/p>\n\n\n\n