Here is a digest of the best links I found each week for anyone who might be interested.

Pandemic: the reality we live in

It’s not a great week. US daily new cases reached new high. In order to safely reopen the economy, the country needs to significantly increase its testing capability. One technique is “pool testing”: which group samples from multiple people and test them together. This approach can quickly filter those large volume of negative cases so it would “go from a half a million tests a day to potentially 5 million individuals tested per day”. As the article points out, pooling only makes sense in places with low rates of Covid-19 and increases the risk of a false negative. This technique helps to scale up the broader disease surveillance strategy, but still relies on the same PCR technique as individual tests.

To understand the current test shortages, it’s better to first know How Coronavirus Tests Actually Work. It’s a complicated process to test the coronavirus.

However, “the bottleneck slowing down test results is not a technical one. It’s about logistics and supplies.”

Besides the common RT-PCR technique described above, there are other types of tests: antigen test and antibody test. Each of them provides different values with its own limitations. Here is a nice 9-minute video explanation.

Not everyone need to be tested for coronavirus. Hospitalized and symptomatic individuals, healthcare providers, first responders, essential works and other high-risk groups should be prioritized for testing.

Besides the supply chain problem, FDA regulation also complicated the testing strategy at an earlier phase. Here is a CDC chief defending the testing failure.

Johns Hopkins University’s COVID-19 Testing Insights Initiative tracks trends in COVID-19 cases and tests across all states. (see the article I shared previously explaining why Coronavirus Case Counts Are Meaningless).

“As testing capacity increases, considering confirmed new cases, testing rates, and percent positivity together gives us a fuller picture of COVID-19 in a particular state or region.”

Disruptions: how it might be different

Nesta publishes a deep dive into China’s AI-powered approach towards public sectors. There has been rapid progress of utilizing data and AI in China to address wide-ranging real world problems from urban management to public healthcare. Many of the applications are “too often default to narratives about authoritarianism or the foreign policy implications of a global AI arms race.”

There are some really interesting findings in this report:

China’s AI innovation successes are not always due to cutting-edge technologies. Instead, success in China is often down to rapid deployment and scaling of existing AI technologies.

Alibaba’s City Brain project consolidates data feeds from 700 IT systems, including carrier base service data, bus GPS data, to realtime traffic signal timing, etc. It integrates AI solutions to solve an array of problems, such as:

optimizes bus frequencies based on travel supply and demand, determines shuttle routes, and controls taxi dispatches to minimize the delay rates at key venues and transportation hubs;
facilitates emergency response for ambulances and firefighters, by coordinating traffic lights to give emergency response vehicles priority passage to the sites of emergency;
improves waste collection through the placement of sensors with low energy consumption and high durability in the traditional trash bins;
manages parking lots with one integrated system, from sensor-based vehicle detection, communication gateway, digital parking panels, kiosks for payments, mobile applications for drivers and an efficient parking management system.

Some of these problems are very familiar to people who have lived in those large populated Asian cities.

While AI is dramatically changing China’s education ecosystem, it could also end up reinforcing inequalities. “Three key factors have laid the unique conditions for China’s current AI education boom: the government’s national push to develop AI technologies, Chinese parents’ willingness to pay for their children’s education and the vast quantities of student data available to fuel new algorithms. One of the most significant challenges is whether or not AI technologies can be widely implemented in the existing Chinese public school system.”

AI ethic in China is a complicated topic, which is mixed of global standard, privacy, safety, transparency and surveillance. However, AI is meant to “improve the functioning of the existing institutions, not replace or reform them.”

Insights: raise the bar for ourselves

David Perell’s Ultimate Guide to Writing Online is a must read to start writing online. The most important source for growth is network effect. Content has network effect As author points out, “Content build on itself. It multiplies and compounds.” He shares a lot of great insights on distribution, which includes improving both discovery and stickiness. The focus on content and distribution will help one to build a personal monopoly based the unique intersection of their knowledge, personality, and skills. While I am still building a regular writing habit outside of work, I really love some of the advice he shares and will follow many of those myself.

Leadership: the ideas for better collaboration

I found a lot of fun to go over these 40 Favorite Interview Questions that are non-technical and culture related. It’s always hard to have that kind of question that can open the candidate, reveal more about themselves, and not vacuous. My favorite three are all about open-mindedness:

Tell me about a time you strongly disagreed with your manager. What did you do to convince him or her that you were right? What ultimately happened?
When was the last time you changed your mind about something important?
If I were to go and speak to people who don’t think very highly of you, what would they say?

Economy: the science hidden among fallacies

New Urban Econ Research Shows the Macroeconomic Benefits of Big Cities: “The `fundamental tradeoff’ of urban economics is that cities create more of both positive and negative externalities (spillovers to other city residents) as they grow.” It’s interesting to see how land use regulation should be considered in urban models. E.g. the congestion of existing commutes is shown to be more fundamental in limiting growth due to more votes for strict regulations.

Here is the Story of Singapore, where we can find the most gorgeous cities (if you have watched the latest season of West World). But, it’s built on top of a different culture, politics, and philosophy from US.