The main problem in AI ethics is called "the alignment problem". But it's exactly the same concept that appears in economics as a market failure called "agent-principal problem". We put people in charge and make them act on our behalf, but their incentives (objective function) are different than ours. The discussion in AI ethics would benefit greatly by borrowing from economics research.

My point is, we already have overlords who don't want the same things as us and it's already a big problem. Why should AI be worse?

It says it at the top. Weekly Parental Forename Transmission Rate. It's not a sample, it's just the percentage of children that were born each week who got named after their dad.

My take on the replication crisis is that it is something 60% bad incentives, 35% bad statistics and 5% malice. Bad incentives is the whole journal system, which incentivizes getting good results and does not deeply scrutinize methodology and source data, the lack of incentives for preregistration, poor quality journals existing, etc.

Bad statistics is mostly the fact that people interpret p<0.05 as true and p>0.05 as worthless results and use it as a threshold for publishing, rather than the crude statistical tool that it really is. Plus just a general bad understanding of statistics by most social scientists. I'm currently doing some research in causal inference, developing methodology that can be used in social science, and it's embarrassing how slow social scientists are in using tools from causal inference. In economics applications are usually 10-20 years behind the research but in psychology for example they often don't even attempt any kind of causal identification but then suggest that their studies somehow show causality.

Malice is scientists just outright faking data or cherry-picking. But even that is tied to the incentive structure. We should normalize publishing negative results

I understand that those are the takeaways, but where is the evidence? The author just jumps to some vaguely related topics as if it's evidence, while what he's really doing is spinning some kind of narrative, and the narrative is wrong.

About the takeaways:

1. As I explained in my comment, this is not true.
2. Who thinks that way? Everybody I know, both laymen and people in the field of Data Science and Machine Learning, have healthy skepticism of AI.
3. Having worked as a data scientist, I can attest that data scientists check their algorithms, use common sense, and put an emphasis on understanding their data.

Honestly,the article just reads to me as a boomer theory-focused economist who's upset of the turn towards quantitative and statistics-heavy approach that his field has taken. There is a certain (old) school of economists who prefer theoretical models and takes a rationalist over an empirical approach. The problem with their approach is that the theoretical models they build use assumptions that often turn out to be wrong. They use "common sense" rather than relying on data but the world is complex and many "common sense" assumptions don't actually hold.

I was oversimplifying my comments a bit. There is the curse of dimensionality. And in causal inference if you just use every variable as a confounder your model can also get worse because you're blocking forward paths. But if you know what you're doing it shouldn't be a problem. And I haven't met any ML practitioner or statistician who doesn't realize the importance of getting to understand your data and making proper modelling decisions.

That gets us into the realm of causal inference. This is not really what the author was talking about, but yes, it's a field that has a bunch of additional challenges. In this case, more data points might not help, but collecting data about additional variables might. In any case, getting more data will pretty much never cause your model to be worse.

The author has an embarrassingly bad understanding of statistics and machine learning and makes a very unclear argument. In fact, the opposite is true. The more data we have - the easier it is to find meaningful patterns. Variance - which is the thing that causes most spurious patterns, decreases with the root on the number of samples. The more data points you have, the more likely it is that if you have a true relationship between variables, you will pass whichever hypothesis test (such as the p-score). More data therefore allows us to set higher standards for hypothesis testing.

However, most of the arguments in the article don't even support this main hypothesis. Instead the author talks about unrelated things, such as some low-quality studies that found some weird correlations and about the replication crisis, which is a complex problem caused by many reasons, none of which is an abundance of data.

I feel like the author of this never really cared to understand Singer's philosophy. It's not only focused on individual actions. Singer has written books advocating for policy change in areas such as animal experimentation. He founded a non-profit that works on inspiring public awareness for animal welfare. He campaigned against tbe Vietnam war. Let me just quote this passage from Wikipedia

Singer has criticised the United States for receiving "oil from countries run by dictators ... who pocket most of the" financial gains, thus "keeping the people in poverty." Singer believes that the wealth of these countries "should belong to the people" within them rather than their "de facto government. In paying dictators for their oil, we are in effect buying stolen goods, and helping to keep people in poverty." Singer holds that America "should be doing more to assist people in extreme poverty". He is disappointed in U.S. foreign aid policy, deeming it "a very small proportion of our GDP, less than a quarter of some other affluent nations."

The ignorance of the author also shows when he calls Singer a preference utilitarian, a position that he has backed away from almost 10 years ago.

Calling Singer a supporter of the status quo is dishonest. What the author is really trying to criticize him about is for not being communist. It is Jacobin magazine, after all. For the author, anybody that comes short of flatly rejecting capitalism is a supporter of the status quo

Are you vegan? Because honestly I think you're a bit naive about the public support for animal welfare. There are quite a lot of people who don't give a single shit about animal welfare. They're not the deciding factors when it comes to this kind of politics though. It's the farmers. Farmers are one of the strongest lobby groups in most countries and they oppose anything that hurts their bottom line. I'm from Israel, we have the highest percentage of vegans in the world and we had a big campaign a while ago to stop importing livestock (they would suffer a lot on the trip). The campaign failed.

I'm not saying that you can't find public support for some animal welfare policies, and many groups in the Effective Altruism space do work on that, but it's usually stuff like "hey maybe you can't keep this chicken in an individual cage where she literally can't move and instead put her in a cage with other chickens where she maybe will be able to take a few steps without stepping into another chicken". We're very far from like, banning slaughterhouses.

That's not true that his only focus is on individual actions though. In his Animal Liberation, there's a whole section of the book where he talks about the mostly unnecessary cruelty of Animal Experimentation, and how it should be solved by advocacy and changing the laws. The Effective Altruism movement for with Singer is considered to be somewhat of an ideological father, uses advocacy, grassroots movements, lobbying, etc in a variety of issues.

However, in some issues individual action can be the best way. Some issues, like Veganism for example that Singer is an advocate of, do not have enough public support at this point to change laws and policies. Same with poverty alleviation. I'm sure pretty much everybody in the movement would be happy to see countries give foreign aid in the forms that have been shown to be effective. However countries generally see foreign aid as a tool to buy influence and that's unlikely to change soon.