Finally, Airbnb extends the opportunity for supplemental income to hundreds of thousands of households. I think it is no coincidence that the sharing economy took off during the economic crisis, when people throughout the United States and Europe needed extra income. Half of Airbnb hosts are moderate or low income. [...] 47 percent of Airbnb hosts say that hosting allowed them to stay in their homes.

The opportunity to work on a project-by-project basis involves trade-offs. There is more independence and flexibility but fewer worker protections and rights. This too tends to skew toward the preferences of younger workers who are less focused on entitlement programs and who don't enter the workforce expecting to have just a few employers over their lifetime.

This might be manageable if the laborer is providing very expensive, highly sought-after engineering skills, but if you are a janitor, having to migrate from a full-time employer with benefits such as workers' compensation and health insurance to brokering your services on a sharing-economy platform will lead to less well-being. When the janitor has to list his spare bedroom on Airbnb, it is not supplemental income--it is survival income. As workers enter middle age and have kids, the need for benefits grows. If more of the labor force is sharing economy-based temporary employment without benefits, it hammers the working class and pushes them into safety net programs. For all the efficiencies of the sharing economy, toward the end of the life or if a worker becomes sick or injured, the responsibility of government increases. Worker protections have shifted from employers to taxpayer-funded government solutions.

Yet as these economic changes take place [...] the role of the state as a regulator has been diminished.

As the sharing economy grows as a share of the total economy, the safety net needs to grow with it. It's a necessary cost for allowing loose labor markets to work without much regulation, and if it generates enormous amounts of wealth for the platform owners, then the platform owners can and should help pay for added costs to society.

[...] Fraud protection is a built-in part of the financial world we live in, which we've simply come to accept as the cost of doing business. But Bitcoin at its best could make fraud impossible unless one's private key is stolen and make the thieves easy to find even if a key is stolen. The result could be a major drop in fraud. Furthermore, by codifying trust for high-value transactions, the blockchain could wipe out middlemen and friction in a variety of transactions, creating consumer surplus. On the global stage, it could also help bring frontier countries into the economic mainstream.

[...] annual losses to intellectual property theft from China exceed $300 billion, comparable to the total amount of goods exported annually from the United States to all of Asia. The NSA director at the time, Keith Alexander, has estimated the total value of all American intellectual property at $5 trillion, of which China is stealing 6 percent each year.

Precision agriculture will not end hunger in India or turn its subsistence-level farmers into serious agribusinesses, but in an environment of scarcity, it can take those scarce resources, be they seed, fertilizer, or water, and get the most out of them. India does not have a national network of agronomist to provide expertise and resources to its country's farmers as China, the Americas, and Europe do. The budgetary resources in India are spread too thin. [...]

Serendipity fades with everything we hand over to algorithms. Most of these algorithms are noiseless. They gently guide us in our choices. But we don't know why we are being guided in certain directions or how these algorithms work. And because they constitute the value of a company's intellectual property, there is an incentive to keep them opaque to us.

Who owns the data is as important a question as who owned the land during the agricultural age and who owned the factory during the industrial age. Data is the raw material of the information age.

Correlations made by big data are likely to reinforce negative bias. Because big data often relies on historical data or at least the status quo, it can easily reproduce discrimination against disadvantaged racial and ethnic minorities. The propensity models used in many algorithms can bake in a bias against someone who lived in the zip code of a low-income neighborhood at any point in his or her life. If an algorithm used by human resources companies queries your social graph and positively weighs candidates with the most existing connections to a workforce, it makes it more difficult to break in in the first place. In effect, these algorithms can hide bias behind a curtain of code.

[...] it is largely unregulated because we need it for economic growth and because efforts to try and regulate it have tended not to work; the technologies are too far-reaching and are not built to recognize the national boundaries of our world's 196 nation-states.

Yet would it be best to try to shut down these technologies entirely if we could? No. Big data simultaneously helps helps solve global challenges while creating an entirely new set of challenges. [...]

The choices we make about how we manage data will be as important as the decisions about managing land during the agricultural age and managing industry during the industrial age. We have a short window of time--just a few years, I think--before a set of norms set in that will be nearly impossible to reverse. Let's hope humans accept the responsibility for making these decisions and don't leave it to the machines.

The high-water mark for Belarus and the Internet is a social media-savvy graduate student in Massachusetts named Evgeny Morozov, who writes neo-Luddite screeds against American technology companies, advancing the official views of Russia and Belarus.