Month: February 2022

Like many millenials, I went to college immediately after high school, majored in Sociology and Anthropology, and then got stuck. With a Bachelor’s Degree in a soft science, my options were pretty limited to begin with. I was accepted into a MS/PhD program, but I dropped out a year in. At that point I knew that academia wasn’t for me – but now what?

Next, again like many millenials, I spent the next few years working various service or retail jobs. I eventually settled into the veterinary field and I did well enough. I was great at my job, but I grew to hate it. The constant stress, the emotional impact, the toxic workplaces, the abuse from clients all got to be too much for me when the pandemic hit. I had already decided that it was time to move on from that field and was already about halfway through this post-bacc program, so I quit my veterinary receptionist job. After recovering for a couple of months, I took yet another retail job to make ends meet.

As I prepare to leave this program and move on to my new career in computer science, I’ve spent a lot of time evaluating my skills. Many of us in this program are making a major career change now and it can feel like a weird position to be in. We are competing for entry level software engineering jobs with 22-year-olds and most of us are definitely not 22 anymore. We’ve been working for years or decades, so starting at an entry level position can feel like a setback in some ways. Many of us are probably leaving fields where we have built a lot of experience, so feeling like a beginner is really uncomfortable.

In order to be competitive in our job searches, I think it is important for people in our position to make it clear how our experience in other fields helped us build our soft skills in ways that people without any work experience don’t have. For example, my time in the veterinary field has helped me strengthen the following skills:

• Attention to detail: Being detail-oriented and accurate is essential in veterinary medicine. Even small mistakes can have big consequences – in some cases, like when administering medication, it could mean the difference between a healthy, happy pet and a pet owner’s worst nightmare.

• Effective communication: In this field, you need to be able to communicate effectively with technicians, doctors, other clinics, and clients of all types – from the nervous new puppy parent who emails with every question that comes to mind to the elderly person who rarely uses emails at all. I’m able to talk to people who have no experience at all on a subject as well as people who know much more than I do. Furthermore, I can keep my cool in stressful situations, even when dealing with highly emotional clients.

• Critical thinking: I’ve dealt with many emergencies during my time in the veterinary field. Providing phone triage is one of the most important aspects of a vet receptionist’s job and you need to be able to quickly assess a situation and determine the best course of action. Being able to quickly recognize red flags and ask follow up questions, then making a decision based off of that information is something that comes with practice (and I’ve had plenty of practice).

Being able to draw attention to these skills will help set us apart from others with less experience, so it’s a good idea to spend some time evaluating how your past experiences can translate to your potential new job.

Since this week’s Exploration is all about personal projects, I thought it would be the perfect week to write about one of the projects I’m planning to do once this term is over and I have more free time. This project is, in essence, a to-do list, but eventually I want it to have many more features than just that.

A few years ago, a roommate mentioned that he had so many things to do but he couldn’t decide which one to do first. He said it would be nice if there was an app that would just assign him a task from his to-do list so that the decision was out of his hands. That really resonated with me and now I know why: we both have ADHD and we struggle with executive dysfunction. If you’re unfamiliar with that phrase, it basically means that we find it difficult to get started on something because we don’t know how to start or even what to start with.

The more I learn about ADHD and my own experience, the more I think an app that assigns me a task from a list of things that I want or need to do would be extremely helpful. All of the things on my list are important, but I can never decide which one is the most important (or at least the most urgent). This becomes even more of an issue when my to-do list is full of unpleasant things, like making a phone call or doing laundry.

Below, I’ve written a rough roadmap of the steps I will take to make this app and then improve it and add the functionality I want:

1. Make a basic to-do list app (easy to do with online tutorials).
2. Make the app randomly choose a task for you to do.
3. Allow the user to assign an estimated time to each task, then allow the user to input the time they have available. The app then chooses a task that fits in that timeframe.
4. Allow the user to assign deadlines. The choice algorithm will prioritize these tasks when choosing a task.
5. Allow the user to rank tasks in terms of importance. The choice algorithm will prioritize these tasks when choosing a task.

