Phenomenal World

December 14th, 2018

Phenomenal World

Cash Transfer, Knowledge Transfer

An interview with Johannes Haushofer

Johannes Haushofer is assistant professor of Psychology and Public Affairs at Princeton University. His work includes development economics, behavioral economics, psychology, and neurobiology. We spoke to him primarily about a neopolicy idea on which he has unique expertise: unconditional cash transfers (UCTs). Along with Jeremy Shapiro, he has led research on GiveDirectly’s UCT program in Kenya, and his work on short-term and long-term effects there has both provided the field with new evidence and set a course for deeper questions. Now Johannes is starting to work on a UBI pilot in a major US city, across the developing-nation/developed-nation divide.

We spoke to Johannes broadly about (1) where he sees the state of the evidence, (2) what conclusions can be drawn from developing nations to developed, and (3) his larger vision for the march of evidence regarding policies like this.

We’re grateful that Johannes took the time to speak with us and to inaugurate this interview series. Interviewing him was Michael Stynes, who leads JFI, as well as Sidhya Balakrishnan and Lauren Burns-Coady of JFI. This interview has been condensed and edited.

MS: Johannes, first of all, thank you very much for speaking with us. Your work is incredibly important to the entire basic income/cash transfer research community and I’m happy that Lauren, Sidhya, and I will have the opportunity to talk through some of your work. We are particularly interested in the point in which a pilot intervention becomes viable policy. Here specifically I want to try to understand what the state of the evidence is in favor of unconditional cash transfers in the developing world, and how your research there might extend to the developed world. Can we start with an overview of the work you’ve done so far, particularly on cash transfers in Kenya?

JH: The main completed study that I’ve done so far is a randomized controlled trial [RCT] on GiveDirectly’s UCT program in Kenya, that we finished maybe five years ago, and published two years ago. In that study, we delivered transfers that are on average $700, which is about two years of per capita consumption, to poor families in western Kenya. And we found pretty sizeable effects on outcomes like consumption, asset holdings, psychological well-being, and income. That piece of evidence is part of a larger body of evidence, which is that cash transfers do a bunch of good things. So they increase consumption, and other welfare outcomes we care about. There are lots of studies that make us think that. And there aren’t a lot of the negative effects that people were original worried about—temptation goods, conflicts, violence, and so on. We’re just now working on a paper that shows pretty large decreases in domestic violence, as a result of cash transfers.

I would say that the state of the evidence is: cash transfers do pretty good things. The 1.0 question for cash transfers is, “Is it better to get cash than to get nothing?” I think the answer to that is yes, it’s better to get cash. This isn’t surprising to many people, but it is surprising to some people who thought the poor are bad at handling money, and were going to blow it and make their lives worse.

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November 9th, 2018

Banking with Imprecision

​In 1596, Spanish troops under the leadership of the Duke of Medina-Sidonia set fire to their own ships in the waters near Cadiz. The sinking of these thirty-two vessels was a tactical necessity: a joint Anglo-Dutch navy had annihilated the slapdash defenses of the city, driving the Spanish ships off to nearby Puerto Real. The Spanish had preferred to see their ships sunk rather than captured by the enemy. Cadiz itself was occupied and sacked, and its most prominent civilians were held for ransom. War, as the Spanish were acutely aware, was very costly. Later that very year, Philip II, King of Spain, would declare bankruptcy. 1

Though he was one of the most powerful monarchs of the era, it is difficult to sympathize with the sheer magnitude of the work with which King Philip II of Spain had to contend. Not only did he have to protect his Iberian possessions, but he also had to prosecute a war against the recalcitrant Dutch in the Low Countries, outmaneuver the Protestants in France, and maintain a bulwark against the Turks in the Mediterranean. 2

In their book, Lending to the Borrower from Hell, Drelichman and Voth have done a remarkable job of illuminating Spanish finance in the 16th century.Notably, the fiscal machinery underpinning imperial operations was managed mostly by a tight-knit cartel of Genoese bankers. Sovereign lending, astonishingly, allowed for a plethora of state actions in a time before instant communication. The foundations of empire rested on a relatively simple model: control certain streams of income and then borrow against them. The institutional origins of our modern sovereign lending come from this tradition. Dealing with uncertainty is an inherent part of this model – now as it was then. What is of use to modern scholars is how the same problem was conceived of and partly surmounted by our institutional forebears.

