With her new company, Chou wants to fix some of the problems she’s experienced firsthand in the tech industry—including the sort of online harassment of which she has been a target. Here, we check in with Chou, who is based in San Francisco, to learn more about what it takes to make change in the tech sector and what entrepreneurs like her are up against.
Tracy Chou, as told to Wudan Yan: When we last spoke, I had just left Pinterest. I’ve always been drawn to smaller companies: I joined Pinterest when it had about 10 employees and left when it had about 1,000. It felt like time for me to move on and do something new.
I’ve worked for so many startups and have come to recognize some of the structural issues around startups and funding and how those factors influence what problems get solved. A lot of founders naturally work on problems that directly affect them: it’s easier to know what’s important or what could be improved by technology.
In thinking about my next steps, I thought about products I’ve worked on and checked that against questions like, Do I care about this? Is there something to be made that can be commercially viable? There are lots of really important issues that will not be solved naturally through a startup.
I ended up on Block Party, which pulls together a few different threads from my background. I’ve worked as an engineer at various social platform companies, and I’ve worked on monitoring, moderating, and increasing the quality of content, and figuring out how product design influences community behavior. Not only did I build moderation tools at Quora that reviewed content quality, but I also took punitive actions against people who violated the site’s policies.
I’d also spent a lot of time looking at how the lack of diversity and representation in teams meant that products were built in a skewed way. For instance, nondiverse teams of people who generally don’t get targeted with abuse and harassment don’t tend to build protections against that in their apps.
The last part of my background that led me to Block Party was just getting targeted more with harassment. Over the last year, I’ve definitely gotten more anti-Asian harassment online. Some of it was truly targeted at me by individuals, and other times I would attract trolls just by having a presence online.
If you could be reborn as anybody in the world tomorrow, how would you design the world today? You wouldn’t want to design a world that’s vastly unequal, where most people are at the bottom, because that could very likely be you if you were born as anybody tomorrow.
I got online very young, and at first the internet was a fun way to connect with friends. I was on AOL Instant Messenger, which was a better way to chat with my friends in high school: I didn’t have a cell phone, and I couldn’t hog the phone line that I shared with my family. I was also on some of the blogging platforms, like Xanga and LiveJournal. They were nice outlets at the time.
Pretty early on, though, someone set up an anonymous Xanga page dedicated to hating me. I think it was someone from school, because it referenced things from high school. A lot of it was hating on me because I did well academically. It didn’t bother me as much at the time as it did when I got older and looked back on it. Back then, I thought this person was just insecure and jealous. I thought it was a bit sad and messed up that someone would write full posts dedicated to trying to take me down.
I didn’t report it. Who would I have reported it to? It didn’t even cross my mind to go to my school and report it. And I didn’t necessarily want my teachers or school administrators to see the page either, since it was pretty hateful content.
My parents didn’t raise me to be someone who was outspoken and challenged the status quo. I definitely wasn’t encouraged to speak up against the system in any way. Like many other children of Asian immigrants to the US, I grew up believing that this is not my country, and my parents and I are here trying to find opportunities for ourselves. We didn’t have a safety net. I grew up more with a head-down mentality of do good work, work hard, and try to make it.
My dad, who’s an engineer, gave me a philosophical thought experiment when I was quite young: If you could be reborn as anybody in the world tomorrow, how would you design the world today? You wouldn’t want to design a world that’s vastly unequal, where most people are at the bottom, because that could very likely be you if you were born as anybody tomorrow. You’d want to design a much more equal world. That got me thinking I didn’t like that the world was so unequal and so many people were much less lucky than me.
That feeling has made me take the privilege that I have and pay it forward to make the world a little more just. I went to Stanford; I’ve worked at companies that people within tech find credible. So I can try to amplify more voices or different perspectives.
Everything you need to know about artificial wombs
The technology would likely be used first on infants born at 22 or 23 weeks who don’t have many other options. “You don’t want to put an infant on this device who would otherwise do well with conventional therapy,” Mychaliska says. At 22 weeks gestation, babies are tiny, often weighing less than a pound. And their lungs are still developing. When researchers looked at babies born between 2013 and 2018, survival among those who were resuscitated at 22 weeks was 30%. That number rose to nearly 56% at 23 weeks. And babies born at that stage who do survive have an increased risk of neurodevelopmental problems, cerebral palsy, mobility problems, hearing impairments, and other disabilities.
