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THE JOURNAL.

The most important stories, explained through the lens of business. A podcast
about money, business and power. Hosted by Kate Linebaugh and Ryan Knutson, with
Jessica Mendoza. The Journal is a co-production from Spotify and The Wall Street
Journal.



TUESDAY, JULY 11, 2023

7/11/2023 4:30:00 PM
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THE HIDDEN WORKFORCE THAT HELPED FILTER VIOLENCE AND ABUSE OUT OF CHATGPT

ChatGPT is one of the most successful tech products ever launched. And crucial
to that success is a group of largely unknown data workers in Kenya. By
reviewing disturbing, grotesque content, often for wages of just two to three
dollars an hour, they helped make the viral chatbot safe. WSJ’s Karen Hao
traveled to Kenya to meet those workers and hear about what the job cost them. 




Further Reading:

- What Is ChatGPT? What to Know About the AI Chatbot 

- The Contradictions of Sam Altman, AI Crusader 




Further Listening:

- The Company Behind ChatGPT 





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FULL TRANSCRIPT

This transcript was prepared by a transcription service. This version may not be
in its final form and may be updated.

Kate: Hey, it's Kate. Today our producer Annie Minoff is going to bring you a
story. It's about a little known part of the AI workforce, the people whose job
it was to help filter out references to violence and sexual abuse on what would
become ChatGPT. Here's Annie.

Annie Minoff: My colleague Karen Hao covers artificial intelligence. And earlier
this year she found herself doing an interview in a kind of unusual place.

Karen Hao: We're currently walking through, what is this? A field? Is this
vegetables that people are growing?

Annie Minoff: Karen was in a vegetable patch on the outskirts of Nairobi, Kenya.

Karen Hao: So I was there to meet this worker named Alex, and we had originally
planned to meet in one of his friend's apartments, but there was construction
work happening, so we were looking for another place to record.

Annie Minoff: That's why they ended up in the veggie patch.

Karen Hao: Do you want to describe more what you're seeing?

Alex Kairu: Yeah, I'm seeing a lot of houses, some grasses, some people in our
right side, watching us. So, yeah, it is a perfect scenario to get this podcast
going.

Annie Minoff: Karen wanted to talk to Alex Cairo because Alex helped make
possible one of the most viral tech products of all time, ChatGPT, the AI
chatbot created by the company OpenAI. When you use ChatGPT and it doesn't spit
out hate speech or extreme violent or pornographic content, it's partly thanks
to Alex and his colleagues in Kenya.

Karen Hao: What their contribution was was basically making ChatGPT safe for
tens of millions of users. They went through and reviewed really toxic grotesque
content day in and day out to make sure that no one else would ever have to see
it.

Annie Minoff: Now, Alex and his coworkers are ready to talk about what they say
that job has cost them.

Bill Mulinya: It was very graphical. You can't start reading the text and ignore
thinking of what is happening.

Alex Kairu: I had nightmares. I feared people. I feared working in the dark.

Mophat Okinyi: I'm very proud that I participated in that project now to help
keep ChatGPT safe. But now the question I always ask myself, "Was my input worth
what I received in return?"

Annie Minoff: Welcome to The Journal, our show about money, business and power.
I'm Annie Minoff. It's Tuesday, July 11th. Coming up on the show, Kenyan data
workers on the price they paid for safe AI. OpenAI is not the first company to
release an AI chatbot. But for many of the bots that came before ChatGPT, there
was a pretty consistent problem. The chatbots did not always behave.

Karen Hao: There's been this really long history of chatbots going off the rails
really quickly after launch. It's pretty much become expected behavior at this
point. In 2016, there was Microsoft's Tay, which just started spewing toxic
remarks days after the launch.

Speaker 9: In less than 24 hours, Tay went from saying things like, "Can I just
say that I'm stoked to meet you?" To saying things like, "I (censored) hate
feminists and they should all die and burn in hell."

Karen Hao: There was a South Korean chatbot, Lee Luda, in 2021. Again, hate
speech towards the LGBTQ community. And then most recently in 2022, there was
Meta's BlenderBot 3, which same thing, just a few days after launch started
saying these really racist things.

