3 lessons from year 1 of Notes by Ada
The word “essay” comes from the French word Essayer which means “to try.” An essay is something you try to figure something out. Paul Graham, who shared this thought on his blog continues —
Figure out what? You don’t know yet. And so you can’t begin with a thesis, because you don’t have one, and may never have one. An essay doesn’t begin with a statement, but with a question. In a real essay, you don’t take a position and defend it. You notice a door that’s ajar, and you open it and walk in to see what’s inside.
If all you want to do is figure things out, why do you need to write anything, though? Why not just sit and think? Well, there precisely is Montaigne’s great discovery. Expressing ideas helps to form them. Indeed, helps is far too weak a word. Most of what ends up in my essays I only thought of when I sat down to write them. That’s why I write them.
In the things you write in school you are, in theory, merely explaining yourself to the reader. In a real essay you’re writing for yourself. You’re thinking out loud.
In the spirit of starting essays with questions, I started today’s with — what are 3 of the top lessons learnt from a year of writing these notes?
1. What does “x” technology make cheap? One of my favorite lessons from this year was to evaluate technology by asking — what does this make cheap? In a video by Frank Chen at a16z, he compared the AI revolution with that of relational databases. Relational databases made it easy to store, sort or count information and these, thus, became fundamental in every piece of software.
His notes led to this crude sketch.
If you want to understand why artificial intelligence is feared by large sections of the population, this image explains it.
When technology makes something 10x cheaper, large scale disruption happens. Two awesome images from a Tony Seba presentation explain this.
It took only 13 years for cars to completely replace horses.
All this brings me to the blockchain. Just to be clear — I don’t claim to understand why Bitcoin is priced at $8,000 and I have no idea how to value cryptocurrencies either. I don’t own much Bitcoin even if I wish I did (ha). I do, however, have a sense of what the blockchain enables — the ability to have decentralized databases. The question, if you’re wondering about a blockchain based future, then is — what will blockchains make cheap? (Trust?)
2. When you think about the future, it helps to understand the past. History doesn’t repeat but it rhymes.In most early editions, I share a version of this foundational technologies chart.
This chart has helped me make sense of where we are now and how to begin making sense of where we might be going.
For example, it explains why we’re seeing old world giants fall like flies in their fight against the technology giants. Technology waves require a complete change in business models. And, old world companies are facing an increasing chasm as they try to adapt to changes that the technology giants overcame a decade ago.
History is particularly helpful in understanding how media industries have evolved over time. All information/media industries have experienced the following cycle. They rise thanks to hobbyists, give way to monopolies and then get supplanted by new technology.
We are seeing this play out with the Facebook — Google media duopoly.
3. What are the second order consequences of this technology?
Finally, while the first step is to understand what the technology enables (i.e. its first order consequences), an important next step is to understand the second order consequences. For example, a second order consequence of what the internet made cheap (easy small payments and the ability to have subscription relationships) meant that the internet was very suitable for the subscription business model.
It also enabled platforms with the “tax” business model like never before. And, suddenly, everyone was capable of running their own retail story and advertise via large online platforms.
All this means businesses need to change business models to survive on the internet.
Similarly, understanding the second order consequences of increased adoption of artificial intelligence makes it obvious as to how woefully underprepared we are. China has installed 20 million cameras all over the country to create the most advanced AI powered surveilance systems. What if repressive regimes in Africa did the same? What happens when the data that powers these systems is biased — e.g. more likely to flag folks with brown skin and a beard?
That aside, 72% of US adults in a Pew research survey are worried about a future where robots and computers can do many human jobs.
That’s because recent technology waves, wonderful as they’ve been overall, have left many behind. And, AI seems poised to further that inequality. This chart explains what happens when you add automation to oil rigs. The number of oil rigs in the US has been increasing — but, employment has not.
We’re still in the early days of figuring out solutions. Enthusiasm for universal basic income has waxed and waned. There are many concerns with such approaches — as there should be. But, we need to keep the discussion and debate up. The University College of London recently proposed “Universal Basic Services” — instead of providing people with income, provide the population housing, food, transport and access to IT in addition to healthcare (which is already free). This would cost 42B pounds and represents just 2.3% of UK’s GDP.
This is just one of many ideas and I’m hopeful we’ll see plenty of experimentation on this. I’ll end by re-sharing the end of a prior note on the importance of not relying on technology to solve our problems —
Technology isn’t going to suggest a “universal basic income” experiment. We have to do that. It may not be the right answer. But, we need to cheer on the politicians in Hawaii and Finland who had the guts to experiment with it. And, if you are a critic and have better ideas, let’s hear about those too.
Similarly, technology isn’t going to automatically create cultures that are more welcoming to women and other minorities. We will have to choose to do so. And, we will have to experiment to find ways to make all this work.
But, if there is a powerful lesson in here, it is that technology is simply a tool that we humans use to be, well, human. To wield it well, we have to choose to learn from our experiences to exercise good judgment and show ourselves to be capable of compassion, benevolence and wisdom.
For all of us chasing the lure of the next cool piece of technology, it is worth remembering that the companies, tools, societies, and algorithms we create are simply reflections of who we are.
As recent events have shown us, we can do a much better job in using technology to showcase our humanity.
The buck stops here.
On that note, I plan to take a break from writing these notes through December. And, in conclusion, I thought I’d go back to the point of essays being about trying to figure things out. That perfectly explains my rationale for starting to write bi-weekly (then, weekly) “notes” on technology earlier this year. I had so many questions about what was going on and wanted to explore them, one at a time. It has been a truly wonderful journey so far.
The biggest challenge has been carving out time and energy over the weekend while attempting to be a half decent first year parent. That will be food for thought in December.
Happy holidays!
Links for additional reading (with 5 of the notes mentioned above)
- Essays — on Paul Graham’s blog
- Concerns about automation — on Pew
- Oil rig image — on Medium
- Universal Basic Services — on UCL
- Horses, cars and the disruptive decade — on Notes by Ada
- Monopolies and advertising — on Notes by Ada
- How to think about the artificial intelligence wave — on Notes by Ada
- The imminent unraveling of CPG giants — on Notes by Ada
This is an edition of a bi-weekly technology newsletter called Notes by Ada. If you like this and would like free weekly notes via email, please just subscribe here.
