S2E10: Decoding Twitter: A Look into Machine Learning, Social Media Moderation, and Workplace Dynamics with Melissa

Looking to understand the world of machine learning and social media moderation? Our guest, Melissa, a data scientist at Twitter, is here to shed some light on these complex subjects. She walks us through her daily work of creating algorithms that sift through millions of tweets, identifying and moderating potentially harmful content using natural language processing. If you've ever wondered how machines are taught to comprehend human speech, this episode promises to enlighten.

But that's not all. We take you behind the scenes of Twitter, revealing the company culture before the acquisition by tech magnate, Elon Musk. Melissa recounts the peculiarities of managing a worldwide workforce, the role of Slack in their daily operations, and the contrasting experiences of contractors and full-time employees. We further discuss the tumultuous period involving Musk's hostile takeover of Twitter, its implications on the content moderation team, and the controversial decision to ban Donald Trump from the platform.

We also broach the subject of the intense stress and controversy that can

Welcome to Season 2, where we embark on authentic and unfiltered conversations about life, relationships, society, and more. Our opinions are solely our own and don't represent professional advice. It's just our perspective, so form your conclusions. Heads up, this podcast may contain adult content and explicit language. Let's dive in!
 
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Transcript

Nicola: 0:42

We are starting this episode today with a bit of a call out for our listeners, so we are pretty much halfway through season two now. We finished recording for season two as well, which is really exciting. However, we don't know if we should do a season three or not, because it is a lot of fucking work and we don't get paid for it. I say a lot of work, it's a lot of work Like this, this camera here just shows up.

Gina: 1:17

Yeah, nikola has done most of the heavy lifting in terms of editing Instagram, linkedin, all of those things. I would be absolutely useless at doing that, but Nikola has really taken on the nuts and bolts of getting this up and running. Every time we talk to someone or I tell someone about this podcast, they're like that's such great work. We only want to help people. We're not here to make money from this, but at this point we both have full-time jobs. We're both single moms. We're not sure the amount of money we're putting into the podcast. We're not even breaking even. So we're upside down in terms of whatever we put into it. That's not even it. We just spend so much time on this and we love doing it, but at some point it's unsustainable.

Gina: 2:15

It's unsustainable. It would mean so much to us. If you guys can rate, you don't have to write the review. We would love it if you write the review. Just hit five stars or four stars or whatever. Just rate us.

Nicola: 2:31

Share on LinkedIn.

Gina: 2:34

Repost our Instagram stuff. We just need more people to listen, we need more subscribers. We need we just need it all. So it would mean a lot to us if you guys especially guys who've been with us since the beginning could potentially help us and share, rate, review All that good stuff. That way, it tells us that our work does matter and that it makes sense for us to keep going. We are at a little bit of a crossroads because we're not sure if we should continue on with season three just because it's just up in the air, because of all the things that we've just mentioned. Nicola, do you want to talk about anything else?

Nicola: 3:23

I think it's so important. You know, word of mouth is so critical and there's just so many opportunities or funny things that we've shared inside a lot of these podcasts that I think people or these episodes that people don't even realize are there because it hasn't really been shared far and wide enough. We've got a really great base following, which is amazing. We're so grateful for that and so thankful for that. We never you know, it's far more than the three we originally assumed would be there, and that's amazing. And we've got listeners from all around the world again amazing.

Nicola: 4:03

But we're kind of at their crossroads now where it's kind of like, okay, well, do we keep doing this? And it's hard because we've received emails and messages and texts saying, hey, listen to your podcast was really impactful I'm in a similar situation or messages on LinkedIn even where people have commented and saying, oh, my God, I've been in the same situation. It's so good to hear that there's kind of light at the end of the tunnel and you know, that kind of key has kept us going until now. But now it's kind of like, okay, we need to do a big shift, or it's just not as sustainable as we would hope.

Gina: 4:41

I also think we didn't realize just how much work it was going to be, because when I approached Nicola with the idea, we were like, oh my God, it's going to be so much fun, and it is fun. It is fun, but I don't think because neither one of us had ever done it before. We just didn't have the knowledge to be like okay, yeah, it's fun, but then you have to do all this other stuff, all the editing, all you know, all of these other back end things that unfortunately fall on Nicola, because I would be useless.

Nicola: 5:12

Absolutely useless.

Gina: 5:14

We'd have literally have one follower and it would be like my mom, who would never actually listen to podcasts, but because my editing would be so bad. But we digress. So anything you guys can do to help us, I think that I've tried not to interrupt a lot of our guests. Season two that was big on my priority list.

Nicola: 5:36

We listen to feedback. We take it on board.

Gina: 5:39

We might give you a little bit of a harsh time, of hard time about it at first, but it's our way of showing love. It's part of my love language. Verbal abuse is my love language. Just kidding, I'm just kidding, although I feel like there might be a little bit of truth to that with my really close friends, but um, yeah, so anything you guys can do just to let us know that you know we're being heard and we should keep doing this would be so amazing, so so amazing.

Nicola: 6:07

Absolutely.

Gina: 6:08

Before we get into this episode.

Nicola: 6:11

No, I think that's it from me. I'm so excited about this episode though. Oh my God, it's wild.

Gina: 6:18

Okay, just a little. Should we give them a little teaser? It has everything. Okay, oh, it's got everything. It has pass-all takeovers. It has machine speaking nuance.

Nicola: 6:30

Language learning.

Gina: 6:33

It's just it's got a little bit of everything. If anyone knows Stefan, it's like a Stefan episode.

Nicola: 6:40

Yeah, it's pretty cool and we learned so much. Oh, my God, so much I was like wait, I didn't even like, I didn't even subscribe for like a master's class in machine learning, but we got it and it was awesome.

Gina: 6:55

Yeah, we got it. So now I still cannot do machine learning, but we know at least that exists, because I don't even think I realized it exists before that. So please buckle up, get ready for this. There's Elon.

Nicola: 7:09

Musk there's.

Gina: 7:10

Sinks. There's right, there's Sinks involved. There's contracts, there's hostage some hostage holding, hostages being held. So in a very broad sense. But yes, we're interested in this episode to see how it goes, so please buckle up.

Nicola: 7:32

All right.

Gina: 7:33

Let's go, let's do it.

Melissa: 7:35

Then you want to be interviewed, maybe by the person who's going to be your boss, your boss's boss, maybe your co-workers and maybe the head of the department or the head of the wherever. So it's yeah, that's. It's a fairly common thing.

Nicola: 7:49

So it sounds pretty robust. Yes, Okay, because again, we know nothing of data science. I'm like this is fascinating.

Gina: 7:58

It's like I was like if someone said natural language learning, I would be like oh, so you're a speech pathologist, like, yeah, right, what Like I? It's so interesting, though, like because you're right, like so. So when you're doing the science behind that, what does that look like? Are you like monitoring for slurs or are you writing algorithm? Is it like a data algorithm? Like what?

Nicola: 8:24

is it?

Gina: 8:24

Tell us exactly what it is, because I have a feeling. A lot of our listeners probably don't know either Are as stupid as we are Lulis says we are yes, no, I think it's also very niche. It's a very niche area, right? So it's like we probably take it for granted. We just get on these sites and it is what it is, but there are people behind that, you know like. Alyssa, who are doing it, so explain. Maybe it dumb it down for me please.

Melissa: 8:54

Of course, and it's you're not dumb at all. This is a really, really complex, as you say, really niche topic, so no one should feel unintelligent because they don't understand something. I spent 10 years learning, right, so, yeah, so at a place like Twitter, when I was working there, there was 30 million tweets every hour, so 500 million tweets a day, every day, coming at you. So some of your users may be familiar with content moderation. On smaller, like a Reddit board or a Discord forum or something like that, where maybe something somebody's acting up, they're harassing somebody, they can they just moderate, they just ban that person, right? So there's this need of human level interaction. That type of human level interaction is just not possible on a site with as large and active a user base as Twitter. So there's this need for machine learning processes, for data science.

Melissa: 9:54

So I write these algorithms that continually search through Twitter and that's for keywords, like if somebody uses I'm not going to say them, but if somebody uses a public slur that we all recognize as a slur, that person can be banned immediately. But it's more complex than that, because there's all kinds of extremism, all kinds of speech that you may not want on your site, so you can't just ban keywords, you have to understand context, and this is this field of natural language processing it's teaching a machine to understand human speech, which is really, really fascinating. So let's say, you feed a machine language processing algorithm war and peace and you say what's this book about, and it can summarize that fairly well. The real challenge is when you have 280 character tweet, a very, very short tweet. So what you do is you look, you see a word that's potentially troubling and you look outside of that word, you expand to try to understand the context around that word and let's say doofus is a slur word, you know, just simple word.

