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Hi friends, I'm Elizabeth. If you don't know me, then please come say hi to me.
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For those who don't know me, here's a quick 30-second bio. I've been involved in open source for a really long time, since 2002, because I'm quite old. I was a PHP developer for many years, and then about six years ago, I transitioned to the community side of things. I pivoted my career, and now I work at GitHub. I've been at GitHub for about four years, focusing on community-related tasks.
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I live in Cincinnati, so if you need recommendations for great places to eat, see, or visit, you might want to ask someone else. I live in the suburbs and never come downtown, so I'm somewhat out of touch. I was excited to come out last night and enjoy dinner downtown; it felt like I was a tourist in my own town.
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I hold a degree in organizational behavior, and I'm fascinated by the behavioral science aspect of open source, which is why I'm giving this talk. I tend to geek out over this stuff, so I apologize in advance for my excitement. Now, let's get started.
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If we were to define what makes open source open, I think this definition fits well: 'individuals working in groups collaborating together online.' So, we want to break this definition down into different layers, starting with the individual.
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According to Wikipedia, there are no less than 107 different ways we act completely irrationally. That's a staggering number! We tend to believe that we are the rational ones in our decision-making, but the truth is we are rarely rational. This phenomenon extends beyond unconscious biases like sexism and racism, which we won't delve into, as discussing all 107 biases would take ages and likely bore you.
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Instead, I'll highlight a few patterns I've observed over my 14 years in open source. My goal is to help you empathize with these behaviors and recognize some of these biases in yourselves.
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Firstly, let's talk about negativity bias. This bias explains that we, as human beings, tend to place more importance on negative experiences and feedback than on positive ones. Behavioral scientists trace this bias back to survival instincts—if your cousin eats a poisonous plant, you learn quickly not to eat it! Consequently, negative experiences register more rapidly and deeply in our brains.
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When you receive negative feedback, it stays in your long-term memory, whereas you'd need about 15 to 30 seconds to appreciate positive feedback before it sticks. Interestingly, every negative experience you have holds over twice the adverse effect of any positive experience. For instance, if I give you $20, you might feel good, but if you then lose that $20, you'll feel worse than you did before. It's a fascinating and somewhat disheartening aspect of human psychology.
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We also learn faster from negative experiences. In the carrot and stick analogy, the stick teaches us much more readily than the carrot does. While not the healthiest method of learning, people quickly grasp what behaviors to avoid when faced with negativity.
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Now, how many of you here participate in or manage an open source project? Great! These insights also apply to work or home life; this is human behavior. Did you know we possess five times more neural networks dedicated to negative affect than to positive affect? Negative affects encompass emotions such as fear, grief, and shame, while positive affects include joy and laughter. This tendency to focus on threats significantly influences our daily experiences.
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Understanding that we process negative experiences more intensely can help mitigate this effect. Additionally, we often have more vocabulary to express negative feelings than positive ones.
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When looking at a picture, what do you notice first? A broken window, right? Now, how many of you consider yourself a problem solver? Many of you! The interesting thing about problem solvers is that they're always on the lookout for problems. This constant vigilance can lead to seeing the world primarily through a lens of negativity.
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In contrast, it's crucial to recognize the difference between creating and problem-solving. The key difference lies in intention: in problem-solving, we seek to eliminate what we don't like, whereas in creating, we aspire to bring forth what we truly care about. If we reevaluate the example of the broken window, we could also view it as mostly intact, with just one pane needing replacement.
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Next up is the Dunning-Kruger effect. Has anyone heard of this? It reflects our struggle to objectively assess our expertise and know-how compared to others. There’s also the concept of imposter syndrome, which many in software can relate to. It's vital to strive for an objective understanding of our skill levels, both positively and negatively.
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Now let’s delve into confirmation bias. One easy example would be social media—such as Facebook or Twitter—where we tend to only seek information that aligns with our preconceptions. Our brains filter out opposing views or confusing information. In research contexts, confirming bias can obscure our understanding of results.