Annie Minoff: BlenderBot also had some choice words about Meta boss Mark
Zuckerberg.

Speaker 10: BlenderBot called Zuckerberg, "Too creepy and manipulative." And in
another it said, "I don't like him very much. He's a bad person."

Annie Minoff: For tech companies, a botched launch like this can be a disaster.
Microsoft, for example, announced it was taking its chatbot Tay offline just
days after its debut. OpenAI was aware of the risk. In fact, the company had
been thinking about it before ChatGPT, back when it was developing earlier
iterations of its technology. And the fix that OpenAI came up with required an
extra bit of engineering. It required building a filter.

Karen Hao: If you imagine your own brain, we always use, metaphorically, a
filter to make sure that you're socially acceptable. It's basically the same
thing, but the AI version. There has to be a final check on the output before
the AI model generates what it's going to generate.

Annie Minoff: Okay, so OpenAI needed that filter. They needed that filter built.

Karen Hao: Yeah, OpenAI needed the content moderation filter built. And you
cannot do that without humans.

Annie Minoff: Among the humans who would help build OpenAI's filter, were about
50 data workers in Kenya. And why Kenya?

Karen Hao: First of all, Kenya is a low income country and it has a very high
unemployment rate. Wages are really low, which is very attractive to tech
companies that are trying to increase their profit margins. And it's also a
highly educated workforce that speaks English because of colonization and
there's good wifi infrastructure.

Annie Minoff: One of those Kenyan workers was Alex Cairo, who Karen met in that
vegetable patch.

Karen Hao: Can you introduce yourself?

Alex Kairu: Yeah, yeah, sure. My name is Alex. I was born in Nairobi in Kilimani
Estate.

Annie Minoff: Alex is 28. He lives with his wife and his brother on the
outskirts of Nairobi. And when he started working on OpenAI's safety filter, he
wasn't working for OpenAI directly. He was working for another American company
called Sama. Sama is an outsourcing company. Its workers in Kenya have done
projects for a bunch of big US tech firms, including removing offensive posts
from social media. Alex says he was excited to join.

Alex Kairu: I just applied for the job, as people do, so I was hired as a
culture analyst in May 2021. When I came into Sama, I was promised that this is
the future company for me. They promised me skills, some training, so career
growth, education. I knew I will grow with this company.

Annie Minoff: Also at Sama was Bill Mullina.

Bill Mulinya: I saw an advertisement on LinkedIn. They were looking for a team
leader.

Annie Minoff: Bill was a level above Alex. He led a team of a few dozen people
at Sama. And at first he says they weren't working on OpenAI's filter. He told
Karen they were doing another kind of AI work.

Bill Mulinya: They first started with data annotation and image labeling.

Karen Hao: What kinds of data annotation were you working on?

Bill Mulinya: We were labeling images. For example, you're given an image, it
has traffic signs, cars, roads, trees, skies. So our work was to make sure we
label everything on the image.

Annie Minoff: Data annotation basically means labeling images or text passages
so that AI systems can learn from them. For example, labeling thousands of
pictures of street scenes so that an AI system can learn what a stop sign or a
tree looks like. But Bill's team wouldn't be labeling images for long, because
in November of 2021 the job changed. Sama had a new client, OpenAI.

Karen Hao: OpenAI had basically tens of thousands of text passages that they
needed labeled. So they would deliver these on a regular basis to Sama and
workers would read each text passage one by one and then assign a label to it.

Annie Minoff: OpenAI wanted a system where if you asked the AI to write
something awful, like a description of a child being abused or a method for
ending your own life, the system would refuse to write that. It would filter out
those bad responses before they got to you. But to do that, the AI has to know
what child abuse and suicide are. Humans have to teach it. And that was the Sama
worker's job, to read descriptions of extreme violence, rape, suicide, and to
categorize those texts for the AI. Here's Bill, the team leader.

Bill Mulinya: Their main work was to read the text and then label the data
accordingly. For example, if you read a text that is about sexual content, there
was a subcategory to determine whether it's incest, and those kind of
categories.

