Artificial intelligence does not give us a “Get out of ethics free” card.Zeynep Tufekci
There are actually people all over the world running this software, and we call them Bitcoin miners. Anyone can become a Bitcoin miner. You can go download the software right now and run it in your computer and try to collect some bitcoins. I can’t say that I would recommend it, because right now, the puzzle is so hard and the network is so powerful, that if I tried to mine Bitcoin on my laptop, I probably wouldn’t see any for about two million years. The miners, professional miners, use this special hardware that’s designed to solve the puzzle really fast. Now, the Bitcoin network and all of this special hardware, there are estimates that the amount of energy it uses is equivalent to that of a small country. So, the first set of cryptocurrencies are a little bit slow and a little bit cumbersome. But the next generation is going to be so much better and so much faster.
Pretty damn funny.
And another one in a similar vein.
Finally educating myself about the blockchain. These videos are a good place to start.
Don Tapscott: How the blockchain is changing money and business
Bettina Warburg: How the blockchain will radically transform the economy
The future state of any single job lies in the answer to a single question: To what extent is that job reducible to frequent, high-volume tasks, and to what extent does it involve tackling novel situations? On frequent, high-volume tasks, machines are getting smarter and smarter. Today they grade essays. They diagnose certain diseases. Over coming years, they’re going to conduct our audits, and they’re going to read boilerplate from legal contracts. Accountants and lawyers are still needed. They’re going to be needed for complex tax structuring, for pathbreaking litigation. But machines will shrink their ranks and make these jobs harder to come by.
99% of my learning in the last decade has happened online, so this resonates with me.
Arthur Benjamin thinks that the end goal of teaching Mathematics at school should be Statistics rather than Calculus. He has a point: in terms of understanding things in the real world, Statistics is definitely more powerful. These ideas are quite compatible with those of Conrad Wolfram, who thinks that we should be using computers more extensively in Mathematics education.
The mathematics curriculum that we have is based on a foundation of arithmetic and algebra. And everything we learn after that is building up towards one subject. And at top of that pyramid, it’s calculus. And I’m here to say that I think that that is the wrong summit of the pyramid… that the correct summit, that all of our students, every high school graduate should know, should be statistics: probability and statistics.
Conrad Wolfram gives a thought provoking talk on a different way to teach Mathematics in schools.
We’ve had the biggest transformation of any ancient subject that I could ever imagine with computers. Calculating was typically the limiting step, and now often it isn’t. So I think in terms of the fact that math has been liberated from calculating. But that math liberation didn’t get into education yet. See, I think of calculating, in a sense, as the machinery of math. It’s the chore. It’s the thing you’d like to avoid if you can, like to get a machine to do. It’s a means to an end, not an end in itself, and automation allows us to have that machinery.
Mathematics is a tool that we use to solve problems. So we should enthuse children with its the power to do precisely this: solve problems, answer questions and build things.
Stephen Lund combines two of my passions: technology and exercise. Awesome. Durban Doodles coming soon.
… but be careful with your plots: they might be misinterpreted.
Amy Cuddy gives a great talk. Provided me with lots to think about and I will happily confess that I have struck a few power poses (but only after ensuring that I am quite alone)!
There is just one thing that troubles me about the talk. The plot below.
The choice of the scale on the y-axis gives the impression that risk tolerance in the Low Power group is roughly 30% of that in the High Power group. This strongly supports her hypothesis. However, careful inspection reveals that the correct ratio is actually around 70%. It might be unintentional, but in my opinion, a plot of ratio scale data should always have axes which go all the way to zero!