Am I wrong when I say that algorithms are representations of exactly how our brains work? Or how they should, at the very least. Because I’m a believer of them being implicit enough for anyone to understand, if they make the effort. Algorithms untangle chaos in our brains. Formally, a set of instructions a computer runs step-by-step is referred to as an algorithm. And here’s why it fascinates me. If a task can be broken down into simple instructions that can’t be interpreted subjectively, it must be an algorithm. It does exactly what we ask it, the way we ask it, and things get done. And being able to make them, understand them and control them gives us immense power to change the world. We already see how much the world runs on algorithms, how much is changing everyday. All complex applications and devices in the name of technological advancement run along with simpler searching and sorting algorithms. And much like doing work, even they take time and space to work. Optimisation of these tasks to have them happen faster, without loss of data in the process. We discussed different search algorithms only to see that they’re different ways of doing the same thing. Creative ways of getting something done, only written mathematically with code! I think that’s a big take-away. Algorithms can just be simple translations of ‘How would you do it?’ With Transportation and Logistics as the theme, my group decided to take up Hebbal Bottleneck as our site to decipher what algorithm runs there, and how that may be tweaked to improve the flow of traffic. We took that very problem up because we believe that infrastructure is not the only solution to the problem. In 2018 with technology so handy, there’s only so much we can’t do. Despite having law and order, speed limits and regulations in place, the working behind flow of traffic does not have too much room for subjectivity. The problem, no matter how jumbled and complex it may seem, in my opinion can be deconstructed, and made easier. We’re working on it! My real takeaways from this class have been sitting through the research process and acknowledging how every step is rigorous and why every step is necessary. First, there is no way you can reach the next step, or build on the solution well if any of the previous ones aren’t done well. We started off as studying the effects of speed limits and general road behaviour as our topic. Our primary research was focused on just that, and we wanted to enquire with the ACP of Traffic Police, Bangalore. Upon being redirected to different places and not receiving any relevant information, our first field study was almost rendered useless, until we decided to study Hebbal’s bottleneck. We had wasted time running across different offices only to have no data available to proceed with. With this new topic, we tried a new approach to gathering quantitative data by taking periodic screenshots and codifying the colors of the roads onto excel. And while this was methodology was restrictive in regards to knowing exactly how bad or good the traffic is, I absolutely liked the fact that we could gain so much information in a day without having to rely on departments and norms. (If there isn’t a plan B, you probably haven’t looked for it enough.) We deconstructed the map of hebbal, which is easier said than done. That place is depicted differently on different web-apps, and google maps. It was quite the task depicting the real Hebbal on paper as nodes and edges. But once we had that, it was also an achievement because it felt like a step in the right direction. Simplification! The problem began to look less intimidating. We went ahead to visually see the patterns of traffic graphically, to observe two major peaks in traffic density. For each of these edges, we calculated the fitting curve polynomial equations of the 10th degree. I didn’t know this was even possible, for and by designers like us. But then that’s the thing. We limit ourselves, by ourselves. Every step of the research was the discovery of something new, something that added to my understanding of the problem, because before I think I only knew of it. I was assigned the k-nearest neighbour algorithm to present to the class, and honestly resonated with it. Not because it’s capable of solving big problems, and machine learning, (although that’s pretty cool too). But instead it brews from a trait- Greed, and laziness. And to honestly acknowledge that and see how much the world can actually make good out of those infamous traits is basically why the study of algorithms and computation excites me.

I’m going to include my random thoughts in here, that originated for and because of this studio. Should people should try understanding computers better, or should computers do that to us instead? Because getting computers to do that may be easier but people would make this world a better place. I think computers with their capability of doing huge tasks, are simple beings. They read instructions and follow till they’re asked. On the contrary, humans feel emotions. And emotions are highly subjective. With trends in technology moving towards giving emotional intelligence to a machine, is it really that necessary? Because humans themselves fail to address emotions ‘correctly’. With so much study and research happening every day, I wondered, if everyone knew everything about the world, opinions would cease to exist. Truths and Lies would either be too complex, or too defined. Thoughts? I know for a fact that I don’t have an on-point definition of anything I wrote about so far, but I’ve learnt to be okay with it because I think with this pace of development, its a phase of interpretation and application over understanding completely. Never was this class ever boring, because it really had me think a lot. It is never okay to blatantly accept pre-existing concepts in the world. Asking questions and wondering is what makes the mind grow, and grow creative at that. And I think that’s the definition of a successful studio here in Srishti, something that probes each of us to think, and really think, and solve problems.