Annie Minoff: Bill and Alex weren't given much information about the project. At
first, they didn't even know they were working for OpenAI. They also didn't know
where these texts were coming from. But according to an OpenAI research paper,
they came from a few sources. Some were written by humans sourced from the
darkest corners of the internet. Others were generated by AI systems themselves.
OpenAI researchers would review the texts and send them on to Sama for labeling.
Here's Alex.

Alex Kairu: My experience on those four months was the worst experience I've
ever had working in a company because the content which I did was the worst
content you can ever read. Say someone is stabbing himself, someone is
committing suicide, you're reading something like that. So every situation was
very disturbing in the content we were reading.

Annie Minoff: Alex was part of the team at Sama that labeled the violent content
from OpenAI. Another worker who Karen talked to, Mofat Okini, was on the sexual
content team.

Mophat Okinyi: We will read about text of maybe a child having sexual
intercourse with their father or maybe a mother or maybe all of them. A child
having a sexual intercourse with an animal. We also had kids trying sexual
advances with each other, so we also had rape. Yeah, such like things, but they
were very graphical, though they were in the form of text. But if you are
reading the text, it becomes very graphic in your mind.

Annie Minoff: At first, the passages coming in from OpenAI were short, no more
than two sentences. But over time they got longer, as long as five or six
paragraphs. Workers might read hundreds of these passages a day. People on the
team were paid from around a $1.50 to $3.75 an hour. OpenAI paid Sama an hourly
service fee of $12.50 for the moderation work. An OpenAI spokesman said that the
company wasn't aware that the workers reviewing the texts were only getting a
small fraction of that. A Sama spokeswoman said that that $12.50 fee also
covered other things, like infrastructure expenses, and that content moderators
were paid according to a recognized formula for determining a living wage. Alex
told Karen that the money wasn't nearly enough to compensate for the
psychological toll that the work began to take.

Karen Hao: So when you would go home at night, what would you think about after
eight hours of reading all of that stuff?

Alex Kairu: Oh, my mental state was very bad. I had nightmares. I feared people.
Maybe I see too many people coming. I see violence. If I see someone holding up
fork or a razor blade, I see people cutting himself or something like that at
night. I will dream. I will have nightmares. Even I will tell my brother, "Okay,
just come here, sleep with me for five hours before I go to sleep because I need
someone to talk to before I go to sleep. Because if I go to sleep, I'll start
screaming or something like that. So many things are going a lot in my mind."
Yeah, yeah.

Annie Minoff: Alex says he'd always been outgoing and social, but as the project
ground on, he drew inward. He didn't want to be around people. For Mofat, the
worker who was on the sexual content team. The impact from doing this work was
even greater. Mofat is a soft-spoken 28 year old, and Karen says when he started
working on the open AI project, things had been going pretty well for him.

Karen Hao: He had actually just met a woman who actually lived next door to him
and he was living in this neighborhood called Pipeline, and he just immediately
fell in love with her. They just had a whirlwind romance and got married in a
few months. She already had a daughter and he very much doted on this girl and
called her his baby girl. And to this day still says daughter instead of
stepdaughter, in describing her.

Annie Minoff: When Mofat started working on open AI safety filter, he didn't
tell his wife about it. The texts he was reading were so grotesque. He says he
didn't want to scare her, but he couldn't hide the effect that the work was
having on him.

Mophat Okinyi: I had a baby girl. It reached the point that I didn't want to get
so much close to my baby girl because of the text I used read. Now if you see
that child, you reflect what you read in the text. Yeah, the good time you had
with your wife, it's taken away. So you remain like someone who doesn't feel
anymore for their partner.

Annie Minoff: Moat became increasingly distant from his wife who grew
increasingly frustrated. He knew he was struggling and he wanted help.
Specifically, he wanted psychological counseling. Sama did provide wellness
sessions with counselors, but Mofat told Karen that the sessions were
inadequate.

Mophat Okinyi: If you even go for a session, what they ask your basic questions
like, "How was your day?" You spent the entire eight hours working on these text
the entire day. And when you go for 30 minutes or an hour canceling session,
someone asks you how your day was or maybe what are your future plans? Those are
basic questions that doesn't help. So you also need professionals.

