The fields of data science and computing hold immense power in today's world. Machine learning affects our lives every day — from healthcare costs to ability to get a mortgage — and can help address intractable problems like climate change. Having diverse teams can lead to less biased algorithms and technology that serves more audiences.
At UC Berkeley's Division of Computing, Data Science, and Society, we believe each of our students bring unique value to the field through their expertise and their lived experiences. Conan Minihan, a formerly incarcerated individual and current UC Berkeley data science major, is one of them. We spoke to Minihan about his journey from prison to Berkeley, why he chose to study data science and what he hopes the field and he as a data scientist can do for society.
This interview has been edited for length and clarity.
Q: Can you talk about your journey from being incarcerated to attending UC Berkeley?
A: I clawed my way here from some very dark places. Going back to when I was locked up, you just don't get to sit back and expect to go home. You have to be actively working to be able to get home. At the same time, I wanted to set myself up for a life beyond this – a life after prison – where I don't go back. So, every moment was just about finding every little positive I could, whether that was learning Spanish or chess or participating in whatever self-help program was available. So year after year, I focused on that.
Then when that time finally came to rebuild my life on the outside, I was able to do that at San Diego City College. I was able to get a job being a math tutor there. Tutoring math made me a better student, and it made me a bigger part of the community there. It put me in a position to help a lot of people and to also get help from a lot of people. Then I applied to a bunch of [four-year schools]. I just needed to get into one place, and I got into all of them. I had a lot of great choices to now put myself in another better situation.
Q: You said you knew that you’d need to go to college when you got out. How did you know that?
A: When I was 15, things weren't good at home, so I moved in with my brother. He was the first person in our family to go to college, and he was pretty intent on breaking some cycles that we had experienced. After I graduated high school and everything, I made some mistakes, but I still understood what he had taught me. To exist in this economy comfortably, you’ve got to go to school. I knew I still needed to do that. I knew that getting out, if I wanted to live well or even do something interesting, I had to go to school.
Also, everyone in prison is pretty cognizant that recidivism is really high. The vast majority will recidivate within a few years of being released. And one thing that's well-known and proven to stop that is getting college educated. So, that's another thing. I didn’t want to go back. I wanted to go forward and move on.
Q: How did you choose data science as your major?
A: I was seeing on the news a lot about people who were graduating and still unable to find a job that paid well. I heard STEM [science, technology, engineering and math] was different. I was interested in STEM, too, so it was just about finding the right bachelor's degree.
I was looking at some things like kinesiology and biology, reading a lot and looking at the Occupational Outlook Handbook, when I came upon an article that talked about the need for statisticians. I thought that was interesting. I also noticed the way a lot of companies were using wearables for fitness and medicine and collecting that data.
When I got out, I was still trying to find my way, and Columbia University had an event at my community college, so I went. I saw they had data science. Then the school I was planning on going to – UC San Diego – had data science. I was like, “Huh, this could really be something.”
Q: What are you hoping to do with data science?
A: When I got to Cal, I was really interested in using it for personalized and predictive medicine. I had done some research that I thought was really cool and important, helping develop a device that would monitor central blood pressure and use that data to predict and prevent heart attacks. Heart disease being the number one killer of anybody, this device could help everybody. It's really interesting, and it's a great application of data science.
But I also wanted to have an opportunity at Cal to explore different domains. I've been able to do that. Through the Data Science Discovery Program, I was on a project where we used geospatial data to plot areas of violence on youth experiencing homelessness in San Francisco. With the Division of Equity and Inclusion, I've been doing projects related to their support programs. And I just decided to take an internship with a startup called DroneSeed. They plant trees after wildfires with drones.
So I'm still in a space where I'm exploring. It's a bit of an adventure.
Q: Has data science affected how you view the criminal justice system or vice versa?
A: Oh my goodness. Yeah. Here’s an interesting experience I had recently to start: I'm in Data 4AC: Data and Justice, and we did a module on the realignment of the California prisons. I'm a data point in this, and it was really eerie working through this Jupyter Notebook that is talking about the facilities I was at when I was at them with numbers that I am one of. It was eerie.
These numbers are generated by the California Department of Corrections and Rehabilitation. That’s one thing I've been thinking about a lot: this data we worked on was generated. You’ve always got to think about where it's generated and why it's generated. That's one thing that we're taught a lot.
Well, this stuff is generated to manage our bodies, right? To manage where we are. There's a lot that's not said in the data. Often, there's really relevant data that they have nothing on or won't include because it may incriminate them. There's a lack of information due to the fact that the people collecting and managing the data have that bias. It’s all from the law enforcement perspective. There is no community perspective on this. There is no one who experiences the criminal justice system who generated this data because of who has the power.
Q: Has that kind of interaction with the data changed how you look at non-criminal justice data in data science?
A: Definitely. It makes you really question who has the data, who generated it, when it was made, why and how did they generate it, how many samples are there, everything. A statistic just isn't a statistic anymore.
Q: How has your experience been at Berkeley? How has community played into your experience here?
A: Community has been really, really important in dealing with a lot of what I’ve experienced at Cal, groups like NavCal, Underground Scholars, Data Scholars, Hope Scholars, Cal NERDS, Disabled Students’ Program and the data science transfers program. I've been able to learn lessons from other people who come from non-traditional backgrounds. It’s important because a lot of these classes were constructed for people from more traditional and dominant backgrounds, and there are different assumptions of privilege that are baked into them. These communities showed me how to get around, how to access resources and how to find the right support to get to the next step, whether that be grad school or work. Having that mentorship has been really important.
Also, when you're part of a community, you get that help, but you also give it. That’s also very rewarding. I tutor Data 100 students. I've been a mentor for NavCal and the data science transfers class. I help people apply to scholarships, introduce them to different programs that they're eligible for and help them with their homework.
Q: What advice do you have for students who have just gotten out of prison, or they're currently in prison, and they want to follow in your footsteps?
A: One very important thing that I read when I was locked up, actually, was Tolstoy says, “the two greatest warriors are time and patience.” Also, it doesn't matter what cards you're dealt. It's how you play them. So in every circumstance, you need to find the silver lining in it, and you need to make the best of it.
And I guess a third thing: you can't make up for lost time, right? You can only make the time you have. So if you're locked up, just do whatever positive thing you can, get whatever you can out of any time and use that to move yourself towards better circumstances and people.
Time and patience will rule all things. It took me 10 years to get here from really dark, scary, dangerous places. Whatever your circumstance you just got out of, make the most of it and keep at it day after day.