For my final column, I’d like to reflect on what brought me here. To this column, yes, but that starts with what initially brought me to UC Berkeley.

My undergraduate career was spent majoring in computer science with a minor in math. I discovered relatively early on that I didn’t want to work with software systems my entire life. Yes, contrary to popular belief, some of us programmers do crave human interaction.

So, like many people who wanted a second go at things, I decided to pursue a master’s degree. 

I chose data science because it lies at the perfect intersection of technology and people. There’s enough math to keep the STEM vibe, but there are plenty of people-facing responsibilities to complement.

The impression I received from admission counselors was that UC Berkeley’s program is the most theoretical, fundamental and abstract.

When it came time to decide, I recalled a piece of advice I received early on as a young engineer that I’d like to pass on to you, the readers: Companies can teach you the technical, but they want the people skills.

I came here not only because of the high quality of education, particularly in anything tech related, but also because of UC Berkeley’s academic culture. There’s an emphasis on ethics, people and society at large.

This is true of all UC campuses — “Fiat Lux” after all, let there be light! — but I believe this culture is strongest at UC Berkeley. I didn’t just want to learn data science; I wanted to learn how data science affects society.

That is ultimately why I wrote this column. It’s an exercise in this intersection. 

While I chose to write about current events in general, many of my columns have been about technology. I have written about emerging technologies, technological failures and tech products. 

Another way of looking at those three columns is through the lens of societal progress, the tragic loss of human life and consumer culture, respectively — technology was just the tangentially related underpin.

Data science is the hot new subset of technology. It has been called “new oil” and “digital gold,” and there is certainly a gold rush to capture this value. UC Berkeley even created a college specifically dedicated to data and statistics earlier this year.

Data can identify and predict diseases, sometimes even better than doctors can. Data can optimize shipping routes and business processes, reduce emissions and waste and make the world a safer place.

It enables institutions to work better and more efficiently.

Data can also identify your pregnancy before your family can. Data can find your probable soulmate and put them behind a paywall, or assign you a credit score that will impact your big decisions. 

Thus, in the wrong hands, data can be detrimental.

Great things are happening with data, and needless to say, bad things are happening with data. There are public debates surrounding concerns like data privacy, safety and ethics.

In fact, if this weren’t my final column, I would’ve written about the recent resignation of Stanford’s president, after an investigation concluded he was negligent in — though not responsible for — falsification of data in scientific papers. This is a good example of a current event about data. In this case, data fraud, the philosophical opposite of data science.

This is an easy take, but moderation is key. Skepticism in the extreme is bad. On the other hand, embracing a technology too fast risks us becoming a cyberpunk dystopia.

In particular, I think it’s important to not lose sight of the individual, or of humanity. As Brad Pitt’s character put it in “The Big Short,” “You know what I hate about f—cking banking? It reduces people to numbers.”

It is easy to view individuals as numbers or as a collection of attributes, as a walking set of probabilities that can predict certain behaviors instead of humans with agency. We would do well to not fall into this trap, especially these days, when we’re already too often represented as pixels on a screen.

It is inevitable that mistakes have been and will be made. However, it is important that we learn from them. Data is useful, and I’m glad to be learning about it and participating in it. 

Hopefully, I can make my mark on this emerging field one day.

Coincidentally, I will finish this column and start my data ethics class a few weeks later in the fall semester. The course is “Behind the Data: Human and Values,” and I’ve been looking forward to it. It is one of the reasons why I enrolled here.

Regardless, I’ve shared my views. Now I must go back to learn some more.

Thanks for reading.