I was honored to deliver a keynote address at this year’s Velocity Conference in New York. My assignment was to talk about what “serverless” meant for teams. As I reflected on that question, and as I continue to reflect on my experience at Velocity, I am increasingly convinced of one basic fact: No technology, no matter how advanced, can replace a good team. In fact, good teams will only become more important as our technology advances.
Now, admittedly, I didn’t make this point in the most obvious way. In fact, I’m pretty sure I heard the room collectively raise an eyebrow when, on the sixth slide of my presentation, I introduced Jean-Paul Sartre. Why, you ask, did I bring up an existential philosopher in the middle of a conference on DevOps and web performance? At the end of the day, philosophers and coders aren’t nearly as far apart as we like to think.
Philosophy is abstract, but it deals with one basic issue: people. Philosophers have spent centuries ruminating on the nature of our existence, our perceptions, and our interactions. Part of what they puzzle over is why people are so different. Why don’t we all see the world the same way? And why doesn’t that girl over there always agree with me? What is her experience of the world, and can I even begin to imagine it? These questions — about human behavior, preference, experience, and fallibility — are exactly what many coders address when they write programs. How can we improve how people communicate? What human mistakes or blindspots can we fix? Will users like this interface?
The fact that most people are strange and different from one another makes humans one of the most complicated elements a computer scientist faces when designing software. We humans don’t follow any single rule. There is no one answer for how we will react to software, user interface, or design. What’s more, the code itself, written by humans, it’s a reflection of the people who created it. That means oftentimes our code has blind spots and makes mistakes. Take Google Photos, for example, whose algorithm incorrectly identified an African American woman as a gorilla. That software was written largely by white men (Google’s tech team is 87 percent male and 57 percent white), and it’s results were skewed by their point of view.
AI Weekly
The must-read newsletter for AI and Big Data industry written by Khari Johnson, Kyle Wiggers, and Seth Colaner.
Included with VentureBeat Insider and VentureBeat VIP memberships.
I brought up Sartre in my talk (as well as de Beauvoir, Hegel, and Said) because people will always remain at the heart of any technology, no matter how sophisticated it is. People use technology, they create technology, and they dictate which technologies succeed and which ones fall by the wayside (anyone still using a Blackberry?).
So what kind of code do we have right now? Well, mostly we have male code, and we have a lot of code from schools like Stanford and MIT. This code has made huge changes to how we operate and has fundamentally transformed how we live. But what else could it do and how many more problems could it solve if a more diverse group of thinkers were involved in writing it?
My brief philosophy lesson might have cost me a few listeners — we were all working outside our comfort zone — but I used that strategy to prove a point. If we are going to solve the big organizational and systems problems of the future – problems that will only increase as our technology gets more and more sophisticated – then we have to be more creative and use a more diversified approach.
A new approach means bringing in problem-solving skills from other disciplines – such as psychology and philosophy; it also means elevating the voices of women and people of color, who have different backgrounds from those of the people who have traditionally written code.
Companies and startups looking to succeed must hire with an emphasis on building teams — in programming and elsewhere — that reflect a diversity of problem solving skills. That might mean recruiting from a wider range of schools, writing job descriptions that are equally appealing to men and women, and choosing the most qualified applicant instead of the applicant who is a friend of a friend and likes the same music as you. It also means valuing all the voices at the table. Listen to feedback from coders, but also consider input from your marketing, legal, and HR departments. Bring in as many voices and experiences as possible so that no blind spot remains unexamined and no assumption is left unchallenged.
Now, more than ever, we need to look beyond the tech industry if we want to create the best tech innovations. It won’t be easy, but in order to build better technology, we have to stop ignoring the human element and start embracing and listening to the differences – and complications – that make us human.
Rachel Chalmers is a principal at Ignition Partners, an early-stage venture capital firm focused on business software. She has over 20 years of experience observing the tech industry, first as a tech journalist and later as a founding member of 451 Group, which conducts tech industry analysis focused on enterprise IT innovation. While at 451 Group, she was among the first analysts to cover industry giants including Opsware, BladeLogic, VMware, Splunk, and Cloudera. Follow her on Twitter: @RachelChalmers.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn More