It is super interesting to me how AI is teaching / re-teaching several important lessons about the nature and qualities of “truth” — and our role in it:
1. The Power of a Well-Defined Goal
A higher quality understanding of your question, goal, or problem yields a higher quality response/solution. An AI algorithm’s efficiency is dependent on the accuracy and specificity of the input you provide. As with any tool, to get the most out of AI, you need a clear understanding of what you’re trying to achieve. This realization requires us to invest time and effort in articulating our goals and problems accurately and in detail.
TIP: Know your use case.
2. The Art of Asking Better Questions
AI also underlines the age-old wisdom – the better the question, the better the answer. AI is as good as the data it’s trained on and the instructions it receives, reminding us of the importance of well-formulated inquiries.
TIP: Simplistic, throwaway questions get simplistic, throwaway answers.
3. The Strategy, Not the Tool, Makes the Difference
AI has a spectacular capability to consume and regurgitate a probabilistic average of other peoples’ pre-existing content. That is a nice time saver, but it definitely isn’t a point of view or a strategy. Relying solely on AI can result in work filled with outdated information, mediocrity, and mistakes. The uniqueness of your strategy, perspective, and execution should be the primary differentiator, not your AI tools.
TIP: Your strategy, point of view, and how you execute are what differentiate you; not your tools.
4. The Contextual Nature of “The Right Answer”
“The Right Answer” is heavily dependent on the situation, the use case, and the people doing the asking. (Unless you’re asking questions that only have a single, determinate answer, such as a math formula.) Sorry if I sound like your undergrad philosophy and comparative religion professor, spouting relativism at a college party, but beware black-and-white thinking.
TIP: People hate the philosopher’s answer: “It depends…” But it often does.
I’m increasingly wary of the potential harm AI can do. But I’m neither an AI Pessimist nor an AI Catastrophist. Rather, I consider myself a cautious AI Realist with strong AI Optimist tendencies. But to unlock AI’s promise, we have to do the work of learning, testing and skill building.
Consider the use case of B2B content:
In the B2B content use case, we’ve been wading through the flood of weak, boring, human-powered content for over a decade now.
I’m pretty sure AI is going to turn that flood into an AI-powered tsunami of inaccurate, samey, boring, and/or patently mediocre content, especially at first. Strategy, POV, quality control, and human guardrails will be extremely important — especially while we learn the pros/cons, strengths/pitfalls of this new superpower that’s being placed into our hands.
However, the potential upside is enormous. Once thoughtful and strategic teams learn to wield AI with skill and safety, the results could be phenomenal. Just like any other tool, AI in the hands of a trained and experienced individual can deliver amazing results.
Clearly, coffee makes me a bit philosophical. But we’re standing at the precipice of an AI revolution. Buckle up though. The journey ahead promises a fair share of turbulence. However, those brave enough to dive in early, practice safety, and embrace a test-and-learn mindset, stand to reap considerable benefits. The real art lies in learning to leverage AI’s transformative capabilities, while maintaining our unique human touch.
What do you think?