Annie Minoff: A Sama spokeswoman said that the company's leadership was unaware
of the psychological impact that the project was having on workers, and that
apart from counseling, the company also offered workers access to prayer and
meditation rooms. In Mofat's case, the counseling didn't work. His isolation
only got worse until his relationship with his wife reached a breaking point.

Karen Hao: His wife texts him and says, "Can you bring some fish home for
dinner?" And he bought three pieces of fish for him, his wife and the daughter.
And when he got home, they were gone and all their stuff was gone.

Annie Minoff: Wow.

Karen Hao: And he asked, "What's going on?"

Mophat Okinyi: And then I asked her, "Why will you not come back and why have
you left?" And then she said, "You've changed. You've changed. I don't see you.
You are not the man I married, things have changed. I don't understand you
anymore. You don't love my kid. (inaudible)"

Annie Minoff: Mofat told Karen that he doesn't expect her to come back and she
declined our request for comment. Mofat, Alex and Bill worked on open AI's
filter project for five months. All the while they weren't even sure what they
were helping to build or what its significance would be, but they and the world
were about to find out because ChatGPT was coming. That's after the break.
ChatGPT went live in November of last year.

Karen Hao: ChatGPT took over the world. You were just seeing people trying and
testing it for all kinds of things. And as the days wore on, the things that
they tried got more and more sophisticated.

Annie Minoff: People asked ChatGPT to come up with recipes based on whatever
they happen to have in the fridge.

Speaker 11: Jesus, that's actually good.

Annie Minoff: They asked it to help pick their next vacation destination.

Speaker 12: ChatGPT gave me five great ideas, and I went with Palm Springs,
California.

Annie Minoff: They asked it all kinds of things.

Speaker 13: I asked Chad GT to write me a song called Sexy Bus just to see how
it would go.

Speaker 14: Then I saw it shining bright (inaudible) Shiny silver bus, built it
so damn cold. It's sexy.

Karen Hao: It went from, "Oh, let me write a poem." And, "Holy crap. It's so
good at writing that poem" to, "Oh, let me try coding an entire website with
this thing. Holy crap. It can also do that too." And there was such a profound
shifting of the earth beneath us in a way of this has never been possible
before, and we suddenly have this technology that is unlocking a completely
different universe of potential.

Annie Minoff: Another way in which ChatGPT was a big leap forward. It was
generally pretty safe.

Karen Hao: One of the reasons why ChatGPT was able to become so virally popular
and continued to sustain popularity is because it is largely not spewing really
awful things. People feel comfortable using the product knowing that it's not
going to do that.

Annie Minoff: At least it won't do it in English. If Alex wanted to use ChatGPT
in his native language, Swahili, would he be able to do that?

Karen Hao: You can interact with ChatGPT in Swahili, but ChatGPT was developed
primarily to work in English. So a lot of the scrubbing, the content moderation,
the important safety measures within the chatbot were done in English. So when
you prompt it in Swahili, you'll get more misinformation. You'll get more
confusing sentences that don't make sense, and you will potentially get more of
this content that they worked so hard to filter out because they were only
filtering it in English.

Annie Minoff: Wow. I hadn't even thought of that. That the kind of filter that
you would build to detect hate speech and violence and sexual assault in
English, it would not work as well necessarily in Swahili.

Karen Hao: Exactly.

Annie Minoff: By the time ChatGPT took over the world, the Sama moderators in
Kenya had already been off the filter project for eight months. In fact, their
work had wrapped early and abruptly. Sama's contract with OpenAI was supposed to
last for a year, but a Sama spokeswoman said that Sama canceled it after just
five months because of a dispute with OpenAI over a related project. After the
filter project ended, Alex Bill and Mofat went on to other work at Sama before
ultimately leaving the company altogether at the end of last year. Bill and
Mofat still do data work at other companies. They say their new jobs don't
involve reviewing toxic content. Alex is currently unemployed, but while they no
longer work at Sama, they say they continue to struggle with what happened
during those months on the filter project, and now they're trying to change
things for all the people who continue to do this work. Bill and Mofat say
they've started organizing.