Nicola: 11:13

So if I were to tweet at Gina and I'm like you're a doofus, that would get flagged. And then Gina tweets I got called a doofus and I'm sad. Essentially, that shouldn't be flag right.

Melissa: 11:28

You are. You are right. You've honed in right there to one of the major problems Because, let's say, you have this statement, as I said, you know, let's. I'm just going to use a figure. Hillary Clinton is a doofus. She drinks blood, she of the children child vampire Right, she's not.

Nicola: 11:47

She's not. I'm just saying I'm sorry.

Melissa: 11:51

I'm sorry, that's just normal.

Nicola: 11:53

We're normal people. We know she's not.

Melissa: 11:56

Of course all your listeners are lovely people, they understand this. But you could say, somebody could say that that would be definitely a red flag. But a journalist says such and such, a politician says, and then they repeat the same thing. You don't want to flag that.

Gina: 12:15

Right or so? That's what I can't believe, so and so says this you don't want to essentially, you're teaching a computer to understand the context, to then flag what is inappropriate and let the non inappropriate like a repetition of the slur, like the repetition of doofus. So that's so.

Nicola: 12:37

I don't bet that is like the math behind that, I feel, is like my brain doesn't even mess.

Gina: 12:43

that's the math, don't mess for Nicola. It's such an interesting like. It's such an interesting sort of marriage between linguistics and like computers, like you know. So it from your standpoint, is like AI is great, but it's like you have to teach right the computer to understand, like what we're asking. So you're probably high in demand now. Wow, you're awesome.

Melissa: 13:11

To me and feel and there's even if you'll allow me, there's even another wrinkle because I worked in, as I said, political misinformation. So, despite gathering a lot of, garnering a lot of headlines, really as a subset of like all speech, all the tweets on Twitter, the pretty small category. So first of all, you have to say you have to identify the tweet as political, so you bucket it into this being a political speech and then you have to search for it being misinformation and it was very, very uncommon. Again, we get big headlines, but it's really not that common, so you really need it's. Can I talk about how the whole process worked, or would you like to get fascinated?

Gina: 14:01

I don't even know this existed.

Melissa: 14:04

Great.

Gina: 14:05

But it does right, because it's like we take for granted what you're doing, because we just go on these sites and type away you know, and we don't even know the half of it, so carry on.

Melissa: 14:14

It's really amazing. Yeah, so there's really three, as I say, this three legged stool, this three legged stool. So, number one, you've got not in any order, they're all equally important. Number one you have the data scientists, the machine learning engineers, the people who are writing these algorithms, because, as I said, 500 million tweets a day, every day, they never stop. No human workforce in the world is large enough to monitor all those tweets. That's the first stool does leg of the stool. The second leg are the experts. We were expected to.

Melissa: 14:56

We Twitter operated in the US, in Brazil, in India, australia, across the world. These, you know large countries, both large and small, and we were expected to keep those sites clean of. Now, think about slang and political misinformation. And I'm I follow US politics, but I'm certainly would not claim to be an expert on US politics and I don't really. I don't really know much of anything about Indian politics or Japanese politics, but Japan is our second biggest market outside of the United States and it's huge, twitter's huge there, and so you have to have experts who understand.

Melissa: 15:40

Hey, I'm seeing imagine in 2017. Hey, I'm seeing this, this political trend called QAnon. You should look out for this. They're saying these things so they can help us to write our algorithms to better catch all these emerging things, all these code words that you can never know right, and so you need that's that site. Say that safety council, which you may or may not have heard of, but there's about 100 or so volunteers who were academics, who were law enforcement people, who were really experts in misinformation and hate speech, who would advise us somewhat to look for. And the third leg of this stool was, in fact, the human moderators, because, as good as I would love to say my algorithm is, it's going to miss things and it's going to miss classify things. If you ever tried to interact with an AI and it gets something wrong and you try to correct it, you know, let's say, on a helpline.

Gina: 16:39

It ends up in a loop.

Nicola: 16:44

Trust me, I had a fight I actually swore it chat GPT the other day where I was just like fuck off, and it was like we don't use language like that. I was like, wow, okay, because I asked it to do something. Gpt, don't tell me what to do, don't tell me, I asked it to do like a simple task. I was like, can you take this bank of text and turn it into 145 characters? And then it gave me 700 characters. I was like, can you count? And then it gave me 300 characters. I was like that's still not 145. Oh, yeah, yeah.

Melissa: 17:19

That's brutal so okay.

Gina: 17:21

So that is honestly, Melissa, that's the coolest thing. Like, yeah, it's very, very.

Nicola: 17:29

This is like one of the funnest jobs you could have.

Melissa: 17:32

I really enjoy it.

Gina: 17:33

Do you I?

Melissa: 17:35

really love it.

Gina: 17:36

Because whenever you're data science, I'm like ooh, like I think there were data and then I think of like data entry and I'm like mm-hmm, but that's not at all what it is, so, so cool, okay.

Gina: 17:49

So, now that we understand better what it is, you do, yeah. So my question is, though how do you handle those types of things? Like and I think that this is a precursor to what we're going to end up talking about how do you handle, like you know, in our Constitution, in America, in our Constitution, it's freedom of speech. So how do you reconcile that with what it is that you're doing? And you would have to know, probably and is Twitter governed, governed by the United States Constitution? Like, how does that work? Because, right, it's in all these different other countries. So how does that work?

Melissa: 18:28

In general, these tech companies follow the laws of the countries in which they are operating. So you definitely have to have lawyers involved. You have to have people who know the, the local laws and you know kind of customs and how the laws are interpreted. You can't feed that into an algorithm yet and have it understand. So that is definitely true. But at the same time, in general, we followed, you know, whatever company in the United States follows diversity. You know DEI practices.

Melissa: 19:06

You want to make sure your speech is not hate speech, it's not slandering somebody in terms of gender or, you know, sexual orientation or race or any of these protected characteristics. And this was not, you know, we were not a, you know, run by the government, so we were free to, you know, allow any kind of speech on the site that we wanted. I understand the argument. I've had a lot of conservatives since come up to me and say, hey, I think you should have let this speech on because of and they would lay out their case and I said I can understand why you're saying that, but Twitter was not some sort of outlier. We were just following, if you looked in, any kind of corporate culture. That's. That's what we were following Basically the kind of company best practices.

Gina: 20:03

Okay, so that makes sense.

Nicola: 20:06

So if you were working in political misinformation and please, you know, you, you, you say you read a bit of the American. I read a little bit of the American news, but I live in New Zealand, so and we're about to go through vote like a voting thing now and it's not great. So I do not claim to be any expert in any political. I don't even know how the political system works in America. All I know is what I read in the news, right?

Melissa: 20:35

So how do?

Nicola: 20:36

you. You know how did leading up to the election. I'm assuming that that made it incredibly difficult to you know on the three-legged stool. Now you've got more tweets, you've got more users using it to kind of spread the stuff. How do you capture, or how do you? How do you get the misinformation before it's spread?

Melissa: 21:04

Yeah, another. Yeah, I mean, that's the big thing, right? So, definitely, during before a midterm election or before an election, in general, political activity would tend to spike in political, hence political misinformation would spike, and there were I'm trying to think of this example, you know. So, if I can mention some political topics, no judgment on these topics. This is just some things that we flag. Yeah, absolutely so, there was.

Melissa: 21:38

So there's a conflict in Ukraine going on right now, a big and a big one. We would see, oh, this such and such a bridge was blown up and you're depriving all these children of their food, and this would sort of go viral. And these monsters, they've done this. A little bit of investigation was saying actually, this image, this video, was taken in 2018 in a different area of the world. So you very, very quickly flag something like that. Other times, there were outright calls to incitement of hate or violence. There was in another country again, I don't want to cast dispersions the mixed faith wedding was proposed of two prominent people. There was a lot of hate speech around that, people who were sort of inciting or calling to violence. Once those go viral, you need to be very, very quick on them to tamp them down. So when your algorithm flags things, you're just extra on the ball for these issues. You're like okay, here's something is so you really really need to be checking all these fires at once? Everybody just works harder.

Nicola: 22:50

Okay now coming back to like the workplace environment at this point. So let's say you are in charge of the political flags. Are you on call 24 seven Like? Is your phone like? Ping, flag alert, flag alert.