Selecting the right participants will be tricky. Some experts argue that gestational age shouldn’t be the only criteria. One complicating factor is that prognosis varies widely from center to center, and it’s improving as hospitals learn how best to treat these preemies. At the University of Iowa Stead Family Children’s Hospital, for example, survival rates are much higher than average: 64% for babies born at 22 weeks. They’ve even managed to keep a handful of infants born at 21 weeks alive. “These babies are not a hopeless case. They very much can survive. They very much can thrive if you are managing them appropriately,” says Brady Thomas, a neonatologist at Stead. “Are you really going to make that much of a bigger impact by adding in this technology, and what risks might exist to those patients as you’re starting to trial it?”
Prognosis also varies widely from baby to baby depending on a variety of factors. “The girls do better than the boys. The bigger ones do better than the smaller ones,” says Mark Mercurio, a neonatologist and pediatric bioethicist at the Yale School of Medicine. So “how bad does the prognosis with current therapy need to be to justify use of an artificial womb?” That’s a question Mercurio would like to see answered.
What are the risks?
One ever-present concern in the tiniest babies is brain bleeds. “That’s due to a number of factors—a combination of their brain immaturity, and in part associated with the treatment that we provide,” Mychaliska says. Babies in an artificial womb would need to be on a blood thinner to prevent clots from forming where the tubes enter the body. “I believe that places a premature infant at very high risk for brain bleeding,” he says.
And it’s not just about the baby. To be eligible for EXTEND, infants must be delivered via cesarean section, which puts the pregnant person at higher risk for infection and bleeding. Delivery via a C-section can also have an impact on future pregnancies.
So if it works, could babies be grown entirely outside the womb?
Not anytime soon. Maybe not ever. In a paper published in 2022, Flake and his colleagues called this scenario “a technically and developmentally naive, yet sensationally speculative, pipe dream.” The problem is twofold. First, fetal development is a carefully choreographed process that relies on chemical communication between the pregnant parent’s body and the fetus. Even if researchers understood all the factors that contribute to fetal development—and they don’t—there’s no guarantee they could recreate those conditions.
The second issue is size. The artificial womb systems being developed require doctors to insert a small tube into the infant’s umbilical cord to deliver oxygenated blood. The smaller the umbilical cord, the more difficult this becomes.
What are the ethical concerns?
In the near term, there are concerns about how to ensure that researchers are obtaining proper informed consent from parents who may be desperate to save their babies. “This is an issue that comes up with lots of last-chance therapies,” says Vardit Ravitsky, a bioethicist and president of the Hastings Center, a bioethics research institute.
The Download: brain bandwidth, and artificial wombs
Last week, Elon Musk made the bold assertion that sticking electrodes in people’s heads is going to lead to a huge increase in the rate of data transfer out of, and into, human brains.
The occasion of Musk’s post was the announcement by Neuralink, his brain-computer interface company, that it was officially seeking the first volunteer to receive an implant that contains more than twice the number of electrodes than previous versions to collect more data from more nerve cells.
The entrepreneur mentioned a long-term goal of vastly increasing “bandwidth” between people, or people and machines, by a factor of 1,000 or more. But what does he mean, and is it even possible? Read the full story.
This story is from The Checkup, MIT Technology Review’s weekly biotech newsletter. Sign up to receive it in your inbox every Thursday.
Everything you need to know about artificial wombs
Earlier this month, US Food and Drug Administration advisors met to discuss how to move research on artificial wombs from animals into humans.
These medical devices are designed to give extremely premature infants a bit more time to develop in a womb-like environment before entering the outside world. They have been tested with hundreds of lambs (and some piglets), but animal models can’t fully predict how the technology will work for humans.