Karen Hao: How did you come up with the idea of a union?

Bill Mulinya: We came up with the idea because we noticed that it was not just
Sama (inaudible), it was the whole country going through the same kinds of
experiences. We met people at other companies that they're doing content
moderation work, and we realized the experiences are just so like the same. So
we decided instead of one person fighting his or our battles alone, we join as a
team and then we form a union.

Mophat Okinyi: We just want to ensure that everyone who's doing content
moderation right now or in future, they have better working conditions. They
have better pay, their rights are respected. So we are fighting for the entire
generation to come and us as well.

Annie Minoff: So far, their union includes over 150 data workers at multiple
companies in Kenya. Bill, Mofat and Alex are also pushing for legislative change
today with their Kenyan lawyer and the backing of a UK nonprofit called
Foxglove. They filed a petition with the Kenyan parliament. In the petition,
they urged the government to regulate the AI industry and bulk up worker
protections. It's now up to the parliament to decide whether to take up those
suggestions. As for OpenAI, the company said in the statement that data
annotation is challenging work that should be done humanely and willingly. It
said workers' efforts to ensure the safety of AI systems has been quote,
"Immensely valuable." A Sama Spokeswoman said that the company supports its
workers in every way possible and that it no longer takes content moderation
projects. She said that the work had never been a core part of the company's
business and that it had made a strategic decision to exit it entirely. When
ChatGPT launched, there was a lot of excitement about what AI might achieve.
There was also a lot of conversation about the jobs it might replace. But what
flew under the radar is the work that AI is already creating all over the world.
AI workers are reviewing all kinds of content. They're helping make AI more
accurate, more helpful, and safer. The stuff that they're reviewing is often
benign. They're labeling pictures of traffic signs or trees, but sometimes it
isn't. They're labeling hate speech, violence and extreme sexual abuse. And
Karen says that that part of the work isn't going away anytime soon.

Karen Hao: This is work that is going to continue to grow in terms of its
demand. This is something that researchers who build these chatbot systems
described to me as persistent necessary work because the more that these systems
are put in the hands of more users, the more creative they get and the more
abuses, basically, that these companies have to account for. So this is like an
iterative process where the safety filter has to continuously be updated over
time and every time it's updated that means more work to be done in the vein of
what Alex, Mofat and Bill did.

Annie Minoff: That's all for today, Tuesday, July 11th. The Journal is a
co-production of Gimlet and the Wall Street Journal. Additional reporting in
this episode by (inaudible) Ramen. Thanks for listening. See you tomorrow.

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HOSTED BY


KATE LINEBAUGH


CO-HOST OF THE JOURNAL., THE WALL STREET JOURNAL



Kate Linebaugh is the co-host of The Journal. She has worked at The Wall Street
Journal for 15 years, most recently as the deputy U.S. news coverage chief. Kate
started at the Journal in Hong Kong, stopping in Detroit and coming to New York
in 2011. As a reporter, she covered everything from post-9/11 Afghanistan to the
2004 Asian tsunami, from Toyota's sudden acceleration recall to General
Electric. She holds a bachelor degree from the University of Michigan in Ann
Arbor and went back to campus in 2007 for a Knight-Wallace fellowship.


RYAN KNUTSON


CO-HOST AND NEWS EDITOR, THE JOURNAL PODCAST, THE WALL STREET JOURNAL



Ryan Knutson is the co-host of The Journal, The Wall Street Journal’s flagship
daily podcast.

He has worked at the Journal since 2013. Before joining the podcast, Ryan
covered the wireless industry, and was responsible for a string of scoops
including Verizon's $130 billion buyout of Vodafone's stake in their joint
venture, Sprint and T-Mobile's never ending courtship, and a hack of the 911
emergency system that spread virally on Twitter. He also spent a year on the
business side of Dow Jones, helping lead the company's strategic relations with
tech companies like Apple and Google. Before WSJ, he reported for ProPublica,
PBS Frontline and OPB, the NPR affiliate station in Portland, Ore. He grew up in
Aloha, Ore. and graduated from the University of Oregon.

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