Melissa: 23:08

I mean yes and no. The secret of working in tech is that you're basically always on call. Hey, I work from home, you can see, but that also means I work in front of my computer. I'm in front of my computer, I can solve issues all the time. So, definitely, this is a that's a big issue in tech. So basically, I could be asked at any time of the day. But we did have a global workforce. We had people in Japan, in the Philippines, we had people across the world, the actual data scientists working on. There's only about 30 of us for the whole company which can. This is a whole other issue, but there's only 30 of us for the whole company. So already kind of a small workforce, but we were dispersed fairly globally in an attempt to combat this issue. So there's always people active.

Gina: 24:03

Wow, okay, that's interesting.

Nicola: 24:06

Who did you guys use slack?

Melissa: 24:08

You slack a lot.

Gina: 24:12

We've got, we've got a big hate relationship with.

Melissa: 24:15

Yeah, really.

Nicola: 24:20

We came from. Slack was used, obviously a lot, and there's just so many conversations that can go over people's heads or misconstrued, or you know, and then there's so many sub channels and it's just like.

Melissa: 24:37

I know it's.

Nicola: 24:39

It's been a over a year since we were at this place and I still have struggles on my notifications.

Gina: 24:47

Okay so can you take us to give us a little idea of what the company culture was before it was purchased by Elon Musk, like? Tell us what it was like working there for the, I guess, the majority of your career, while you're at Twitter, right?

Melissa: 25:04

Sure. So um, so I came on and I was this new data scientist. I've not new to data scientists, but I didn't understand all these. You know funky terms, you know impressions and you know articulations and annotations and all this kind of stuff and what what they all meant. And so the people who were there were very, very generous in volunteering their time to help me understand and to get me up to speed.

Melissa: 25:33

And you know, you've got to write these complex algorithms and multiple languages Python and SQL and high spark and all these different languages and you know, helping me understand that the code that existed, you can imagine, a company's been there for 15 years and some of that code has been around a long time and I'm hard to interpret, and so people really very generous and helping me understand things. I would say it's fairly a fairly generous and open, collegial environment. You don't get to work in data scientists and, you know, certainly at Twitter unless you have multiple degrees. So the everybody there is kind of has a certain level of understanding of the issues that are going around. So I found it to be very open and supportive environment.

Nicola: 26:54

Okay.

Gina: 26:55

Did you?

Nicola: 26:55

get? I'm just curious to know because I'm the nosey neighbor Were there any cool benefits like did you get extra leave?

Melissa: 27:07

I worked at Twitter as a contractor, so I technically worked for a different company. This is very common in tech and this is something I found out also once I left Twitter that this maybe works differently in different fields in a different country. So in the US, if you work as a contractor in the tech field, look, I had a Twitter email address. Let's angle it. Twittercom had a company slack. I went to all the meetings. I just was treated as this kind of disposable workforce. I didn't get that, I didn't get healthcare, I didn't get all these benefits. So, yeah, that's basically.

Melissa: 27:45

So no, I didn't have no, no cool perks for me, but I think you know, other people had certain things.

Gina: 27:51

Yeah, was the office like really cushy, though was it nice. Like that was very nice, I went in maybe once a week or so.

Melissa: 27:57

But I mean, I work in. I live in San Francisco. You know you could. It was easy for me to go in, but yeah, yeah, but it's also easy to stay here.

Gina: 28:06

Yeah with your cute little puppy over there. Okay, so you were pretty happy with with Twitter the way it felt meaningful to work in that environment, to work in political misinformation.

Melissa: 28:17

Feel like you were going to make a difference.

Nicola: 28:21

Yeah, because you know, because I know nothing, were you a Twitter during that big like January six stuff.

Gina: 28:31

Oh, the insurgency here.

Nicola: 28:34

Yeah, because I feel like that would have been a firestorm.

Melissa: 28:39

Yeah, that actually was right before I started, so I did not deal with.

Gina: 28:43

Oh, you missed it by like.

Melissa: 28:44

I can't comment on that. I was still feeling the effects of that. A lot of policies came into place because of that and, of course, our then President, donald Trump, was banned from Twitter two days after that. Whatever, after Jan six, in that space he tweeted something like 145 148 separate violations of our terms of service. It's not just excitement to violence, political misinformation, etc. Etc.

Nicola: 29:15

But I you know when there was happening and I read in the news that he'd been banned. In the back of my mind I saw and please correct me if I'm wrong here, but in my mind All I saw was, like all these Twitter people just like running around, like headless to things go oh, my God, find us a cat. Delete, delete, delete.

Melissa: 29:36

That you? That's really true, because another thing about Twitter is that if an account had over 10,000 followers, it was considered a political events to ban it, so my algorithm could not ban could not action person has to actually add the account.

Melissa: 29:57

It goes up above my head to people who make a decision, and so you can see in the Twitter files I don't know if any of your listeners went through and read the Twitter files, but you can see people like Jack Dorsey, who was then the CEO, and you'll rock like agonizing over should we ban Trump? Should we ban, you know, other US politicians like what do we do here? So yeah, it was a really big decision.

Gina: 30:25

Yeah, I can't even imagine. And then, okay, so I am still fuzzy. When did the whole, when did Twitter even go like be put on sale or whatever? Like when did they say, when did the current owners say we want to sell it? Or did Elon go approach Twitter?

Melissa: 30:45

If I can give us sort of abbreviated history of what happened.

Gina: 30:49

Yeah.

Melissa: 30:54

So this I know some of this stuff because of the what this recent Wall Street Journal article that came out, but I knew most of it just because of working there at the time. So in January, elon Musk completed the sale of a lot of his Tesla stock and so we had all this cash and he was looking to invest it and he started buying up Twitter stock. So in January, he purchased about 9% of available Twitter stock and he was a significant investor at that point in Twitter, which was then a public company. And so he, being a very, very, very public personality, was invited. Like the board said hey, you want to be on the board, this would be, you know, great. And so he was at first on the board and he had some personality clashes with a project or see pro agro wall and some other people who were there at the time and so he made the decision he wanted to buy it.

Gina: 32:00

Nobody was actually selling it.

Melissa: 32:03

Nobody was selling it. This is going to be a hostile Okay makes the decision he wants to buy it, although it's yeah, he made a decision, he wants to buy it. He offers he has to put together all this money. So put together this $44 billion offer, this staggering amount of money, for that's a company that, frankly, probably was not worth that much even at the time.

Gina: 32:27

Right, it's worth a lot, but 44. That's a shit ton of money.

Nicola: 32:32

That's like. That's like a couple of small countries.

Melissa: 32:36

Yes, yeah that's the ggb.

Gina: 32:39

It's like a number you say when you're like exaggerating oh my God, I don't know. 44 billion, right like I. Just I called you for a billion times and you know if it's like that much money to throw away on Twitter.

Nicola: 32:55

Can he not just bump me like just just half a mill, like I'm not even asking for a lot, like half a mill, why?

Gina: 33:01

don't we all just get like half a mill? It's a hostile takeover, she's. That's crazy. I don't think I realized that. I thought that he just gave them like an offer they couldn't refuse with that 44 billion.

Melissa: 33:16

Yeah, so yeah, essentially he, so he offers them this money. There's some resistance in the board, but again it's. It's something he's able to push through because of who he is. Even Elon Musk doesn't have $44 billion. Three, because most of it's tied up in stock and all this stuff that you know so puts together this loan involving lots of different people Larry Ellison, saudi investors, people around the world.

Melissa: 33:46

He sort of pools his money. When you're rich, people give you money. So he sort of pools his money and he makes this offer and almost immediately starts to back out and he doesn't want to see this offer anymore. But he's already signed, the ink is already dry, is already signed. He's already signed this contract that he sort of ironed out this agreement with the board that he's going to buy it. Um, they say no, this is the contract You've made this contract. You need to buy it. And so from about late January all the way through the summer, he's saying he wants to back out of it. All of us workers there were like what the hell is going on here?

Gina: 34:35

That was my next question how did all of that back and forth?

Nicola: 34:41

Because I feel like that would have felt so unsettled, like what a horrible environment.

Melissa: 34:48

Yeah, it was really tough. It was really tough. It was really hard to know what the future was gonna be. And, specifically, I worked in content moderation. We all felt like we had targets on our back, even before we purchased it. He was saying I don't like the way you do content moderation, I don't like the way you do political misinformation. We banned one of his favorite sites, this Babylon B. It's this political conservative humor site. We banned it. He didn't like that, but they violated our terms of service and so we all felt like, oh, this is really bad, and so you're right. It was really unsettled. Nobody really knew what the future was gonna be. You can imagine how upsetting that would be to your morale if you're trying to work in that environment.

