Maybe if the trees are planted correctly and are still alive, the government would requires the farmers to water them or face punishment, leaving no water for the crops.
The median income for a man in 1940 was $956. In 2010, the median income was $33,276. Women in 1940 earned 62 cents for every dollar a man earned. In 2010, women earned 74 cents for every dollar a man earned. In 2019 the income numbers probably has grown by another 20% just because of inflation.
So basically education cost grows only slightly faster than median income. Given the biggest portion of the cost is human capital, this makes economical sense.
I don't think not using their products is a solution. Even if you don't use facebook, your friends and colleagues have your name and phone number on their phone, and your friends upload photos with your face in them. You may also share the wifi with family members so facebook knows where you are indirectly.
As we are all parts of the society that we can't escape from, regulation matters a lot to everybody who may or may not use facebook products.
95% false positive rate is extremely good for surveillance, as the cost of false positive is low (wasted efforts by the police). That means for every 20 people the police investigate, one is a target.
Algorithmic traders focus on short-term market movements. The investment decisions described in the study are about long-term foundamental of companies. As long as enough investors prefer cash flow to capital reinvestment on the earning report, the strategy will continue to work.
Cutting costs and investments can easily dress up short-term financial performance at the cost of long-term productivity. But it will look good for investors who don't understand the underlying matter and rely on simplistic metrics to make investment decisions.
I remember back in college when I applied for a job in a multi-national company, I didn't get a math screening quiz that applicants from outside of United States had to take. The quiz was pretty easy middle school math that would take 15 minutes to complete.
It turns out that the reason is that screening for basic math competency could be discrimination, because it reduces the chance of hiring for minorities who do less well at math testing. If the quiz were carried out in US, the company would need to prepare some report stating that math is essential to the job, which would be very cumbersome and costly to do scientifically.
I found it ridiculous as the position clearly needed math and I believe basic arithmatic is a valuable skill to ask for majority of the jobs, even for low-skill positions like cashier at Walmart. While eliminating discrimination is a great cause, all the band-aids to make the issue look less bad is shameful. Instead of improving basic education for minority communities (which costs some money now with high return from enhanced labor productivity and less welfare), our governments/society artificially discriminate in the opposite direction and suppress valid criteria that are statistically unfavorable to minorities.
I'm not a lawyer either. But I remember that explicit racial quota are illegal.But in another precedence, diversity is considered a valid objective. So having preference that favor minority for the sake of diversity is OK. That is the case for a lot of hiring and admission processes now: No explicit quota, but a soft preference towards diversity, which usually means favoring under-represented racial and gender groups.
If I understand it correctly, it is only discrimination if employer cannot demonstrate the criteria are needed for work performance. Race and gender are not related to performance in most work categories. In the case of body types in sports, they are.
Chinese government utilize some pretty good machine learning to analyze and monitor those cameras. Techniques include:
- Vehicle plates recognition. They are automatically captured and mapped. Chinese police can get the complete historical routes of any car around major cities in real time just buy entering the number.
- Activity detection. If something interesting is happening in front of a camera (e.g. two people running in front of a camera middle of the night), AI detects that and pops the view up in front of humans for further action. Because less than 1% of cameras contain any useful info at any moment, they don't need that many humans to watch those cameras live.
- Face recognition. For many cameras, Face capture and recognition is running live and report any criminals or targeted personnel to police.
- Footage markup. If police need to go through the camera footage manually, the recording playback can skip the uninteresting parts to save time.
Combining these with unrestricted real-time integration of other data sources, such as real time GPS from mobile apps, cell tower call history from telecoms, network traffic inspection and remote spying capabilities, Chinese police forces can pretty much find anybody very quickly. They are also known to have state of the art big data platforms developed in house.
One anecdote I read: Somebody killed a person in a small city middle of the night, removed battery of his phone, ran to his car parked on street, drove a couple of hundred miles to another middle sized city, only to be caught in a motel next morning. How? Complete camera footage covering his walking path, vehicle plate tracking all the way to his destination, and motel check-in system that is also integrated with police.
I agree with most of your observations but disagree with your interpretations.
China's per capita GDP is only 8000 USD (vs 57000 for USA). So average Chinese people are still poor, and only few people are rich. But that's what is supposed to happen in a developing country undergone huge socio-economic changes.Also impoverished districts and poor people on streets can be found in pretty much any country, developed or not.
Older Chinese people (born before 1980) are mostly savers with mortgage paid off. Younger Chinese in big cities are more open to spending. Because those older people still hold majority of the existing wealth, China is a saver economy overall. That may change when younger generations start to take over. Housing is expensive and bubbly in big cities and certain regions but more affordable in smaller cities and rural areas. There is no property tax on housing in China and rent is expected to rise for many years to come. So high property cost is not as crazy as the price comparison suggests.
Chinese economy has some problems. Its debt load and housing bubble may bring major slowdown to the economy. But a recession will not be the end of China. Economic cycles should occur in China anyway. USA has experienced many financial crises and recessions and is still doing fine.
Pollution is bad in China, as in many other developing countries and in US and Europe a hundred years ago. That does not contradict its leading status in green-tech investment and research. Big problems lead to big problem-solving effort and political support.