Undercover in the metaverse | MIT Technology Review
The second aspect of preparation is related to mental health. Not all players behave the way you want them to behave. Sometimes people come just to be nasty. We prepare by going over different kinds of scenarios that you can come across and how to best handle them.
We also track everything. We track what game we are playing, what players joined the game, what time we started the game, what time we are ending the game. What was the conversation about during the game? Is the player using bad language? Is the player being abusive?
Sometimes we find behavior that is borderline, like someone using a bad word out of frustration. We still track it, because there might be children on the platform. And sometimes the behavior exceeds a certain limit, like if it is becoming too personal, and we have more options for that.
If somebody says something really racist, for example, what are you trained to do?
Well, we create a weekly report based on our tracking and submit it to the client. Depending on the repetition of bad behavior from a player, the client might decide to take some action.
And if the behavior is very bad in real time and breaks the policy guidelines, we have different controls to use. We can mute the player so that no one can hear what he’s saying. We can even kick the player out of the game and report the player [to the client] with a recording of what happened.
What do you think is something people don’t know about this space that they should?
It’s so fun. I still remember that feeling of the first time I put on the VR headset. Not all jobs allow you to play.
And I want everyone to know that it is important. Once, I was reviewing text [not in the metaverse] and got this review from a child that said, So-and-so person kidnapped me and hid me in the basement. My phone is about to die. Someone please call 911. And he’s coming, please help me.
I was skeptical about it. What should I do with it? This is not a platform to ask help. I sent it to our legal team anyway, and the police went to the location. We got feedback a couple of months later that when police went to that location, they found the boy tied up in the basement with bruises all over his body.
That was a life-changing moment for me personally, because I always thought that this job was just a buffer, something you do before you figure out what you actually want to do. And that’s how most of the people treat this job. But that incident changed my life and made me understand that what I do here actually impacts the real world. I mean, I literally saved a kid. Our team literally saved a kid, and we are all proud. That day, I decided that I should stay in the field and make sure everyone realizes that this is really important.
What I am reading this week
- Analytics company Palantir has built an AI platform meant to help the military make strategic decisions through a chatbot akin to ChatGPT that can analyze satellite imagery and generate plans of attack. The company has promised it will be done ethically, though …
- Twitter’s blue-check meltdown is starting to have real-world implications, making it difficult to know what and who to believe on the platform. Misinformation is flourishing—within 24 hours after Twitter removed the previously verified blue checks, at least 11 new accounts began impersonating the Los Angeles Police Department, reports the New York Times.
- Russia’s war on Ukraine turbocharged the downfall of its tech industry, Masha Borak wrote in this great feature for MIT Technology Review published a few weeks ago. The Kremlin’s push to regulate and control the information on Yandex suffocated the search engine.
What I learned this week
When users report misinformation online, it may be more useful than previously thought. A new study published in Stanford’s Journal of Online Trust and Safety showed that user reports of false news on Facebook and Instagram could be fairly accurate in combating misinformation when sorted by certain characteristics like the type of feedback or content. The study, the first of its kind to quantitatively assess the veracity of user reports of misinformation, signals some optimism that crowdsourced content moderation can be effective.