Gina: 35:33

That would be horrible. And everything's up in the air.

Nicola: 35:35

Yeah, I mean, that's like the worst, like you're just feeling like shit, Like why are you even bothering moderating? Like why are you even bothering? But the moderation when no one gives a shit now?

Gina: 35:45

Yeah Well, that's not true, because it's still Twitter's terms and conditions. From the old guard, right, nothing's actually changed hands, so-.

Melissa: 35:53

Nothing has changed.

Gina: 35:55

Right, you still have to do what you've always done, knowing that the potential new owner of this company doesn't like what you're doing. That's gotta be the worst fucking feeling.

Melissa: 36:06

It was really bad and there was a lot of internal sort of rearrangement and we went through a major reorg. At that time, in anticipation of the very scant information we had on what he wanted and how he would like, we tried to consolidate all of our services to sort of better please this person, who may or may not be our eventual CEO.

Gina: 36:30

And that's nuts, because it's like then you're catering to one person.

Melissa: 36:34

Yeah, exactly.

Gina: 36:35

It was very like tyrannical, almost it's like okay, so he ends up not backing out of the deal, obviously, because now we know.

Melissa: 36:44

Yeah. So in mid to late October, very, very rapidly, everything switched. She says no, I'm gonna go in. His lawyers advised him you can't get out of this, they're gonna sue you, you're gonna lose. There's a $1 billion back out clause that he would have to pay out of pocket. So you can't back out of this. So he goes to find I'll get it. So he goes through and I think that just typifies his style of leadership ever since just sort of this impulsive sort of mercurial style of leadership. Besides, he's gonna buy it really quickly. Panic, panic sets in at the company. People are freaking out. I've been through takeovers, I've been through mergers, I've been through companies just dying on the vine, these tech startups, and I've never seen anything like it where people are openly disparaging. I don't trust the new owner, I don't trust he's going to do what's right for the company. I've just never. I've never seen that before, and people really fearful for their jobs.

Gina: 37:49

Yeah, I mean also I go ahead.

Nicola: 37:51

Neville, I was gonna say how did you feel Like? What were you feeling at the time? Cause you're a contractor, right, so you did you have some kind of like okay, this is gonna get really ugly, but at least I've got the opportunity to eject eject if needed.

Melissa: 38:08

Yeah, I did sort of start to. I was terrified. I mean, I was personally terrified. I did sort of start to look for another job. But it's hard to job search when you're I keep in mind the.

Melissa: 38:24

US Like you're doing, full-time work Coming up, yeah, exactly, and I just, you know, my then partner and I would just sort of he was just like sort of commiserating with me and sort of like trying to distract me from this awfulness that was happening and yeah, I mean just really terrible. And then, you know, Musk purchases the company on, I believe, October 28th. He goes in. There's this photo of him holding a sink which I guess one of his poor aides must have scratched up for him, and he says he tweets a picture out. I just bought Twitter, let that sink in, so he had one of his assistant partners. That is so corny. Yeah, it's so corny. That's so corny. I can't stick.

Gina: 39:12

Also, we just did an episode with an ex-celebrity assistant and what you said? That his poor aide probably had to get him the sink.

Nicola: 39:20

Oh my God, he just wanted to get a sink, like immediately, like he just decides for the moment he needs to find me a sink and the poor aide is like OK, I'm a flatter, like I'm fladding with my flatmates, you know what? I'm just going to pull it out from my own home.

Gina: 39:36

And I'll like drag it over, or like it's like in the middle of the night and like he calls up his aide and he's like I need a fucking sink.

Nicola: 39:48

Oh my God this makes me think of. I don't know if you've seen the movie the consultant. I mean the TV show the Consultant Melissa.

Melissa: 39:55

Yep, yes, definitely.

Nicola: 39:56

You did.

Melissa: 39:58

Yes.

Gina: 40:00

Is he not Elon Musk?

Melissa: 40:02

Oh yeah, and inside there put that together.

Gina: 40:06

Absolutely. He is Elon Musk, because he's just like oh that's so funny. He's like I need a pistachio churro at 2.30 in the morning.

Nicola: 40:14

Oh no, give me my pistachio sink. It's going to be pistachio colored. It's going to come from like an art deco vibe.

Gina: 40:23

Yes, Vintage sink. Ok, so when that happened, when you saw the let that sink, I truthfully have never seen that, because that's unbelievable, but it doesn't surprise me. Famous people are fucking insane. Yeah, definitely Most of them.

Nicola: 41:19

Well, OK, let's dial that back for a second. I don't feel like he's famous. Let's just make that clear. He's just got a fuck ton of money. That has made him special.

Gina: 41:28

But he's well known. I would say he's famous. He's like not famous after he's a famous business person, like Lea Aikoko was famous business person, like there's tons of people.

Nicola: 41:38

And I'm just restating that South Africa does not claim him. We're not claiming him. He can be someone else's issue. He's not us.

Gina: 41:48

I guess he's. He's ours now. He's America.

Melissa: 41:51

He's all American now your problem.

Gina: 41:54

Ok, so when you found that out, how? First of all, how was the information being disseminated to you? Was it that nobody even really knew what was going on, and then it would come trickling in? Or how was the chain? Well, we know that the change management was not existing. It was not an existing change management. But when you did get fed information, how are you learning it when the rest of the world was learning it? How was that happening?

Melissa: 42:21

There was very little that was coming through to us. So there's panic, there's scrambling, there's let's write up our business processes so maybe we can communicate to this guy what we're doing, what's happening. And so that went on for about a week. Where we were, everybody was trying to get me I was not important enough to get a meeting with him, believe me, but there were people who were ahead of my department who were trying to get meetings with them, just trying to get FaceTime with them, to explain like, hey, this is what we're doing, this is why our job is important, and I imagine that was happening across the company. Sure, yeah. So for about a week that happened, he had one quote unquote town hall with everybody where he just talked about how hard he was going to have everybody work and we asked about layoffs and he said he felt the company was over staffed at that point. And I just I know there's a lot.

Melissa: 43:28

Well, thankfully, you all are probably not aware of this, but there's like a lot of arguments on Twitter, outside of Twitter, about like, hey, he owns the company, he can do whatever he wants, he can make his employees work hard. Yes, he can, but we're all adults, we all I have two children. We all have lives. What about this work-life balance? Hey, you're going to work 60, 70 hours a week and you might get fired. Just imagine what that would do the morale of your company. Not good things. And we were already highly fractured from this year almost year long now tension of sort of real he won't he.

Nicola: 44:04

Yes, you know what? Ok, so that actually really is interesting for me, right? Because we talk a lot about toxic workplaces and I find that fascinating that now you've got not only a toxic environment unfolding literally in front of your eyes you can see it coming like a freight train but now you've got people online pushing that toxic workplace narrative as well, where it's like, oh, tough luck, just fucking pull your socks up and work. Any way, you slackers.

Gina: 44:36

Yeah, that's exactly true and people who idolize Elon Musk, like, oh, he's going to let Trump back on blah, blah blah, and just want to say I don't have any say on any of that. It's above my pay grade, I don't know whatever, but the big thing that we heard about was that one of the impotences for Elon Musk to purchase it was to get Trump back on Twitter and to really sort of uphold the constitutional right of free speech, so that basically that endangers what you do on so many levels, like personally.

Melissa: 45:17

Yeah, exactly, it was something that we were all very, very much worried about, especially after the events of Jan 6, that he's going to let back on these dangerous political actors who are going to continue to undermine the election integrity and to incite violence and to perform this just really awful amounts of speech and hate that they were spewing onto the site pre being kicked off.

Nicola: 45:44

Wild, but it just undermines all of the work that you and the rest of the data people have done. You've got this years you said 15 years of algorithm and work and shit that had blood, sweat and tears, that has gone into creating something that is safe enough or manageable enough to make things not bad. And here you have someone coming in and going eh, the wanky name, Meh.

Gina: 46:15

It's like what is I really like this. We're just going to throw it out.

Nicola: 46:20

I'd rather like it in pistachio.

Gina: 46:24

I'm sure it must be pistachio. I agree. Yeah, go ahead, melissa, because that must have made you feel were you angry? I would have been fucking furious if I were you like in your position.

