It's Not What You Know... Edition
1. Social Enterprise: A few weeks ago I noted that Etsy was under pressure from an activist investor for behaving like a B Corp (which it is (was?)). I missed the notice that the investor won: Etsy layed off 80 employees and fired the CEO/Chairman. Here's a piece reflecting on the Etsy saga that is emblematic of much of what I think is wrong in social enterprise rhetoric. The argument that social enterprises have to be ruthless competitors may sound good (to some) but it ignores the exact issue that is at the heart of social enterprises: how do you manage the trade-offs. It's worthless--less than worthless, I should probably say "actively harmful"--to pretend there are no trade-offs or to imply that there is value in advice like "be ruthlessly competitive except for in these parts of your business model." It's why efforts like B Corporations that don't have any governance teeth are a distraction, and why even efforts like For Benefit Corporations that do have governance teeth are fraught.
In other social enterprise-ish news, I can't resist a story about a star rapper, off-grid solar power in Senegal and Chinese investors. You can't either can you? On a more practical level here's Devanshi Vaid on the lack of information flow on social enterprise in India.
And here's Felix Salmon with some remarkably clear reframing of an important wing of social investment: if a foundation endowment can't get high investment returns in the near term, don't cut back on grantmaking, accelerate it!
2. Our Algorithmic Overlords: The Atlantic has a long piece on how cryptocurrencies like Bitcoin, purportedly designed to limit centralized authority, actually can become tools of authoritarianism. You don't have to go all the way to cryptocurrencies though, as I try to frequently point out. Digital currency of any sort can easily become weaponized by authority, even authority that isn't fully authoritarian.
I wasn't sure whether to include this in "Social Enterprise" or "Our Algorithmic Overlords" because it's a bit of both, through an extraordinary lens: Venezuela's bonds. As Matt Levine relates, Goldman Sachs (sort-of) bought some bonds from Venezuela (sort-of) that (sort-of) prop up an authoritarian government apparently bent on starving people. But no one is really responsible for this decision because of the way governance of the investment funds is set-up and which all point back to an index by which fund manager performance is measured. (I know, this is confusing and complicated, but it's worth it). In this case everyone is pointing to some arbitrary set of decisions as responsible for their behavior and denying any responsibility for moral judgment. If we struggle with these issues already, how much worse are they going to get with the arbitrary set of decisions are made by an algorithm that we don't really understand?
But people are more worried about algorithms driving their cars, than about algorithms ruling their moral decisions.
3. Statistics, Research Quality and External Validity: Admittedly this is just going to be a hodge-podge of stuff loosely connected.
There's apparently some new work suggesting wide-spread errors or research misconduct in medical RCTs. I haven't had time to look at this much, so here's Andrew Gelman's thoughts which will be much better than anything I would have come up with.
Stuart Buck this week asked whether we're nearing the point of more papers about the 1970s pre-K experiments in the US than there were kids in the experiments. It got me thinking about external validity. Here's an honest question: to a first approximation, do you think there's more in common between, say, microenterprises in Zambia and the Philippines in 2017 or between Chapel Hill, NC in 1972 and Detroit in 2017?
Here's David Evans working through a framework for external validity judgments proposed by Mary Ann Bates and Rachel Glennerster. I'd have to say at this point that I'd lean toward applying lessons from Zambia to the Philippines more than from Chapel Hill to Detroit.
4. American Inequality: The major focus on inequality in America has been on income and wealth but it's not just the money, it's the instability. A substantial part of inequality of income, wealth and stability seemingly can be traced back to exclusionary zoning, which limits lower-income people from getting access to jobs and pushes up both the income and wealth of the already wealthy. Hsieh and Moretti estimate that exclusionary zoning has also "lowered aggregate US growth by more than 50% from 1964 to 2009."
And here's a review of The Financial Diaries--or alternatively, an essay on how to measure poverty--in the New York Review of Books.
5. It's Not What You Know...: Two weeks ago I made a big deal about the technology of management and how underrated it is within policy and economics. Here's a paper about spreading management technology among Indian tech start-ups, finding that peer networks work to change behavior. The authors seem to attribute this to knowledge diffusion--but based on other research I'm skeptical this is a "knowledge" story rather than a "behavior change" story.
It's not just a management knowledge story. In the energy space, product knowledge, even gained via product demonstrations from peers who are using and very satisfied with the product, fails to induce demand for solar home systems in India in another new paper. And Alcott and Greenstone show that information failures don't play a role in energy efficiency program results in the United States. I'm reminded of this earlier work by Meredith, Robinson, Walker and Wydick on health good purchasing that pretty conclusively demonstrates that the barrier to purchase isn't knowledge, it's not having the money that matters.
When will "high level machine intelligence" arrive? Is a 25% chance in the next 25 years scary or reassuring? Source
