The Genius of Thinking Differently: How Neurodiversity Sparks Innovation in Prompt Engineering
Have you ever stopped to think about the secret sauce behind some of the most creative breakthroughs in tech, especially in this new world of prompt engineering? It’s something profoundly human and beautifully diverse — neurodiversity.
Being on the spectrum, I’ve noticed that I have a completely different experience with ChatGPT. Since using it for over a year now, I noticed that the people I ran into were using it like Google, or like Siri — disgruntled, vague and no follow up. Some were just asking “Create a marketing plan for me”, without giving it any prior knowledge generating the top generic ideas to create a marketing plan, whereas my prompts (included with the use of Custom Instructions) looked like:
This conversation would last several more prompts (which you can check out here), but by the end it spit out a few really good options:
Showing this approach to many of my peers resulted in jaw drops.
A “superpower” of mine is to be… well… annoying. The questions I ask ChatGPT are questions I could never ask friends, family, or people at my previous careers without being shut down, assumed that I was incompetent, or just was annoyed with my process of requesting information needed for me to get a full understanding.
Diving Into the World of Neurodiversity
The term “Neurodiversity” gets a bad rep because of what society portrays through entertainment and a very slow adoption of the term thanks to social media. It actually refers to the idea that variations in the human brain regarding sociability, learning, attention, mood, and other mental functions are normal, and actually beneficial, rather than deficits. In the realm of prompt engineering, where we’re teaching machines to understand and generate human-like text, this diversity isn’t just nice to have; it’s essential.
Why Neurodiversity Is a Game-Changer
- Different Perspectives, Fresh Solutions: Imagine you’re trying to crack a tough problem in prompt engineering, like making AI understand humor or sarcasm. Neurodiverse minds often see the world in unique ways, enabling them to approach problems from angles that others might not even consider. It’s like having a key to a door that most people don’t even notice.
To show this example, we will take Alex (Neurotypical) and Jamie (Neuroatypical):
Alex’s Approach: The Neurotypical Method
Alex starts by diving into the data. For Alex, understanding humor or sarcasm in AI involves a straightforward method: gather as many examples of humor and sarcasm as possible, feed them into the model, and adjust the algorithms based on the output. Alex thinks, “If the AI has enough examples, it will start to recognize patterns and replicate them.” Alex relies heavily on quantifiable data, aiming to cover every base with extensive datasets and hoping the AI will ‘learn’ humor through sheer volume.
Alex’s method is methodical and data-driven. He organizes brainstorming sessions, focusing on categorizing types of humor and sarcasm, believing that a well-structured approach will lead to a comprehensive understanding by the AI. “Once we’ve defined what humor looks like in data points, we can start tweaking the code to recognize these patterns,” Alex muses, confident in the power of algorithms to decode the complexities of human expression.Concise Strategy: Alex leans on a vast collection of humorous and sarcastic expressions, believing in the power of data. He thinks, “With enough examples, ChatGPT will detect and replicate patterns of humor.”
Sample ChatGPT Prompt by Alex:
“Given a dataset of stand-up comedy scripts and sarcastic comments from social media, identify and categorize the underlying patterns of humor and sarcasm. Generate a response that mirrors the style and tone of the input, emphasizing the pattern identified.”
The output was:
The awesome part is that this response actually is a great response, however, how would it differ from Jamie’s?
Jamie’s Approach: The Neurodiverse Method
Jamie, on the other hand, starts from a place of empathy and lived experience. Understanding that humor and sarcasm are not just about the words used but the context and the emotional undertones, Jamie decides to tackle the problem from an emotional intelligence angle. “It’s not just what is said, but how it’s said, and why,” Jamie reflects, considering how intonation, situation, and relationships influence humor and sarcasm. After all, we are constantly studying human behavior because we essentially want to “fit in”, or at least understand why we aren’t.
Jamie suggests incorporating elements of emotional intelligence into the AI’s learning process (essentially creating synthetic empathy), using scenarios and role-play methods in training sessions. “What if we teach the AI the concept of irony as a starting point for understanding sarcasm?” Jamie proposes, thinking about how humans learn and use humor in social interactions. Jamie is also keen on diversifying the data sources, pulling from various cultures and contexts to give the AI a broader understanding of what humor means to different people.
