Speaker 1: The first law you should know about is the law of unchosen outcomes. That is, as a researcher, you do not get to decide what experiments work and what experiments fail. You do the experiments to find that out. We get attached to what should be easy, what should be the outcome, but that is not the reality of research. Even the simplest, the easiest of research, can go wrong for reasons that are outside of your control and that you'll never know. For example, in my PhD, I made a solar cell. It was a great solar cell. I controlled all of the variables that I could, but could I repeat it? No. And importantly, there was a moment where I had to let it go. I could have chased my tail for years and years and years trying to emulate that same sort of set of conditions. It got to the point where we were even trying to sort of like control the time of the year that we were doing the experiment because we thought maybe that was like the important factor. You have to do research with an open mind. Every experiment you do, you have to approach it as if you cannot control that outcome and you have to remain agile and move according to where your research is telling you to go. It's really hard when your supervisor wants you to follow a particular line that is not working and they're convinced that it's going to work. In fact, one of my co-supervisors said to one of my supervisors, like, I think this should happen. And my supervisor said, no, no, be quiet. This is why we do research. You can't just sort of like project what's going to happen. That is research. So stay indifferent to the outcome, remain agile, and you'll move much faster through your research. I promise you. This law I love. It's the law of minimum effort. You have to make sure that through the processes you create during your PhD that you minimize the friction that you have to go through. Any little friction point just is a point where you can decide, you know what? I'm going to stop and do something else. Remove that friction as much as you can. Create a nice space for your research that's as easy as possible. For me, I often found that going straight to my desk in the morning was a friction point. I couldn't leave after I sat down in my nice comfy desk with my cup of tea. So instead, I removed that friction point and I put my laptop in the lab so that in the morning I would always have to go to the lab. And once I was in the lab, the momentum started. So all of those little friction points throughout your day, throughout your research, just look at them and try to remove them. It's going to be much smoother for you. You get into a nice habit. All of these things are just a way of moving your research along nicely. And it doesn't just mean you. It extends to your supervisor or anyone you're collaborating with. People are lazy. There's no doubt about it. Any person has got a tendency when they reach a friction point to stop moving. To say it's all too hard, they'll do it later. So this is a prime example. If I wanted to get nominated for a certain award or for a certain thing, I would approach my supervisor with the information they needed. And sometimes, this is probably a bit cheeky, I would write my own application on their behalf and say, hey, I've written this application for you just so to like help you out and make sure it's got all the key points in. Do you mind submitting it for me? Looking over it, changing it, that sort of stuff. And so removing the friction in that point meant that they were just right away going to send it off. It was easy for them. So with your supervisor, remove friction as much as possible. Don't go in with problems. Come in with problems and solutions to your meetings and things will just move so much easier, so much quicker and it always works. Low friction and low effort. Brilliant. The law of primacy and recency. I use this all the time when I'm trying to get people to listen to certain points of what I'm saying. I use it now. I use it in talks and that is the first thing they hear and the last thing they hear are the most important. People tend to forget the things in the middle. Take a list, for example. The first and the last tend to be the most remembered points of that list. So if I'm communicating just on a daily basis even with my supervisor, with colleagues, I will lead up front with the most important information. We have a tendency to bury the information and it just gets lost. So go up, most important stuff first, talk about that and finish with the most important stuff again. That means that will be on the front of their mind. A supervisor, a collaborator, they've got their own stuff going on. They don't remember the ins and outs of your project. So just make sure you hit the first most important thing first and you remind them at the end of the conversation, at the end of the presentation because those are the bits they're going to remember and it kind of means like you're hacking other people's brains for your priorities. Brilliant. I've said this on the channel before and goddammit, I will say it again. This is probably the most important rule that I live by even today and that's the Pareto principle. It is the 80-20 principle. Too many times in research I've seen people try to sort of like bring up their trailing and failing experiments to the success of their sort of like other experiments. No, forget them. They're dead. Have a look at your research ideas. Have a look at the experiments you've done recently and look to see where your successes are. I guarantee you that about 80% of all of your successes come from about 20% of ideas and research. That is what you should be focusing on. Forget everything else. Bad ideas are left behind. You let this grow and then within that once it's grown you'll start to find that there's a subsection, a 20% in there where you'll get in most of your ideas and most of your successes. Grow that. Forget the rest. Doing this systematically throughout your PhD in any research project will mean that you are progressing in the right direction and it will keep you moving forward. Do not try to resurrect a dead experiment. It'll never work. It will be wasted time. Anchoring bias. That is when you get an initial result. But that initial result in our minds becomes like the anchor by which we view all of the next results. The problem with this is this first result can sometimes be wrong and we can waste a lot of time because we put so much emphasis on this first result. Scientists do it all the time. So here's a relatively embarrassing story for you. I was trying to create an interwoven network of silver nanowires and carbon nanotubes to create these nanowires of superconductive material. We put them through this sort of like spinning tube, this vortex fluidic device and we got at the end some fibers. Oh my god. This was amazing. I was so over the moon. I couldn't believe it. It was the first experiment we did as well. And I was like, this is it. I'm a genius. We started to sort of like have a look at these wires and couldn't work out really what they were. They didn't look like silver nanowires. They didn't look like carbon nanotubes. But everyone was like, yes, you can see the chirality at the end from the way this the tube was spinning. Supervisors were getting excited and then I was like, you know, I'm going to take it to this specialist in microscopy and we're going to see what he says. And I showed him to him. He said those look like fibers from tissues. And I was like, of course not. Don't be silly. This is high-level nanotechnology in action. This is not just tissue paper. And then he showed me tissue paper next to it on the microscope. And what happened was we were pulling out paper towels above the tubes that we were using to collect our results and the fibers were falling in there. And it's embarrassing to think of that. But at the time, that's what happened. And we spent so much time trying to convince people that that's what it was because they had anchored on our first result and it was so difficult. We could have spent ages just chasing our tail on this result. But that's what happens. People get attached to the first result they think when it's actually could be wrong. So don't get attached to your first results and use that to make sure that you're always just staying agile and you're moving with where the data is telling you to move. If you like this video, go check out this one where I talk about the five skills that you won't learn throughout your PhD, but are crucial for success. It's a really good watch and I think it's something that no one else tells you. So there we have it. There's everything you need to know about the powerful laws for research success. Let me know in the comments which ones you would add and what you think of that. And also remember there are more ways that you can engage with me. First of all, sign up to my newsletter. Head over to andrewstoughton.com.au forward slash newsletter. The link is in the description. And when you sign up, you'll get five emails over about two weeks. Everything from the tools I've used, the podcast I've been on, how to write the perfect abstract and more. It's exclusive content available for free. So go sign up now and also head over to academiainsider.com. That's my project where I've got ebooks, got resource packs, I got blogs, I got forums and then everything is over there to make sure that academia works for you. All right, then I'll see you in the next video. Transcribed by https://otter.ai