Barack Obama on Artificial Intelligence, Autonomous Cars, and the Future of Humanity | WIRED

The president in conversation with MIT’s Joi Ito and WIRED editor-in-chief Scott Dadich.

[Obama:] Joi made a very elegant point, which is, what are the values that we’re going to embed in the cars? There are gonna be a bunch of choices that you have to make, the classic problem being: If the car is driving, you can swerve to avoid hitting a pedestrian, but then you might hit a wall and kill yourself. It’s a moral decision, and who’s setting up those rules?

[Obama:] Part of what makes us human are the kinks. They’re the mutations, the outliers, the flaws that create art or the new invention, right? We have to assume that if a system is perfect, then it’s static. And part of what makes us who we are, and part of what makes us alive, is that we’re dynamic and we’re surprised. One of the challenges that we’ll have to think about is, where and when is it appropriate for us to have things work exactly the way they’re supposed to, without surprises?

DADICH: But there are certainly some risks. We’ve heard from folks like Elon Musk and Nick Bostrom who are concerned about AI’s potential to outpace our ability to understand it. As we move forward, how do we think about those concerns as we try to protect not only ourselves but humanity at scale?

OBAMA: Let me start with what I think is the more immediate concern—it’s a solvable problem in this category of specialized AI, and we have to be mindful of it. If you’ve got a computer that can play Go, a pretty complicated game with a lot of variations, then developing an algorithm that lets you maximize profits on the New York Stock Exchange is probably within sight. And if one person or organization got there first, they could bring down the stock market pretty quickly, or at least they could raise questions about the integrity of the financial markets.

[Obama:] most people aren’t spending a lot of time right now worrying about singularity—they are worrying about “Well, is my job going to be replaced by a machine?” … if we are going to successfully manage this transition, we are going to have to have a societal conversation about how we manage this. … The social compact has to accommodate these new technologies, and our economic models have to accommodate them.

[Obama:] As a consequence, we have to make some tougher decisions. We underpay teachers, despite the fact that it’s a really hard job and a really hard thing for a computer to do well. So for us to reexamine what we value, what we are collectively willing to pay for—whether it’s teachers, nurses, caregivers, moms or dads who stay at home, artists, all the things that are incredibly valuable to us right now but don’t rank high on the pay totem pole—that’s a conversation we need to begin to have.

Source: Barack Obama on Artificial Intelligence, Autonomous Cars, and the Future of Humanity | WIRED

Brexit and Trump – How the hell did we get to this point?

We got here by failing to ensure that enough demographics of people enjoyed the benefits of globalization and the continued progress of technology. Which is a little depressing since about 75% of the global population has done quite well – but that last 25% are relatively concentrated geographically and they are becoming concentrated politically.

 

Source: Milanovic, B., Lead Economist, World Bank Research Department, Global income inequality by the numbers. Annotations by James Plunkett.

The Story of Globalization in 1 Graph | The Atlantic

 

The ideological divide in the years to come will be the one May staked out this week: for openness to the world, or against it.

We aren’t “left” or “right” any more; we are either for globalization or against it | Quartz

Why an unhackable mobile phone is a complete marketing myth | TechCrunch

Consider this: The smartphone in your pocket is 10 times more powerful than the fastest multi-million dollar supercomputers of just 20 years ago. There are tens of millions of lines of software in that phone of yours. There are hundreds of apps written by more than one million developers, some of whom are hackers, and some of whom are just incompetent at security. And then there are chips in your phone that run sophisticated software, from companies located in countries all around the world, all of which have security bugs.

The complexity is mind-boggling — and so are all the security vulnerabilities that exist and will be found in the future.

Source: Why an unhackable mobile phone is a complete marketing myth | TechCrunch

Developer hiring and the market for lemons

You need an information asymmetry to create a market for lemons … both current and prospective employers have incomplete information, and whose information is better varies widely. It’s actually quite common for prospective employers to have better information than current employers!

Another problem with the idea that “great” developers are sticky is that this assumes that companies are capable of creating groups that developers want to work for on demand. This is usually not the case.

The result of this dynamic is that, as a dev, if you join a random team, you’re overwhelmingly likely to join a team that has a lot of churn. Additionally, if you know of a good team, it’s likely to be full.

Another problem with the idea that “great” developers are impossible to find because they join companies and then stick is that developers (and companies) aren’t immutable.

Is developer hiring a market for lemons? Well, it depends on what you mean by that. Both developers and hiring managers have incomplete information. It’s not obvious if having a market for lemons in one direction makes the other direction better or worse. The fact that joining a new team is uncertain makes developers less likely to leave existing teams, which makes it harder to hire developers. But the fact that developers often join teams which they dislike makes it easier to hire developers. What’s the net effect of that? I have no idea.

Source: Developer hiring and the market for lemons

Table of Contents — How to Think like a Computer Scientist: Interactive Edition

An interactive version of the How to Think Like a Computer Scientist book

The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions.

The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem solving skills.

Source: Table of Contents — How to Think like a Computer Scientist: Interactive Edition