This blog is the product of my personal fascination with the advancement of technology and my frustration with sensationalized reporting on these matters. Specifically, Nay-I Say-I is a play on words regarding my dissenting viewpoint on the future of artificial intelligence (AI), but I intend to explore a broad range of topics – allow me to explain!
We live in an unprecedented age – although, true to the spirit of this blog, I’ll pause to point out that EVERY age is unprecedented until it’s in the past! Nevertheless, it is undeniable that truly remarkable technological developments occur almost daily. Compounding that, unlike any prior point in history, we have the capability of near-instant transmission of information, which has greatly streamlined the speed at which ideas spread, further fueling the knowledge engine of mankind (more about engines – the internal combustion kind – to come in a future post.) Speaking of ideas…
About the author
I am enraptured with ideas. Interesting ideas and new ways of thinking are what led me to study mathematics, and from the first time that the concept of a limit was introduced to me in high school calculus, I was hooked (note to self: make a layperson accessible post describing how totally rad limits are.) I now have a PhD in Applied Mathematics with a focus on computational science.
But back to ideas! I’ve often said that mathematics is the science of ideas, and the big take-away lesson from my journey in math is an appreciation for the foundational process of logic on which the great towers of human knowledge have been built. Logic is slow and requires patience. It starts with assumptions, and one truly wonderful realization is that you can choose any assumptions you want – whether they are good or bad – and follow the logic to see where they take you. Even when starting with assumptions that we know are wrong, following the logic trail can lead to deeper insight in surprising ways.
The ability to formulate our assumptions is vital, because then we are able examine, criticize, and refine them against our observations in order to increase our knowledge and understanding.
Assumptions and Reductions
We are all unique human beings each working only within our own limited capacity and with a tiny fraction of human knowledge. There is no way that a single person can learn everything – but the beauty of ideas is that they need not be concrete. With enough effort, we can reduce immensely complicated concepts into a digestible package that the average person can understand, appreciate, and use.
Reductionism is an awesome tool, but also a dangerous one depending on (1) the level of simplicity desired and (2) the knowledge/competence/intellectual honesty of the person who does the reducing.
The greater the level of simplicity desired, the less accurately the explanation will reflect reality (which might be totally fine! The level of detail that you require really depends on what you plan to do with the knowledge next.) On the other hand, if someone’s grasp of the underlying assumptions and mechanisms of what they attempt to explain is insufficient, then the accuracy of their reductions will inevitably suffer, being contaminated by their influences, i.e., their worldview. The layperson is left with no way to distinguish fact from opinion, extrapolation, or outright falsehood.
What I’m trying to do here
In due time, I want to rigorously flesh out my understanding of some big foundational concepts such as assumptions, reduction, approximation, cognitive biases, skepticism, and logical/critical thinking. Additionally, I will do my best to bring a balanced perspective to the science and tech news that I find to be either significant or totally blown out of proportion. And I hope to do all of this in a super compelling way that will inspire you to give deeper thought to the way you process new information and the way you see the world.