I’ve been thinking about what I really want to do since returning home to Newfoundland in July. Slowly but surely, I’m starting to understand where I need to head. I have no end-goal in mind. Datalove is an outlet to help me along, whatever path that might be.

Loosely, here’s where I want to play:

- Epistemology
- Empiricism
- Self-Experimentation
- Health
- Data, Statistics & Visualization
- Psychology of the above

Epistemology & Empiricism

In the last twelve months I’ve been slowly digesting Nassim Nicholas Taleb’s book The Black Swan. Reading and re-reading. His ideas have changed the way I see the world. Far more than other idea, book, event, dessert cake or Frenchman. In a few words or less: we don’t know squat. Surprising events are predictable only in hindsight. A single dis-confirming observation can nullify millions of confirmations (the problem of induction). We are serial-categorizers, even where no categories exist. Beware mathematical models… Especially in Extremistan. Embrace wild randomness and the unknown. Have the courage to say “I don’t know”.

Self Experimentation

Like Prof Seth Roberts, I want to hack my mental acuity, mood, sleep, energy, strength and endurance. And with luck, make a few interesting finds. But I’ll need to learn a few things about experimental design (or is that observational studies?). What happens when there are a thousand Seth Roberts?

Data, Statistics & Visualization

Self-experimentation means lots and lots of data. How do I collect it? How do I interpret it? How do I present it?

Health

What better data to play with those I care most about? I’m starting to get the difference between health and medicine. Health is a choice. And we’re much more in control than most think. Especially via self-experimentation. A major theme to explore – that our moderns environments are very different (and far less random) than those that guided our evolution. What effect will a Paleo-random lifestyle have on my health?

Psychology

There are lots of blind-spots and biases to be aware of when dealing with knowledge, uncertainty, data, stastistical thinking, etc. First is being able to reason around those biases. Much harder is being able to intuit around them.