Melissa: 46:38

I was terrified. I was terrified, I wanted to check out. I wanted to curl up on my bed, which I worked right in front of, and just cry. But I didn't know how to handle this stress, and so I am a tech worker I handled it the very unhealthy way of just working harder. I didn't know what else to do. And again this is like October 28. Us midterms are November 8. And I thought, look, the only thing I have controlled over is trying to keep this platform safe of bullshit Right Before this midterm. It's the only thing I can really do at this point. And we just safely shepherded through the Brazilian election. If your listeners recall, this was a really big election.

Nicola: 47:28

Oh, I remember that in the news. That was weird.

Melissa: 47:31

Yeah, yeah, yeah, and there was like a runoff election. It was a huge thing for us to deal with because we're very, very big in Brazil as well. So, yeah, wild, ok, put my nose down and work harder.

Nicola: 47:47

I didn't know what else to do. Now I mean I can understand that Now I'm going to take a slight left turn for a second, ok, and so I have got a couple of glass door. What glass door reviews?

Gina: 48:04

Please, I cannot wait, I can't believe you and I didn't think to do this earlier.

Nicola: 48:09

Oh, I had already thought this through buddy. Ok, good, let's hear it, I was right with my glass door reviews.

Gina: 48:15

Let's hear them please.

Nicola: 48:17

Ok, these are not old reviews. This is August 23. August 2023.

Gina: 48:26

Like last week, possibly so 27th of.

Nicola: 48:27

August yeah, 2023. Worst place on Earth. Pros Nothing, not a single thing. Cons Elon Musk is a horrendous excuse for a person putting people through hell all the time. The treatment of employees, the treatment employees are subjected to, is equivalent to torture. Also, a rich moron can have his fun. Do your mental health a favor, quit now. That's amazing. This is not just like a tech person or a person at the bottom, you know, down at the front lines. No, this is management. Wow, all right. Oh, there, we have another one star. The title is Eh Social media specialist. Ok, pros Cool team. Very fun people. Cons it's not heading in the right direction. I'm going to quit. Oh my God, this is so good.

Gina: 49:36

So what is overall on Glassdoor, what's the rating? It's not great, it's 3.2.

Nicola: 49:43

I really thought it would be lower. That's probably because you know why.

Gina: 49:48

Previously to Elon Musk it was a good. Previously they're pretty good right.

Nicola: 49:53

So that balances it out.

Gina: 49:54

We should check back in like a year and see what happens.

Nicola: 49:57

Yes, if the overall so, with that in mind, so now we're in the process of transitioning into this new empire. Oh my God, We've got so many TV references here. It's like we've got Star Wars, We've got, you know, the rebellion. Were there people within the organization that were like actually something needs to be done about this? Or was there people in the organization that were like this is this is not okay, Like what did HR do? Yeah, I think.

Melissa: 50:37

Yeah, I think there definitely were so people at the top. So all the entire executive council was fired immediately. Jack Dorsey had left about I don't know five months earlier to be replaced with Prague Agrawal. Yol Roth was there, I think Yazmina oh my gosh, yazmina Reza, I think, was still there. So I know just from listening to Yol Roth interviewed I didn't have contact with these people, but I know from hearing him interviewed and reading other people they all pushed back against this, against his decisions to do these things, quite vocally and I know that people on my team one person did was able to speak with him Personally. He'd been there for many, many years. Highly respected data scientist, just a brilliant guy, and he was fired after offering his suggestions. People who spoke out on Slack were critically. He had Musk had people go through Slack channels to see if people were talking badly about him and he fired engineers and other people. I know the engineers who were fired if they spoke poorly of him. It's just. You know, that's just insane to do that.

Gina: 51:57

It's insane. Because, like any boss, you're a boss for a reason, right, or you're a leader for a reason and you're not gonna be able to please everyone all of the time. And he had to have some kind of modicum of understanding that when it's this like social and it's being written about in the news and you know there's gonna be people with feelings Like he just wanted a blind loyalty, it sounds like yeah, that's.

Melissa: 52:23

Exactly right.

Gina: 52:24

Yeah, that's terrible Okay so when the executive team started firing or getting fired or leaving or whatever. Obviously, I would imagine the morale of everyone is in the garbage. It's in the gutter, right, like nobody wants. You know you're either overworking because you're terrified or you're probably like fuck this place, I can't wait to quit, like our yeah, dumpster fire and also like our glass door review. What did they say it's like it's akin to torture?

Nicola: 52:57

Yeah, I'll see if I can find some more James.

Gina: 53:02

How did you feel Like? You're like, oh shit, now all of the people who were in leadership positions, like super leadership positions, executives aren't being picked off Like. Did you just know it was like a matter of time before you were?

Melissa: 53:16

Yeah, who's gonna advocate for me? Who's gonna advocate for my department? Who's going to say, hey, this is from 30,000 feet, this is what all the departments do? Who's gonna help him understand the company? And, as it turned out, there was nobody there, because the way the layoffs I'm sorry to jump ahead a little bit the way the layoffs were conducted is basically he just took a giant sword and split and cut the company in half. Because on my team I worked in a subset of a subset of political misinformation Two of the three of us were let go and everybody I talked to the department just seemed to be cut in half, irrespective of your job, your specialty, what you were actually doing. And then he ordered a complete reorganization of the company at that exact same time. No, oh, I'm gonna walk you through. I'm gonna have a gradual change, nothing like that. It's just gonna happen in a blink of an eye and you're gonna get aboard my new regime immediately.

Gina: 54:25

And if you don't, I'm gonna find out and slack and fire you.

Melissa: 54:28

I will fire you. Yeah, you have to perform high to high standards A few, and I was like I can get into this, but I was let go after two weeks after he purchased the company. But people who stuck around had to sign a loyalty pledge that they wouldn't work hard. Yeah, they had to sign a loyalty pledge. He promised them that they would have to work hard and that they would be highly rewarded if they did so, but they had to pledge that they would fulfill these terms.

Nicola: 54:57

And were they unrealistic? The expectations just shitty.

Melissa: 55:03

Yeah, the expectations, the stated expectations, were really incredibly onerous. But I just again, I just want people to what if your boss said, hey, for the next year we're gonna have to put in extra long hours you might be working nights and weekends how do you feel you probably wouldn't. That's not a place you'd wanna work at, would you? I wouldn't. I work hard, by the way, I work really hard. I have to believe I believe it. I have to work hard throughout my life. But, like Absolutely, I absolutely also need some balance in my life.

Gina: 55:44

And we all do. Of course, nobody can be the best version of themselves, working all the time, you know what.

Nicola: 55:50

Let's use our toxic workplace as an example. Right when Gina met me, I was working like maybe 3 am my time to 11 pm my time, so there was very little time for work-life balance or sleep. And when she met me, I was a fucking asshole.

Gina: 56:10

This is a different person you see before you, melissa, than the person I met, and so it's similar to that. Right, it's like if you're gonna be working nights, weekends, you're like eating, sleeping at your desk or at work or whatever. It's like you're not the best version of yourself. There's no way you can be. Like, if you have to do it like for one week because you're like your deadline is like coming up and maybe you have like a bunch of last minute things to do, fine, I think anyone can get behind that, but like literally for a year, no, and did anyone have anything to say about like, was there any offer to and this might not have been something that you were offered because you were contractively, but yeah but like any therapy or mental health offers for like people, the people who are staying there to go through the transition was there anything like that, provided?

Melissa: 57:07

No, there was actually nothing.

Gina: 57:10

There's actually nothing. Oh my God.

Melissa: 57:13

Yeah, nothing like that at all. Are these poor people?

Gina: 57:16

Yeah, I just feel bad for everyone. So, out of the people who were there when you were working, how many do you think still exist? And you're like, we know like a majority of them got fired. But of those people who didn't get fired, who were there when you were there, what percentage do you think is still there?

Melissa: 57:37

Well, my department of 30 data scientists I specialized not easy to replace who were working in political misinformation. Of those 30, there were eight that were left after the various firings.

Nicola: 57:51

But then that doesn't that then just cause like a ripple effect of shit. Like now you've got low resourcing, you've got people that are stressed out. They're gonna miss things because they're human. You're not going to have the best algorithms. Spotting bullshit coming through Like this is just like a ripple effect of doom.

Melissa: 58:12

This is what I'm saying because these algorithms we have this idea that machine learning you, just it's magical, it's understanding you, but really that's not true. You need to continually be updating these algorithms Like teach it, keep teaching, keep teaching your accuracy, especially as the nature of in my field I know about it's the nature of political discourse changes. You need to make sure you know. Let's say, like six years ago when this pizza gate scandal, there was a scandal in the United States called Pizza Gate, this conspiracy theory. If you did not update your algorithm since Pizza Gate and you were still looking for Pizza Gate today, you're not going to catch all the new things, all this new misinformation that's out now. So you need people there to continually update.

