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The Audio Long Read

Becoming a chatbot: my life as a real estate AI’s human backup

The Audio Long Read

The Guardian

Society & Culture

4.32.4K Ratings

🗓️ 13 January 2023

⏱️ 41 minutes

🧾️ Download transcript

Summary

For one weird year, I was the human who stepped in to make sure a property chatbot didn’t blow its cover – I was a person pretending to be a computer pretending to be a person. Help support our independent journalism at theguardian.com/longreadpod

Transcript

Click on a timestamp to play from that location

0:00.0

This is the Guardian.

0:30.0

Welcome to the Guardian Longread, showcasing the best long-form journalism covering culture, politics and new thinking.

0:54.0

For the text version of this and all our long-weeds, go to the Guardian.com for a slash long-weed.

1:02.0

Becoming a chatbot, my life as a real estate AI's human backup. By Laura Preston.

1:12.0

The recruiter was a chipper woman with a master's degree in English. Previously, she had worked as an independent bookseller.

1:30.0

Your experience as an English grad student is ideal for this role. She told me. The position was at a company that made artificial intelligence for real estate.

1:44.0

They developed a product called Brenda, a conversational AI that could answer questions about apartment listings.

1:52.0

Brenda had been acquired by a larger company that made software for property managers. And now thousands of properties across the country had put her to work.

2:04.0

Brenda, the recruiter told me, was a sophisticated conversationalist, so fluent that most people who encountered her took her to be human.

2:18.0

But like all conversational AI's, she had some shortcomings. She struggled with idioms and didn't fare well with questions beyond the scope of real estate.

2:30.0

To compensate for these flaws, the company was recruiting a team of employees they called the operators.

2:36.0

The operators kept vigil over Brenda 24 hours a day. When Brenda went off script, an operator took over an emulated Brenda's voice.

2:48.0

Ideally, the customer on the other end would not realize the conversation had changed hands, or that they had even been chatting with a bot in the first place.

2:58.0

Because Brenda used machine learning to improve her responses, she would pick up on the operator's language patterns and gradually adopt them as her own.

3:08.0

It was the spring of 2019. My time as a creative writing student had just come to an end, as had my funding, and the rent was due. I needed a job.

3:20.0

I sent the recruiter my CV. Several phone interviews later, I was signing up for training slots and watching a 45 minute PowerPoint presentation on Fair Housing Law.

3:34.0

I did a little math. An operator made $25 an hour and worked between 15 and 30 hours a week, depending on how lucky they were in the weekly shift lottery.

3:44.0

It wouldn't be enough to cover my rent, but I had no other leads. I packed my things and moved back home to live with my parents in New Jersey.

3:54.0

I was one of about 60 operators. Most of us were poets and writers with MFA's, but there were also PhDs in performance studies and comparative literature, as well as a number of opera singers.

4:09.0

Another demographic evidently well suited for chatbot impersonation, or, I suppose, for impersonating a chatbot that's impersonating a person.

4:20.0

We all convened on a Slack channel. Everyone was aggressively good-natured with leftist politics and pronouns in their display names.

4:31.0

When we weren't talking about Brenda, we were swapping syllabi, soliciting tattoo advice, and distributing e-fliers to our sound and movement workshops.

...

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