WorksInProgress: “Our view is that prediction markets on everything – liquid markets over a wide range of important topics – will not work without subsidies. These subsidies would be expensive, so other forms of information aggregation are usually more attractive. The scarcity of prediction markets in the world today is not a failure of regulation, but a sign that they are much less promising than many advocates, including the authors of this piece, once hoped.”
FT: “What can other countries learn from Singapore? Be small. If the US could hive off 320mn people and 99 per cent of its land mass, it would be an easier nation to mould. Second, have a maritime rather than continental setting. The likes of Bolivia are missing a trick there. Third, and foremost, get an individual of the calibre of Lee Kuan Yew as founder-leader…In the end, Singapore is too particular, too sui generis in both its assets and liabilities, to constitute a template. It has but one universal lesson: the importance of an open mind.”
Mint: “More than half the value addition in the manufacturing sector is now generated in rural areas and about two-thirds of rural income comes from non-farm activities. Rural development can be accelerated to achieve double-digit growth rates and make India’s land distribution less lopsided.”
WSJ: “We are told repeatedly about the benefits of delayed gratification, of being more disciplined and less hedonistic. The grasshopper and the ant, and all that. And no doubt, for many that lesson is an important one: Learning to save for the future and to know our spending priorities can be extremely useful. But, in reality, many people lean in the opposite direction. They are a bit too disciplined, and have a nasty habit of putting off the sweet things in life—potentially until it’s too late. It’s a lesson that is just as important to learn as the lesson of delayed gratification.”
Ethan Mollick: “Most companies do not have an artificial intelligence strategy, yet they are already riddled with the technology. A survey published this month by LinkedIn suggested that three-quarters of white-collar workers have used AI for work, and four-fifths of them have done so from their own accounts and devices. They are not seeking the permission of their employers; in fact, they are hiding it from them, because they are afraid of the consequences. What that means is managers need to stop asking if AI will matter in their organisations and start shaping how it will matter. That is going to introduce a wide range of new challenges that will alter what management means. Our organisational structures are built around the idea that human workers are the only form of intelligence at work. That is no longer true…By leveraging AI…as a coach and mentor, organisations can scale employee development and support it to a degree that was previously impossible — creating freedom from boring tasks along the way.”