Melissa: 58:57

Automation is a nice goal I actually think it's a really good goal and we probably were over sapped. There's a lot of layoffs that have gone on in the tech space since then, but I've been part of change management. Before you have a goal, you have a plan, you transition people, you make sure roles are filled. He cut staff in half, ended up even being more than half, but who quit and were fired long-term he cut services. So all this cafeteria that was closed, all these other things were closed, all these extras were taken away from people and you're just. It's like this austerity plan. You know like you have to work so hard to succeed at this company, where you're given nothing.

Gina: 59:47

So I just like I don't understand how he, I also don't understand how he thinks this can now be successful.

Melissa: 59:57

I don't either, and I believe he you know a lot of the people who've left. They don't have an option. They are people who are here on H1B visas or they are people who he has locked into. You know, like, who are the people he has some amount of power over, and not everybody, of course. But there's a photo of the Twitter workers that he posted about a month after I left. It was posted at 2 am on a Saturday and he's bragging about how they're all working so hard and if you look there, all people who are foreign born workers, people who are here on H1B visas, people who are stuck, who are here because they have them and they leave, they lose their visa.

Melissa: 1:00:45

Yeah, they lose their visa, they gotta go home and I know plenty of people who were cut off like this. You got, you know, I think, 60 days, 90 days I'm sorry, I'm not super familiar in the US and you have to leave and you have to go home if you can't find a job in that time.

Gina: 1:00:59

Right, it's just cruel. That is cruel and even, like I know, when we first briefly talked, we were talking about, like you know it does. It trickles down to everyone, even the cafeteria workers, like okay, so now you don't have on-site cafeteria, and all of those people are now without a job and like what's the purpose of that, Like don't you want your employees to be fed and healthy?

Melissa: 1:01:26

Exactly.

Gina: 1:01:26

Like I'm a mess when I don't eat enough. Like I am a fucking mess.

Melissa: 1:01:30

I make terrible decisions.

Nicola: 1:01:33

Oh my God, you guys can do that. I get, I get. I'm trying to still come up with a word for thirst hangry, because I get thirst hangry.

Gina: 1:01:40

Okay. Thirst hang Thirst hang oh my God, I get so angry, Like if I'm thirsty, I start like, like no, for me it's food, unlike if I'm not being fed, if I'm not feeding my face in, like you know, a normal fashion. It's no good.

Nicola: 1:01:58

Totally unrelated. But when you do eat, do you do? When you eat something really yummy, do you do the food wiggle?

Gina: 1:02:08

Not usually, unless, like I'm out at like a really fancy restaurant, because then I was like, like, like, like. But my daughter does the food, the food, toe wiggle when she's eating something she likes, she like, wiggles her toes, she's like, yeah, she's so cute.

Nicola: 1:02:26

Do you do the food wiggle, Melissa?

Melissa: 1:02:29

I do, sometimes Absolutely. Right sometimes it helps.

Nicola: 1:02:33

It has to be like exceptionally delicious. Oh no, I could do it for like a sandwich.

Melissa: 1:02:39

Oh, I love it.

Nicola: 1:02:40

I love it. I'm like, ooh, that's so good.

Gina: 1:02:46

Well, you know I get it. You know food does bring joy. But like, how fucked up. Back to Melissa's story. How fucked up is that? It's like now you got to go out and like Find a sandwich.

Nicola: 1:02:57

Pay for a sandwich with your location. Get a sandwich. Where do you go home?

Gina: 1:03:00

But you're never home because you're fucking working 24 seven, so you're just eating air and ice and water. I mean, I don't understand this, how I still, even with the limited amount of information I had because I don't really get too involved with much in terms of, like, I hear about it, I don't form an opinion, but I was like I just thought, like in the back of my mind how does he think that this is going to be successful?

Nicola: 1:03:25

Like there's already all what's sustainable.

Gina: 1:03:27

Right, and there's already all this rumbling of exactly what Melissa is now confirming and what the glass-drawered views say that are like it is intolerable to work here. It is intolerable to be under Elon Musk, like how does he think this is going to get a return on his investment?

Melissa: 1:03:43

I don't understand, because even he did not even really reward the people who ended up being loyal to him. There was a woman named Esther Crawford and I don't mean to put her on blast. She was a brilliant, lovely woman. I'm not criticizing her. She very publicly put her out on Twitter that she was bringing her sleeping bag to work. She was sleeping in the office. She was so dedicated. This is the thing she's advertising publicly, everybody saying so. Some people mocked her at the time. Well, three months later, she was fired by Elon. He just doesn't reward people making sacrifices, people trying to work under his regime. There's nothing that you're getting.

Gina: 1:04:28

What does he actually want?

Nicola: 1:04:33

He wants results, he wants results Of people just to suck his dick every morning Like this is where we're at. I just don't understand.

Gina: 1:04:39

Okay, so he comes on, he gets rid of some of whatever it's. Now Trump is reinstated Freedom of speech. It's probably a lot, messier on Twitter, which is also now called X.

Nicola: 1:04:52

I can't with the X. Actually, to be honest, the minute I woke up okay, I don't really use Twitter that much, it's not really my pet views, but like cool, cool, cool, usually had it in the background. The minute I woke up in the morning and my Apple phone had updated and I had a big black X on my phone, I was like you're done, delete, we're done. Thank you very much.

Gina: 1:05:17

And also, like when we first started chatting with you, melissa, we said, like it's part of like the lexicon, like it's like I tweeted something, or did you read this tweet? What the fuck are you gonna say now, did you? I asked something, I mean.

Nicola: 1:05:30

I'm sorry, what are?

Gina: 1:05:31

you saying, like, where's the forethought? Does he have like people who handle branding and marketing helping him, or is he just coming up with shit and, like word, vomiting it out? Cause, that's what it sounds like he is the toxic visionary.

Melissa: 1:05:47

You know, when he originally, you know he had this company called this payments company that he ended up merging with PayPal Peter Thiel's company, paypal. So they merged together he wanted to call it X. This is like in 1999. So he wanted to call it Xcom. So he's had this in his brain for a long time 24 years, 25 years.

Nicola: 1:06:12

Laying dormant, waiting for the right time to strike.

Gina: 1:06:16

To exit Wait. So his kid is also named, something ridiculous.

Nicola: 1:06:22

X, black x x, a lot, a lot it's like with like weird, like outer space letters that don't really fit. Give me a second. I won't Google it, Because it's right.

Melissa: 1:06:32

It's pretty much like Ash 12 or something like that it's ridiculous.

Gina: 1:06:37

So based on that, he should be. He should be like stripped of all of his name giving power.

Melissa: 1:06:43

I think you're right Like.

Gina: 1:06:45

I just like and I keep saying it, but I just can't understand, from a business perspective, why he thinks what he's doing is going to end up being successful.

Melissa: 1:06:55

It's really wild.

Nicola: 1:06:57

It's X, a E A 12. So X S to 12.

Melissa: 1:07:07

Rolls off the tongue.

Nicola: 1:07:08

Just really rolls off the tongue, doesn't it? Oh, okay, hold on, fast forward. I went to take you all in your minds to a moment in time.

Melissa: 1:07:19

We're in.

Nicola: 1:07:22

This child is 25.

Gina: 1:07:25

He's at a pub.

Nicola: 1:07:27

He's, he's picking up some girls or guys. We're you know, we don't judge whatever he's picking up. They get home and he's like, yeah, baby. And the guy or girl is like, say, my name bitch. And he's like I don't know how.

Gina: 1:07:45

I've been pronouncing your name, or like what do you think he does when he goes into Starbucks? For me, just give me a sec I need the pronunciation the Google translation on that.

Nicola: 1:07:56

Hold on a second. I'm sorry, what was it again Hold on. Can we go through that?

Gina: 1:08:00

one one time. I just I can't, and he like okay. So there's just, this is a hot fucking mess, melissa, so tell us how you got, let go.

Melissa: 1:08:10

Yeah, this is quite a story in and of itself, so I'm here for it.

Gina: 1:08:14

Let's buckle it.

Melissa: 1:08:14

I mean just, a little bit of time to talk about this. So, as I said, I was a contractor, so all of the full-time employees and everybody in my department except me and one other person were full-time, so all the full-time employees got an email on Thursday. I guess this would have been November 2nd or something.

Nicola: 1:08:34

I don't have the exact date, but and now we're also on stress mode because we're like two minutes away from your elections.

