SDS 376: Expose Yourself to New Ideas Regularly

Welcome back to the SuperDataScience podcast everybody, super pumped to have you back here on the show. As you may know, from previous episodes, I’m reading this book called Deep Work by Cal Newport, a huge fan of it. In a nutshell, it helps you understand how and why to focus on individual task and work deeply without any distractions and how that can help get better results and also feel more fulfilled. I’m definitely getting a lot out of it. And I recommend it to absolutely anybody who wants to work more effectively and efficiently. 

And at the same time, so this chapter that I came across, it advocates for something different or in addition to that deep work. So on one hand, you got to work, the whole premise is working deeply, but on the other hand, in this chapter Cal talks about exposing yourself to new ideas, regularly, interacting with people and so on. And I found this very interesting, and that’s why I wanted to share it here. 

So it starts off with two stories. And the first story is about building number 20 at MIT. It was quickly put together during World War Two to be a shelter, temporary shelter. And after World War Two when there was a huge influx of people who wanted to study at MIT, there was just not enough space and other buildings and respective departments so this building was used for different departments. And you had people from different areas, walks of life, bumping into each other here all the time from nuclear science to linguistics, to electronics and so on. And what this led to was a massive number of breakthroughs and innovations. For instance, it generated innovations in topics ranging from Chomsky grammars to video games, to long range navigation, just to name a few. 

And the second story is about another building that was designed on purpose this time but around the same time as building number 20. It was designed by the director of Bell Labs, Mervin Kelly, in New Jersey. And there, Kelly didn’t want that university style of old departments being separate. Instead there was one contiguous building one, one connected building with a very long hallway. And there people with lots of different mixes and backgrounds from scientists to engineers from different fields would be staying in this one building that’s fully connected and therefore whenever they would want to go somewhere they would bump into each other. 

It’s not that they didn’t have their private space where they could work and focus and get rid of distractions. That was still the case. They had their own labs or their own offices, but when they wanted to go for a walk or go for lunch or go to some other place in the building, they would inevitably bump into other people from other divisions, from other backgrounds, other areas. 

And what this led to was an even greater number of innovations. For example, here are some of the accomplishments from Bell Lab in the years following World War Two. This first solar cell, laser, communication satellites, cellular, communication systems, fiber optics, a Nobel Prize for empirically validating the Big Bang Theory and as Cal Newport puts in his book, perhaps the most important one is the transistor, which gave us the modern computer. And even just looking at the transistor that required people who were scientists from solid state physics, quantum theorists, world-class experimentalists, all working together. 

So what is the main takeaway for me from here? Well, it was that I need to more regularly expose myself to new ideas, to talking with people. I tend to get carried away by locking at myself up in a room and focusing on deep work. That’s why this book resonates with me so much. I love deep work. I get really fulfilled. I get great results from it. But here he also reminds me that, or reminds us that, we can’t just invent everything by being by ourselves. Some inventions, yes, come to you by yourself. But others, you need to be exposed to other ideas, perspectives, different fields, different worldviews that you might not have, but being exposed to them will challenge your thinking will get you thinking in different ways. 

And we don’t have to be inventing the transistor to benefit from this. Whatever we’re doing, if we expose ourselves to peers or people in other industries, other areas, then we can enrich our thinking and generate new ideas, new solutions, new products, new ways of thinking for ourselves. And so that’s something to think about. That made me stop and think how often do I expose myself to new ideas? And it’s not that often. I tend to stay in my own head and develop my own ideas further and further, but indeed I should expose myself more. 

And I started thinking like, how can I do this? Maybe now attend some virtual gatherings. Maybe after coronavirus settles down attend more meetups, more talks, more places where entrepreneurs, or people from different fields. It doesn’t even have to be people from the same field, it can be people from absolutely different fields. Maybe a meet up for musicians, or maybe an art group where I could do some painting or something like that. Or maybe I meet up with data scientists or entrepreneurs and understand what I’m missing there, what I can learn from that. So definitely an area that I can improve. 

And my question to you is, is this an area that you’re already doing great at? Or is it something you can improve at as well? How often do you expose yourself to new ideas? How often do you get out of your comfort zone or you make an effort to be communicating with somebody you haven’t communicated with before? Because if it’s the same people that you’re always constantly talking with, those are not really new ideas. Maybe there’ll be new ideas sometimes, but what if it’s somebody from the other side of the planet? What if it’s somebody in a completely different field? Or if it’s somebody who has a completely different world view? How often do you expose yourself? So something I encourage to consider and think about. And if your answer is like me, that you don’t expose yourself often enough, there are definitely solutions out there. And I encourage you for you to look for them. 

But a great starting point I can already suggest to you now, and I am a biased because it’s something that we’ve created, but the good news is absolutely free. So if you haven’t signed up for DataScienceGO Virtual yet, then I highly recommend checking it out. If you’re listening to this podcast on the day it came out, on the Friday on the day it comes out, on the Friday, then tomorrow on the 20th June and 21st June, we’re hosting DataScienceGO Virtual for the very first time where you’ll be able to get new ideas from speakers, from workshop facilitators. And from peers, from people, from other people in data science, because we have this networking time where even virtually, even though it’s virtual event, you’re going to these networking sessions where you click a button and you get assigned somebody else randomly who’s also open to networking and you get to chat to them for three minutes. 

And if you want to exchange details, you can continue the conversation later on. If not, not, but then you get another person, another person, another person. You can meet a lot of people this way, who are also interested in data science, but might have different worldviews. And might be working in different industries. And might be solving different problems and you can enrich your library of ideas, expose yourself to new ideas and grow that way, change your perspectives, or challenge your opinions and worldviews and become a better data scientist that way. So that’s what this event is going to be like. Once you apply to join, and the thing is we can’t invite absolutely everybody at this stage because our first event, we need to make sure that we can handle the amount of people that will be there. We already have over three and a half thousand applications.

So once you apply, you’ll be able to fill in a form and say whom you want to network with. A mentor, a peer, a manager, a mentee, and basically you can specify whom you want to network with. And even if you don’t get into the event for some reason, or if you’re listening to this podcast after the event is over, still highly recommend registering for it. Even if it’s over because you’ll still get the recordings. You’ll get the recordings of the workshops and the talks and you can get those new ideas from our speakers. So highly recommend checking out, it’s datasciencego.com/virtual. Absolutely free, some amazing speakers coming. 

But don’t stop it that if this event is not your cup of tea, for whatever reason, then there’s definitely tons of events out there that you can attend. I highly encourage you to check them out. There’s free events. There’s paid events. There’s events in absolutely different industries, meetups, and so on. So expose yourself to new ideas, whatever the case. And if you are coming to DataScienceGO Virtual, then I’ll see you there. And until next time, happy analyzing.