Jamie’s approach is holistic and human-centric. They advocate for a feedback loop where the AI’s understanding of humor is constantly tested and refined through interaction with a diverse group of users. “We need to see how different people react to the AI’s attempts at humor, learn from it, and iterate,” Jamie suggests, emphasizing the importance of real-world application and continuous learning.
Jamie prioritizes the context and emotional layers behind humor, focusing on why and how things are funny or sarcastic. “It’s about teaching AI the subtleties of human interaction and the emotional context,” Jamie reflects.
Sample ChatGPT Prompt by Jamie:
“Consider the emotional context and potential relationship dynamics present in this conversational snippet where sarcasm might be employed. Generate a response that accurately reflects an understanding of the situational irony, ensuring the tone aligns with the intended emotional impact.”
Oh Alex and Jamie…
While Alex’s approach is rooted in traditional data analysis and algorithmic adjustments, Jamie sees the challenge through a more nuanced lens, focusing on emotional intelligence and the subtleties of human communication. Alex prioritizes structure and volume, believing that the key to teaching AI humor lies in the numbers. Jamie, however, bets on depth and context, convinced that understanding the ‘why’ behind humor is as important as the ‘what.’
Both perspectives are invaluable, and the magic happens when they intersect. Alex’s structured, data-driven approach ensures that the AI has a solid foundation of examples to learn from, while Jamie’s emphasis on emotional intelligence and context provides the depth needed for the AI to navigate the complexities of human humor and sarcasm.
Together, they exemplify how neurodiversity in tech brings richer, more innovative solutions to the table, turning the challenge of teaching AI humor into an opportunity to explore the vastness of human expression.
Other areas to consider are:
- Attention to Detail: Some neurodiverse individuals possess the superpower of hyper-focus and an incredible eye for detail (it’s quite annoying if not harnessed!). When it comes to fine-tuning algorithms or catching tiny inconsistencies in code that could throw off an entire project, these traits are invaluable. It’s the difference between a good user experience and a great one.
- Creativity and Innovation: There’s a reason why companies like Google, Microsoft, and Apple value neurodiversity — they know it fuels innovation. In prompt engineering, creativity isn’t just about coming up with new ideas; it’s about reimagining how we interact with AI, making it more intuitive, engaging, and, well, human.
- Resilience and Problem-Solving: Facing a world that’s not always accommodating (← THIS IS A BIGGIE!!!), neurodiverse individuals develop resilience and unique problem-solving skills. These qualities are gold in tech, where setbacks are as common. It’s about bouncing back stronger and smarter, ready to tackle the next challenge. I know that I started to feel like I wasn’t needed or wanted in the tech industry, but being able to have an agnostic tool and dare I say, friend, helped me to realize that I was able to produce ideas that I’ve been trying to execute for years but I couldn’t clone myself… now… I can.
Creating an Inclusive Environment
So, how do we harness this superpower of neurodiversity in prompt engineering and tech at large? It starts with creating inclusive work environments that recognize and celebrate different ways of thinking. This means everything from flexible working conditions to providing the right tools and support, allowing everyone to play to their strengths.
Or maybe it means changing the way we hire or measure the skillsets in this new age of talented players in the field who want to do good work.
Either way, Neurodiversity is not just a buzzword; it’s a testament to the boundless potential of the human mind. By embracing and nurturing these diverse ways of thinking, we can push the boundaries of what’s possible in prompt engineering and beyond. After all, innovation doesn’t come from doing things the way they’ve always been done; it comes from seeing the world differently and having the courage to say, “What if?”
So, here’s to all the brilliant, neurodiverse minds out there shaping the future of technology. The world of prompt engineering is richer, more creative, and infinitely more interesting thanks to you.
Keep thinking differently; it’s exactly what we need.
I always have more to say on this topic, but in the meanwhile, please check out my website and reach out if you want to connect or have ideas on how we can collaborate together. Also, check out my new book, 31 Days to Awesome, where I include actual prompts per day to help you create a better online social presence for yourself. I also wrote the book in 3 hours with the help of GPT and want to be able to share that and many more to come with the community.