Melissa: 1:08:41

Yes, exactly, exactly so we've got double, double stress okay.

Melissa: 1:08:46

The email says tomorrow morning there's going to be a reorganization. Tomorrow morning you're going to get an email in your inbox at 9 am and it's going to have your instructions for your future here at the company. If you are fired, it'll come to your personal email because you won't have a company email. If you still have a job, it's going to come to your company email and it's going to contain your new, your instructions for your new, your new role, basically your new department. This is awful. It's awful, it's terrible.

Nicola: 1:09:19

What kind of change management is that? None, the answer is none. There is no change management.

Gina: 1:09:25

This is I'm picturing this right out of that the consultant TV show. Oh my god this is absolutely. If you're not here in 10 minutes, you're done.

Nicola: 1:09:34

No, he gave them an hour. If you're not here in an hour, you're fired, okay so they get this email.

Melissa: 1:09:43

And so all of us formed this WhatsApp group outside of Twitter, so that we could talk in case we were fired. You know, to commiserate, we're all. We all feel awful and people here on visas, you know, people have kids. It's just traumatic to do your job anyway. And so we all from this WhatsApp group we're talking. We're supposed to get. They were supposed to get fired at 9am. Now I don't know what's going to happen to me. I didn't get this email. I don't know, no idea. So I'm there, but I'm there to support them into whatever.

Melissa: 1:10:16

And so what actually happened is at 11pm local time, people started losing access to Slack and email and being cut off, being booted out of the computers. So that'll tell you how hard we were working. I'm on this WhatsApp people on the east coast in New York City hey, I just got kicked off Slack. Hey, I just got kicked off. I just got booted off on my computer while I was running code, I just got kicked off, and you know, by half the people. And then it goes to Chicago, which is in our central time zone. I just got kicked off, and, as it turns to be 11 in the mountain time zone, I got kicked off. So it's this slow motion tidal wave that's coming across the United States and I'm like, am I going to be high enough to not ground? Like, am I high enough ground here to?

Nicola: 1:11:07

escape or not. The tsunami is coming for you.

Gina: 1:11:11

Yes, so they didn't even honor the email thing, it was just you lost access.

Melissa: 1:11:18

We got kicked out.

Gina: 1:11:20

Okay, just wanted to make sure, okay. So then what happens?

Melissa: 1:11:23

My boss was fired and my boss's boss was fired as well. Somehow I escaped, I don't know why. I guess because I was a contractor. They just kicked out. My boss texted me, I got kicked out. I guess I'm fired, and he has a two-year-old daughter and so of course that's awful, and he lived in Seattle and so it's terrible, and so that's like Friday. That's Thursday night, and so Friday is a mess. Everybody's scrambling around. The weekend happens On Monday. I'm still there, but I have no official role. I don't know my roles. I didn't get this email, but I still have access to all the systems. So again, I just nose down. I'm working hard. I was like who's my boss? Who do I report to? What am I supposed to be doing? I emailed the HR rep and I still have this because she filed a ticket in Jira, which is like a ticketing system, and it has Elon Musk's name on it and it says who does this employee work for? Who does this employee report to? It has Elon's name on it and I was like this is insane.

Gina: 1:12:46

That's so right. You're employed, but you have no idea who you're reporting to.

Melissa: 1:12:50

You have no idea who you're reporting to who?

Gina: 1:12:51

does he know who I report to? Oh my god. So, nicola, to answer your question, there was no change management, none whatsoever, zero. It was fear mongering and surprise retaliation. It sounds like okay, so you're there, you don't know what the hell you're doing. Then what happens?

Melissa: 1:13:09

So because Twitter is this public company, it's in the spotlight, people start saying, hey, what about the US election that's coming up? This is outside pressure, shouldn't we have some people here? And he's like fine, nobody else in political misinformation is going to be fired for this time. Oh, great, I get like a week, yeah, okay great.

Melissa: 1:13:33

I don't know. So this week goes by, the election happens, then we do. You know, there's always like collection to mop up and clean up and all this kind of stuff happens. I make it through the week somehow. I go that. That Saturday I was at the mall with my daughter, who at that time was 11, and her friend. I'm at the mall, I looked at my phone and I get a pop-up that says one or more of your access tokens has been removed about 7 pm and I open it up and I try to get into Slack on my phone and I try to get an email on my phone and I couldn't. And that's how I was fired on my phone at the mall at 7 pm on a Saturday.

Gina: 1:14:14

So wait, did you, just so. You never got an email. You never did anyone ever reach out to you. Did the? I know you were working through a staff.

Melissa: 1:14:23

They did later, but not till after I was already fired.

Gina: 1:14:28

Right, but did anyone say like? So what did they say to you when they reached out to you?

Melissa: 1:14:33

The email said your position at Twitter and it was just.

Gina: 1:14:36

And you're like so I know I don't have one. Yeah, like I'm not an idiot, like you could have started with just you're fired.

Nicola: 1:14:43

Thank you, oh my god. You know, what would have been really fun at least they should have taken a bit of piss out of this is they should have gotten Trump to just do a you're fired. You're fired, melissa. That's so funny.

Gina: 1:14:58

Maybe you want to laugh at that.

Nicola: 1:15:00

I would have had a chuckle at least, yeah.

Melissa: 1:15:03

I wanted to say also is like for that week of of uncertainty. As a contractor, I have to submit a time card every week and get it signed. So I didn't even know who was going to sign my time card, approve my hours. I contacted my employment company and I'm like, hey, what's going on? Am I going to get paid for this week? And they said well, I don't know if you get paid. If we get paid, you'll get paid. And I was like, then you'd better make sure that you get paid.

Gina: 1:15:34

Yeah, did you get paid I?

Melissa: 1:15:37

did end up getting paid. I will say Okay good, but I didn't. I didn't know, I didn't know what was happening.

Gina: 1:15:44

Yeah, and like most Americans, regardless of their salary are still living, especially like an hour generation. Are still living paycheck to paycheck.

Gina: 1:15:53

Absolutely Like in San Francisco is more expensive than Manhattan to live, and I mean, I'm sure you're making a good amount of money, but when you're living in like the most expensive place it doesn't matter. I mean, I remember right before I moved to Florida, when I was in New York, still in Manhattan I was probably making close to 200,000 and I was still pretty poor, like I was still like living paycheck to paycheck, you know, yes, so it's difficult. And do you know if the full time employees were given any kind of severance, or were they just fired and that's it?

Melissa: 1:16:26

So they were given three months of severance and although there were some issues with some people not receiving it on time, to my knowledge most of them have received them, have received that three months severance by now, although some haven't. But I, as a contractor, I got nothing Right. I got no severance. My company sent me a box of Geardelli chocolate, which Geardelli's nice, but it's not three months of severance.

Gina: 1:16:57

You're in San Francisco. I mean Geardelli's everywhere they should have imported something different, right, like that you wouldn't have access to.

Nicola: 1:17:04

To kids from New. Zealand.

Gina: 1:17:08

Or something like even I don't know something else I feel like yeah, or like even I'm trying to think is there like a New York chocolate place that everyone loves? I can't think of one, but um, yeah, that's kind of tacky, I mean.

Nicola: 1:17:21

I'm sure you ate it. It's not tacky. Okay, so we've gone through this whole shitty change management process. It sucks. Do you still have friends there? Do you still have people you chat to?

Melissa: 1:17:34

Yeah, so we still have this WhatsApp group. There's still people who are there. We don't chat as much, but you know we still do chat. People post updates every once in a while but yeah, there's still people there, they're. I mean again, of the eight people who are left, six of them are here on H1D visas. So they they don't really have a choice of like, hey, maybe I should look for another job. It's extra difficult if you're here on an immigrant visa.

Nicola: 1:18:03

Yeah and what about you? Are you doing okay now?

Melissa: 1:18:09

Yeah, so you know, like you said, it's an just incredibly expensive place to live. Most of my adult life I've worked two jobs. I teach part-time on the side. So, um, yeah, I mean, for you know, this is like November 12th that I was let go and I'm like the holidays are coming, nobody hired the end of year anyway. I'm like panicking, I'm trying to take. I took my kids to see some movie, a movie and I just remember having a panic attack in the movie theater, like I can't, I'm not gonna be able to afford to continue to pay rent for this place, let alone to provide my children a nice Christmas.

Melissa: 1:18:48

Sure that's terrifying, I'm just like I'm like panicking, and then like you don't want to show your children. Of course you know you want to be that good, strong parent for them and and it was a brutal time to just to be frank, but like, fortunately I did get a job. My skills are in demand, so I was able to get a job. I'm employed now. I'm doing great at my new job.