Why embracing complexity is the real challenge in software today
The reason we can’t just wish away or “fix” complexity is that every solution—whether it’s a technology or methodology—redistributes complexity in some way. Solutions reorganize problems. When microservices emerged (a software architecture approach where an application or system is composed of many smaller parts), they seemingly solved many of the maintenance and development challenges posed by monolithic architectures (where the application is one single interlocking system). However, in doing so microservices placed new demands on engineering teams; they require greater maturity in terms of practices and processes. This is one of the reasons why we cautioned people against what we call “microservice envy” in a 2018 edition of the Technology Radar, with CTO Rebecca Parsons writing that microservices would never be recommended for adoption on Technology Radar because “not all organizations are microservices-ready.” We noticed there was a tendency to look to adopt microservices simply because it was fashionable.
This doesn’t mean the solution is poor or defective. It’s more that we need to recognize the solution is a tradeoff. At Thoughtworks, we’re fond of saying “it depends” when people ask questions about the value of a certain technology or approach. It’s about how it fits with your organization’s needs and, of course, your ability to manage its particular demands. This is an example of essential complexity in tech—it’s something that can’t be removed and which will persist however much you want to get to a level of simplicity you find comfortable.
In terms of microservices, we’ve noticed increasing caution about rushing to embrace this particular architectural approach. Some of our colleagues even suggested the term “monolith revivalists” to describe those turning away from microservices back to monolithic software architecture. While it’s unlikely that the software world is going to make a full return to monoliths, frameworks like Spring Modulith—a framework that helps developers structure code in such a way that it becomes easier to break apart a monolith into smaller microservices when needed—suggest that practitioners are becoming more keenly aware of managing the tradeoffs of different approaches to building and maintaining software.
Because technical solutions have a habit of reorganizing complexity, we need to carefully attend to how this complexity is managed. Failing to do so can have serious implications for the productivity and effectiveness of engineering teams. At Thoughtworks we have a number of concepts and approaches that we use to manage complexity. Sensible defaults, for instance, are starting points for a project or piece of work. They’re not things that we need to simply embrace as a rule, but instead practices and tools that we collectively recognize are effective for most projects. They give individuals and teams a baseline to make judgements about what might be done differently.
One of the benefits of sensible defaults is that they can guard you against the allure of novelty and hype. As interesting or exciting as a new technology might be, sensible defaults can anchor you in what matters to you. This isn’t to say that new technologies like generative AI shouldn’t be treated with enthusiasm and excitement—some of our teams have been experimenting with these tools and seen impressive results—but instead that adopting new tools needs to be done in a way that properly integrates with the way you work and what you want to achieve. Indeed, there are a wealth of approaches to GenAI, from high profile tools like ChatGPT to self-hosted LLMs. Using GenAI effectively is as much a question of knowing the right way to implement for you and your team as it is about technical expertise.
Interestingly, the tools that can help us manage complexity aren’t necessarily new. One thing that came up in the latest edition of Technology Radar was something called risk-based failure modeling, a process used to understand the impact, likelihood and ability of detecting the various ways that a system can fail. This has origins in failure modes and effects analysis (FMEA), a practice that dates back to the period following World War II, used in complex engineering projects in fields such as aerospace. This signals that there are some challenges that endure; while new solutions will always emerge to combat them, we should also be comfortable looking to the past for tools and techniques.
McKinsey’s argument that the productivity of development teams can be successfully measured caused a stir across the software engineering landscape. While having the right metrics in place is certainly important, prioritizing productivity in our thinking can cause more problems than it solves when it comes to complex systems and an ever-changing landscape of solutions. Technology Radar called this out with an edition with the theme, “How productive is measuring productivity?”This highlighted the importance of focusing on developer experience with the help of tools like DX DevEx 360.
Focusing on productivity in the way McKinsey suggests can cause us to mistakenly see coding as the “real” work of software engineering, overlooking things like architectural decisions, tests, security analysis, and performance monitoring. This is risky—organizations that adopt such a view will struggle to see tangible benefits from their digital projects. This is why the key challenge in software today is embracing complexity; not treating it as something to be minimized at all costs but a challenge that requires thoughtfulness in processes, practices, and governance. The key question is whether the industry realizes this.
This content was produced by Thoughtworks. It was not written by MIT Technology Review’s editorial staff.