“Let me hazard a guess that you think a real person has written what you’re reading. Maybe you’re right. Maybe not…Because, these days, a shocking amount of what we’re reading is created not by humans, but by computer algorithms. We probably should have suspected that the information assaulting us 24/7 couldn’t all have been created by people bent over their laptops.” S. Podolny The NYT
ESL Voices Lesson Plan for this post with Answer Key
Excerpt: If an Algorithm Wrote This, How Would You Even Know? By Shelley Podolny NYT
“It’s understandable. The multitude of digital avenues now available to us demand content with an appetite that human effort can no longer satisfy. This demand, paired with ever more sophisticated technology, is spawning an industry of automated narrative generation. Companies in this business aim to relieve humans from the burden of the writing process by using algorithms and natural language generators to create written content. Feed their platforms some data — financial earnings statistics, let’s say — and poof! In seconds, out comes a narrative that tells whatever story needs to be told. These robo-writers don’t just regurgitate data, either; they create human-sounding stories in whatever voice — from staid to sassy — befits the intended audience. Or different audiences. They’re that smart. And when you read the output, you’d never guess the writer doesn’t have a heartbeat.
Consider the opening sentences of these two sports pieces:
“Things looked bleak for the Angels when they trailed by two runs in the ninth inning, but Los Angeles recovered thanks to a key single from Vladimir Guerrero to pull out a 7-6 victory over the Boston Red Sox at Fenway Park on Sunday.”
“The University of Michigan baseball team used a four-run fifth inning to salvage the final game in its three-game weekend series with Iowa, winning 7-5 on Saturday afternoon (April 24) at the Wilpon Baseball Complex, home of historic Ray Fisher Stadium.”
If you can’t tell which was written by a human, you’re not alone. According to a study conducted by Christer Clerwall of Karlstad University in Sweden and published in Journalism Practice, when presented with sports stories not unlike these, study respondents couldn’t tell the difference. (Machine first, human second, in our example, by the way.)
Set loose on the mother lode — especially stats-rich domains like finance, sports and merchandising — the new software platforms apply advanced metrics to identify patterns, trends and data anomalies. They then rapidly craft the explanatory narrative, stepping in as robo-journalists to replace humans.”
Did a Human or a Computer Write This?
Can you tell the difference? Take this interactive quiz from the New York Times
Level: Intermediate – Advanced
Language Skills: Reading, writing, and speaking. Vocabulary and grammar activities are included.
Time: Approximately 2 hours.
Materials: Student handout (from this lesson) access to news article, and video clip.
Objective: Students will read and discuss the article with a focus on improving reading comprehension and learning new vocabulary. At the end of the lesson students will express their personal views on the topic through group work and writing.
I. Pre-Reading Activity
Stimulating background knowledge: Brainstorming
Directions: Place students in groups, ask students to think about what they already know about the topic. Next, have students look at the picture(s) in the text and generate ideas or words that may be connected to the article. Debrief as a class and list these ideas on the board. Students can use a brainstorming chart for assistance.
UIE brainstorming chart (sample)
II. While Reading Tasks
Directions: Students are to infer the meanings of the words in bold taken from the article. They may use a dictionary, thesaurus, and Word Chart for assistance.
- There is a multitude of digital avenues now available to us.
- This demand is spawning an industry of automated narratives.
- Companies aim to relieve humans from the burden of the writing process by using algorithms.
- These robo-writers don’t just regurgitate data.
- They create human-sounding stories in whatever voice — from staid to sassy.
- When you read the output, you’d never guess the writer doesn’t have a heartbeat.
- Software is stealthily replacing us as communicators.
- Narrative Science claims it can create “a narrative that is indistinguishable from a human-written one.
- There’s so much information to absorb every day.
Reading Comprehension:Word Recognition
Directions: Have students choose the correct word or phrase from the article. This exercise reinforces students’ attention on words that have been introduced in the reading. Have them skim the article to check their responses. Students should also find the meanings for all unknown words.
It’s understandably/understandable. Algorithms and natural/neutral language generators/generates have been around for a while, but they’re getting better and faster as the demand for them spoors/spurs investment and innovation. The sheet/sheer volume and complexity of the Big Data we generate, too much for mere/more mortals to tackle, calls for artificial rather than human/humane intelligence to derive meaning from it all.
Set loose/lose on the mother lode — especially stats-rich domains like finance, spots/sports and merchandising — the new software platforms apply/apple advanced metrics to identify patterns, trends and data anomalies. They then/than rapidly craft the explanatory narrative, stepping/steeping in as robo-journalists to replace humans.
Grammar Focus: Structure and Usage
Directions: The following groups of sentences are from the article. One of the sentences in each group contains a grammatical error. Students are to identify the sentence (1, 2, or 3 ) from each group that contains the grammatical error.
- Things looked bleak for the Angels when they trailed by two runs.
- If you can’t tell which was written on a human, you’re not alone.
- Study respondents couldn’t tell the difference.
- Algorithms have be around for a while.
- At least 90 percent of news could be algorithmically generated by the mid-2020s
- Humans can do more reporting and less data processing.
- Automated Insights states that its software created one billion stories last year.
- Books is robo-written, too.
- Our phones can speak to us (just as a human would).
III. Post Reading Tasks
Directions: Have students use the WH-question format to discuss or to write the main points from the article.
Who or What is the article about?
Where does the action/event take place?
When does the action/event take place?
Why did the action/event occur?
How did the action/event occur?
Directions: Place students in groups and have them answer the following questions. Afterwards, have the groups share their thoughts as a class. To reinforce the ideas, students can write an essay on one of the following discussion topics.
The following three statements were taken from the article. Rephrase each one, then discuss the meaning with the members of your group.
1. “But we should be forgiven a sense of unease. These software processes, which are, after all, a black box to us, might skew to some predicated norm, or contain biases that we can’t possibly discern. Not to mention that we may be missing out on the insights a curious and fertile human mind could impart when considering the same information.”
2. “Automated Insights states that its software created one billion stories last year, many with no human intervention; its home page, as well as Narrative Science’s, displays logos of customers all of us would recognize: Samsung, Comcast, The A.P., Edmunds.com and Yahoo. What are the chances that you haven’t consumed such content without realizing it?”
3. Our phones can speak to us (just as a human would). Our home appliances can take commands (just as a human would). Our cars will be able to drive themselves (just as a human would). What does human even mean?… With technology, the next evolutionary step always seems logical. That’s the danger. We rarely step back to reflect on whether, ultimately, we’re giving up more than we’re getting.”
Directions: Allow students 5 minutes to write down three new ideas they’ve learned about robo-journalists from the reading, two things they did not understand in the reading, and one thing they would like to know that the article did not mention. Review the responses as a class.