Nicola: 1:19:09

Great. Are there, are, there, are. Is there any chance of them being taken over by Elon? Because I'm like now it's like a like a toxic, like bacteria. It's just coming, it's just spreading.

Melissa: 1:19:21

Just spreading everywhere? Well, I hope not.

Gina: 1:19:26

We work with medical universities.

Melissa: 1:19:27

So I don't think he's interested in that.

Gina: 1:19:29

He's probably not, and I kind of can't wait for him to lose 44 billion dollars when he runs Twitter or X, I should say, into the ground, because that's the only way I can see this ending.

Melissa: 1:19:41

He just announced that his ad revenue was down 60 percent.

Nicola: 1:19:45

He gave away blue ticks for like two, two dollars.

Melissa: 1:19:49

Yeah, yeah, yeah, yeah, it's not surprising.

Gina: 1:19:53

And is he unilaterally making decisions for X slash Twitter?

Melissa: 1:19:58

Yeah, people who talk about. Of course there's maybe not of course, but there's a new CEO, linda Yoccarino. She comes from NBC, she has ad experience. He brought her on because she's all these relationships with advertisers and he wanted to bolster up somebody, but he very much remains in charge. It's very obvious. He's the public base of the company. He's tweeting out directives and people who again, people who do work there talk about. You know, he's just this incredibly mercurial director and owner and he can be incredibly charming if he wants to be, but he can all. He turns on a dime and he's he's dark Elon and that's the worst kind of leader to have.

Gina: 1:20:37

Because you're not, you never feel safe in that environment because you're like, oh, he likes me today, and then you're like I wonder if he's gonna like me tomorrow or you know, on a bigger scale of course, but you know it's. I grew up with someone who was very much like that, like would switch on a dime, and it's so. It's like it's traumatic. It's traumatic to be around someone who you have to kind of try to guess their mood. Guess what you can say, what, guess what you can't. Guess what you do, what you don't do. It is, I feel, bad for all the people who stay there.

Melissa: 1:21:10

It is. I really do yeah, so do you think? He's obviously a brilliant guy, but just no.

Gina: 1:21:15

No, I know, but maybe he's just not a good leader, right?

Nicola: 1:21:18

I don't think he's a good leader at all. I think he has been pended to because he's got a whole fuck ton of money to. Oh my god, he is literally the guy from the consultant.

Gina: 1:21:30

No, he is he is.

Nicola: 1:21:31

They are one and the same and he's not a good leader. That's not gonna you're not gonna get. You're not gonna get the best out of people. You're not gonna get the best out of anything. And now you're in a situ where you know you're just gonna see a decline in in morale. You're gonna see a decline. You see more staff quitting.

Gina: 1:21:49

But that's why I'm like how does he think this is going to be successful? Like it's just like it's like the company's like spiraling the dream hole, you know, it's like I don't know. The sink, the sink, let that sink in.

Melissa: 1:22:04

The sink. That's so funny.

Gina: 1:22:09

So now that you're on the other side of it and you went through that painful time but you're now gainfully employed, do you think you, knowing what you know now, looking back, would you have done anything differently? Would you have quit of your own accord or like what do you? Is there anything you would have done differently?

Melissa: 1:22:29

You know, I'm not really close to my coworkers there and I think again, I still believe in what we're doing. I still believe in keeping it safe from political misinformation. I think that's a good thing that we were doing. So it's hard to say that I would have given that away, but I think from my own sanity and my own safety, I would have just hey, this person doesn't care about me. He clearly doesn't care about my job security. I'm gonna devote myself full time to looking for work. I would have just tried harder to get another job.

Gina: 1:23:01

Yeah, yeah.

Melissa: 1:23:03

Instead of doubling down and working harder.

Gina: 1:23:05

Yeah, because you don't. But in that period you're so stressed You're like I don't know what's happening. I'm being told new things every day, like nobody knows who's coming and going. Who knows how you would handle it, you know? Like unless you're in it, but yeah. But looking back I could see like, yeah, you probably should have devoted your entire time to finding a new job. Yeah, but are you happy that you had the experience of working at Twitter?

Melissa: 1:23:34

I really love working. Having worked at Twitter, I've used the platform since like 2009,. A long time user, I can hardly stand to be on there anymore. I used to use it a lot. It's painful to be on now, but I'm glad have you moved over to Threads. I've been on Threads, I've been on Blue Sky Post Tribal, all the ones that are out, yeah, they're just not. It's not. None of them is quite there yet.

Gina: 1:24:02

Is that the same yeah?

Melissa: 1:24:03

No, we'll see.

Gina: 1:24:04

That's because there's not data scientists like yourself.

Melissa: 1:24:08

There's not data scientists. They're not you?

Gina: 1:24:09

Yeah, that's true, they're not you, okay, well, I feel like we just I feel like we had a school.

Nicola: 1:24:17

We've had another school lesson today where we're like we came into this not knowing what data science was. I feel like we've lived still not knowing, but having some understanding.

Gina: 1:24:27

Well.

Nicola: 1:24:28

I mean.

Gina: 1:24:28

I knew what data science was. I did like I actually recently did a course on it, just so I wasn't antiquated with certain things, but I would not have known that super niche that you are in, Melissa. It's so interesting and it's like, like.

Gina: 1:24:43

I said previously, like we go on these sites and you know things are being cleaned up and we don't even know that that's happening behind the scenes, you know, and it's like there's a whole team of people who are making sure that it's safe for you to post, you know, your thoughts on Taylor Swift or whatever.

Gina: 1:25:00

And then she's a doofus, you know, because doofus is now our flag, our slurrward yeah, but I mean, it's true, it's like I wouldn't have even thought of, like oh, this is just safe, I can say what I want to say about whoever you know, or what I did today or whatever, and you don't think about what really goes behind it. So it's been very insightful for me and I thank you for explaining it so like beautifully, because I totally got what you were doing once you yeah, once you got there.

Melissa: 1:25:29

Great. Well, yeah, I mean, I love to talk about data science and I'll get enough opportunities too, so thank you for being great listeners.

Gina: 1:25:38

You're welcome.

Nicola: 1:25:39

Well, we really yeah, go ahead. Nicholas. I was gonna say we really appreciate your time today because it's just, I feel like this has been a great chat.

Gina: 1:25:47

It has. I feel like it was fun. Yeah, it was fun. Is there anything you want to say to anyone or how can people find you if they want to hire you or have you come?

Melissa: 1:26:01

in and consult and not be a terrible consultant. Yeah, what. Yeah, I'm still occasionally on Twitter at mingle Melissa Engel mingle74. Oh, my God Talbot yes, okay, funny, you can find me there. I'm go find me at LinkedIn. I'm happy to take on consulting projects and yeah, I'm just sort of generally available to offer my expertise as needed. Yeah.

Gina: 1:26:34

Okay, great. Well, we will put all of that information in this show notes so people who might hear your lovely tweet, tweet, tweet. No, your voice will can reach out. Yeah, so this has been wonderful.

Melissa: 1:26:51

Thank you so much.

Gina: 1:26:53

Thank you, I'm not going to ever use Twitter again. I used it for like months. Yeah, we probably should. No, not we probably shouldn't, it'll be interesting. Maybe in like a year from now, if we're still doing the podcast and Twitter acts whatever is in a different like, well, maybe we have to invite you back on and see what happened.

Melissa: 1:27:14

I think it can still be saved. I really do, yeah, yeah.

Gina: 1:27:18

We'll see.

Nicola: 1:27:18

We'll see It'll be saved if you know my skits on a on one of his rocker If he gets out of his own way it'll probably be saved, yeah, I think, if he extracts himself and let's and hires appropriate people.

Gina: 1:27:31

it's like exactly what we had in our toxic workplace If the owner got out of her own way, the business would be totally successful. Yeah, yeah Just as long as we're able to do that, just as long as you're hiring people with the correct experience and understanding of how to get your business to where you think it should be, and if you don't do that. You're dead in the water.

Melissa: 1:27:51

Right Actual people not like friends and family.

Gina: 1:27:54

But yeah, if you're not doing that, you're dead in the water. So let's see what happens.

Nicola: 1:27:58

What's the?

Gina: 1:27:59

space.

Nicola: 1:28:00

Yeah.

Gina: 1:28:00

Yeah, all right. Well, thank you so much, melissa it was such a joy and so insightful, and we will chat with you later.