I don't think that will be that popular (on humans). Embyro selection - which is what they actually appear to use in Gattaca - on the other hand will probably be common place.

I do think gene editing in agricultural plants and animals will be common, but it's pretty risky and expensive compared to just sequencing a bunch of embryos and picking the good ones (in most cases).

Your first point is almost a good one, but the last three lines give away the game - you're the politician here.

Real incomes in the US have matched their 1999 levels only this year. That fact represents a radical departure from all postindustrial economic behavior, but to you if students or professors want to talk about why that is - from any perspective - they're already too "political" and should be silenced. Be serious.

It's also not generally appreciated that the quantitative part of Marx represents the foundations of econometrics even to this day, and while things have become generally more sophisticated since his time, that aspect of his work is not particularly questioned or devalued by contemporary economists with right-wing political leanings.

Indeed, but interestingly large parts of textbook macroeconomics performed (and continue to perform) very well during the crisis. ISLM / ISMP style models have accurately predicted the behavior of economic actors of all different scales this past decade. Some economic programs had neglected these approaches for some time, while others had continued them, but moved them onto a more rigorous mathematical framework. (See for example Romer's treatment of ISMP).

IMHO any movement in economics towards empirical validation and towards more robust models (i.e. less overfitting) is for the better.

There is an ongoing debate in macroeconomics about the role of inequality. Does inequality impact growth, and if so negatively or positively? How do we measure inequality, and more generally distribution of resources? How do economic systems, and specific policy choices, influence the distribution of income and resources?

These are fundamental aspects of economic study.

Again...what is "globalization?" How do we measure it? How has it benefited or harmed different countries and different segments of society within countries? How do we measure that? Why have these effects been visited on these particular groups? Can we build quantitative models around these ideas? Do those models have predictive power? How can we measure their predictive power? How can we establish confidence in model outputs?

Especially given that there are conflicting viewpoints across the political spectrum, it's hard to see an inherent political aim in discussing this important contemporary economic movement (e.g. there are right-wing populists and left-wing populists who write that they oppose globalization, and right- and left-wing thinkers who favor globalization, in both cases often for different reasons).

How do different climate outlooks effect economic prospects? How does the existence of these outlooks effect economic behavior of individuals, firms, and nations? How do we measure climate risk? What are the economic effects of potential mitigation efforts? What level of risk should motivate what degree of mitigation cost, given various estimates of uncertainty? How can these ideas be placed in a quantitative framework? How can model output be assessed given the scale and ongoing nature of the topic? Are there past climatic events with known economic impacts? How do we measure those impacts? How do they compare to current data? And on and on.

It only takes a moment's reflection to note the importance of these questions, and their relevance to the study of economics. That's probably why there are economists from all over the world, and from all over the political spectrum, who spend their academic (or corporate) lives on just these ideas.

Nothing could reveal a deeper lack of understanding about contemporary biology than that sentence. It simultaneously rejects our actual findings and betrays an erroneous confidence in the power of current methods, all without any apparent irony.

Under other circumstances I would feel compelled to say more, but the parent is either a troll or an ideologue and I don't want to waste the time.

Our (USA) funding system was designed under the assumption that ~30% of grant applications will receive funding. Today, that number is a little more than 5%. Science prospers when practitioners compete for excellence, rather than because there isn't enough to go around.

In this case, because they all had to read and write English. The Indian and American programmers probably grew up speaking English. The Russian and Chinese programmers who took the test were selected for preexisting proficiency in nonnative language.

That's not how statistics work. If the samples are random, but different in size, the smaller sample will have a more biased average. So in this case, if we assume the samples are random, we just know that the Russian and Chinese averages are much less representative than the American and Indian averages.

However, we also know that the samples were biased. American and Indian programmers speak English. The testing company is based in Palo Alto, CA. Their website is totally in English. The Russian and Chinese programmers were selected not only for motivation to take an online test, but for a preexisting ability to speak a nonnative language.

He's right. Show us the wage spike and we'll believe in your worker shortage.

Hacking? TFA is just about test scores.

On a side note, the sample size of 1.4 million doesn't matter if the sample is non-random. Many more Indian and American programmers took the test, and their average scores are most likely lower for that reason, even if there is no additional bias in the Russian and Chinese scores.

That's a big "if" though...what India and the United States have in common with the testing company is the English language. The Russian and Chinese samples are sampling Russian and Chinese people who speak English.

Not really, apparently he had permission.

Actually it's more basic even than that - from what I've read today the bot would obey requests to parrot incoming content. Most of the crazy things it said were literal repetition of such inputs, though I guess eventually whatever pretraining it had was overwhelmed by the new inputs.

You admit that "replacing BART track with roads" was at best a non sequitor, and then refer to subregions not served by BART. OK, then.

Right, it's the people who don't own cars that are the rich and privileged. You need to get out more.

Does making up arbitrary numbers to suit one's ideology fly in your line of work? Interesting.

Agreed. This thread has a lot of uninformed comments from folks who've never lived or worked in the Bay Area, making ludicrous claims that eliminating BART to "make space" for "more roads" would solve all our problems.