After I get all of this working, I have a lot more ideas that will make this app more fun and motivating. For instance, gamifying tasks is a well-known and very effective way to keep someone interested and motivated. I think adding various rewards (chosen by the user) that are achieved by completing certain tasks or reaching milestones would be a great way to encourage users to complete their tasks.

Another aspect of ADHD is the tendency to hyperfocus on tasks that you find interesting or exciting. I only mention this to explain why I am waiting until this class is over before starting to work on this project… I foresee this project taking up every little bit of spare time I have for a while, so it’s best that I wait until I don’t have any more assignments to potentially neglect 🙂

In the very beginning of this course, after we were assigned our projects but before we had any meaningful information that would let me begin working on the project in earnest, I watched several documentaries on machine learning and artificial intelligence.

Of course this field is incredibly interesting and full of potential, but there are so many concerning possibilities as well. I learned about robots learning to pick things up and projects that are improving driverless cars. I also learned about the ethical concerns relating to these concepts.

https://www.youtube.com/watch?v=OEoU9k5hApM

Apparently it’s very difficult for robots to dynamically pick up objects of varying sizes. Humans are very good at it, but robots have to be specifically trained to pick up individual things and it’s difficult for them to adapt to differently sized things. In this way, humans still have a significant advantage over robots, but we should not assume this will always be the case.

One thing I worry about is how companies are investing into machine learning as a way to eventually replace human workers. Proponents of this plan insist that this will free people from working menial, repetitive jobs. In a utopia, this sounds great. People would (theoretically) have more free time to strengthen social and familial bonds or to create art. Given the current capitalist society, I can’t help but think that this is simply another way to pay the working class less and less money. Repetitive jobs will be eliminated, but will new jobs be created? Or will a universal basic income be implemented to provide everyone with the necessities for living? Some of these documentaries say that this is the goal, but I have my doubts.

Why should we trust those in power to act ethically when, historically as well as currently, they have never acted ethically? When faced with new social movements, capitalistic leaders have been quick to beat down laborers and pay them as little as possible, while cutting as many jobs as they can.

I understand the great potential that artificial intelligence and machine learning have to improve human quality of life. After all, computers are much better than humans at a lot of things, especially when those things are repetitive in nature. I am extremely skeptical that the people who will most benefit from “employing” highly intelligent machines will act in a way that actually benefits most people, though. Given the long history of exploitation of the poor and working classes, I think it is very healthy to be suspicious of the true benefits of robots and computers taking over human tasks.

When I chose the Fire Risk Prediction as my Capstone project, I knew very little about machine learning. After five weeks of work, I still know very little about the vast field of machine learning, but I know much more about a specific type of neural network, created by our sponsor, Chester Ornes: the visual neural network.

You can read his original publication here. This paper describes the benefits of having a visualization of “the relationship between the query and the data in the training set.” It’s a great way not only to examine the data and the model to understand the relationship, but also to foster a better understanding of how neural networks work.

For me (and the rest of my group), most of these first weeks of the Capstone course have been an intense onboarding process. Our sponsor provided us with some material to start with, but it was up to us to get ourselves up to speed. This has been a pretty painful process for me, if I’m being perfectly honest. As I said earlier, I had basically no knowledge of machine learning concepts beyond that of a layperson.

I spent many, many hours trying to understand this complex topic. Thankfully, there are many resources available for that purpose. The most helpful, unsurprisingly, involved lots and lots of visualizations. One of the first videos I watched did a great job providing dynamic diagrams and graphical representations of concepts they were explaining.

Watching these visual depictions, along with some excellent explanations, really started to drive the knowledge home. I feel like I have a long way to go, but I’m finally able to understand what is happening at a deeper level.

While this isn’t exactly the visualization that we’re working on, reflecting on this experience has definitely reminded me of how valuable visualizations can be in helping people understand complex concepts. It’s exciting to be working on a project that will actually implement this in a way that can help in real world situations, like predicting fire risk.