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Additionally, when we feel like imposters, we often align our thoughts to reinforce our feelings of inadequacy. Mitigating this bias requires conscious effort.
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Another interesting concept is the illusion of transparency. Has anyone heard of this? This occurs when we overestimate how well others understand what we are thinking. We believe our intentions or thoughts are clear, but without proper documentation, misunderstandings arise. A study showcased how when individuals tapped out a song for someone else to guess, they anticipated that the recipients would easily identify the tune, but the reality was starkly different.
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The curse of knowledge illustrates further challenges—once we gain expertise in an area, we often struggle to empathize with beginners. In my role at GitHub, I run events for beginners, and the experience reveals how essential it is for mentors to recall their own learning pathways.
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We all learn differently—be it through traditional schooling, boot camps, self-teaching, or other methods. There’s no single way to become skilled in our fields, which can lead to significant gaps in collective knowledge. When we react negatively to someone's lack of knowledge, we should recognize the myriad experiences that shape our learning paths.
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The false consensus effect leads us to overestimate how many people agree with our viewpoints. We often think our perspectives are common, which they may not be. Our personal experiences can mislead us into believing everyone feels similarly about a topic.
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Let's discuss rejection sensitivity. This trait manifests in a spectrum—some people are entirely unconcerned about rejection, while others are hypersensitive. It's essential to remember: just because we respond differently doesn't render others 'overly sensitive.' Our subjective perspectives can vary widely.
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Remarkably, our brains react similarly to social rejection as they do to physical pain. If we feel rejected or disconnected, we experience real, physiological effects. Painkillers released in our system help alleviate that discomfort.
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Now, let's shift our focus to collaborative groups. Inclusivity becomes even more critical when navigating diverse complexities present in team dynamics. Ingroup favoritism can lead to tribalism, leading to unhealthy competitiveness within project communities.
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It's essential to embrace diversity and recognize our shared goals in open source development. People often become too attached to their identities tied to specific tools or languages. This emotional attachment can create an unnecessary divide and shift focus from our mutual goal.
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Feeling understood is crucial for community members. Studies have shown that being respected and comprehended strongly influences our emotional wellbeing, and when we feel misunderstood, negative emotions arise.
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The want for social belonging is deeply rooted in human history. As indicated in open source projects today, we thrive better as a unified group. Everyone needs to feel they belong to foster motivation and engagement.
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Now, let's look at SCARF—a model designed to understand what motivates individuals in group dynamics, which involves status, certainty, autonomy, relatedness, and fairness. Each domain influences how people engage with peers and perceive their contributions.
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The need for status or recognition can significantly impact someone's involvement in an open source project. Meanwhile, certainty often diminishes feelings of threat, which can encourage engagement. Some people require clear guidelines to feel comfortable contributing.
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Autonomy is essential; contributors value the freedom to work independently, as feeling powerless can lead to disengagement. Relatedness ties back to our inherent need for connection and belonging within a community.
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Finally, fairness is a complex, emotion-laden concept. It varies dramatically based on individual perspectives. What seems fair to one group may not be perceived the same way by another, contributing to conflict.
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Collaborating online, particularly in open source projects, is intricate and requires conscious effort. Recognizing ourselves in these behavioral patterns can foster empathy toward others.
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As I've mentioned, these slides will be available on Speaker Deck, alongside links to every research paper I referenced. I encourage you all to explore the factors influencing human behaviors. Understanding these can lead to better personal interactions within your open source community.
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In conclusion, let’s extend a bit of grace towards ourselves and others in our communities. We're all navigating complex emotional landscapes, and a little kindness can go a long way.
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Once again, I'm Elizabeth, but known as Elizabeth N on various platforms, including GitHub and Twitter. If you have any questions or just want to chat, I'm here for you.
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Thank you all for your time!