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October 18th, 2018

Machine Ethics, Part One: An Introduction and a Case Study

The past few years have made abundantly clear that the artificially intelligent systems that organizations increasingly rely on to make important decisions can exhibit morally problematic behavior if not properly designed. Facebook, for instance, uses artificial intelligence to screen targeted advertisements for violations of applicable laws or its community standards. While offloading the sales process to automated systems allows Facebook to cut costs dramatically, design flaws in these systems have facilitated the spread of political misinformation, malware, hate speech, and discriminatory housing and employment ads. How can the designers of artificially intelligent systems ensure that they behave in ways that are morally acceptable--ways that show appropriate respect for the rights and interests of the humans they interact with?

The nascent field of machine ethics seeks to answer this question by conducting interdisciplinary research at the intersection of ethics and artificial intelligence. This series of posts will provide a gentle introduction to this new field, beginning with an illustrative case study taken from research I conducted last year at the Center for Artificial Intelligence in Society (CAIS). CAIS is a joint effort between the Suzanne Dworak-Peck School of Social Work and the Viterbi School of Engineering at the University of Southern California, and is devoted to “conducting research in Artificial Intelligence to help solve the most difficult social problems facing our world.” This makes the center’s efforts part of a broader movement in applied artificial intelligence commonly known as “AI for Social Good,” the goal of which is to address pressing and hitherto intractable social problems through the application of cutting-edge techniques from the field of artificial intelligence.

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October 10th, 2018

Who cares about stopping rules?

Can you bias a coin?

Challenge: Take a coin out of your pocket. Unless you own some exotic currency, your coin is fair: it's equally likely to land heads as tails when flipped. Your challenge is to modify the coin somehow—by sticking putty on one side, say, or bending it—so that the coin becomes biased, one way or the other. Try it!

How should you check whether you managed to bias your coin? Well, it will surely involve flipping it repeatedly and observing the outcome, a sequence of h's and t's. That much is obvious. But what's not obvious is where to go from there. For one thing, any outcome whatsoever is consistent both with the coin's being fair and with its being biased. (After all, it's possible, even if not probable, for a fair coin to land heads every time you flip it, or a biased coin to land heads just as often as tails.) So no outcome is decisive. Worse than that, on the assumption that the coin is fair any two sequences of h's and t's (of the same length) are equally likely. So how could one sequence tell against the coin's being fair and another not?

We face problems like these whenever we need to evaluate a probabilistic hypothesis. Since probabilistic hypotheses come up everywhere—from polling to genetics, from climate change to drug testing, from sports analytics to statistical mechanics—the problems are pressing.

Enter significance testing, an extremely popular method of evaluating probabilistic hypotheses. Scientific journals are littered with reports of significance tests; almost any introductory statistics course will teach the method. It's so popular that the jargon of significance testing—null hypothesis, $p$-value, statistical significance—has entered common parlance.

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October 2nd, 2018

The "Next Big Thing" is a Room

If you don’t look up, Dynamicland seems like a normal room on the second floor of an ordinary building in downtown Oakland. There are tables and chairs, couches and carpets, scattered office supplies, and pictures taped up on the walls. It’s a homey space that feels more like a lower school classroom than a coworking environment. But Dynamicland is not a normal room. Dynamicland was designed to be anything but normal.

Led by the famous interface designer Bret Victor, Dynamicland is the offshoot of HARC (Human Advancement Research Community), most recently part of YCombinator Research. Dynamicland seems like the unlikeliest vision for the future of computers anyone could have expected.

Let’s take a look. Grab one of the scattered pieces of paper in the space. Any will do as long as it has those big colorful dots in the corners. Don’t pay too much attention to those dots. You may recognize the writing on the paper as computer code. It’s a strange juxtaposition: virtual computer code on physical paper. But there it is, in your hands. Go ahead and put the paper down on one of the tables. Any surface will do.

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October 1st, 2018

About Phenomenal World

Phenomenal World is a new publication that distributes research, analysis, and commentary on applied social science. We chose this name for our blog because we hope to publish work that addresses the social world in all its apparent complexity.

Our contributors are economists, philosophers, social scientists, data scientists, and policy researchers. You’ll find posts on metaresearch; basic income, welfare and the commonwealth; digital ethics; education; economic history; social policy; and evolving institutions. We also host the archival of our weekly newsletter, a roundup of recommended reading from across the social sciences. Posts are wide-ranging in subject matter, length, and style.

Phenomenal World is managed by staff of the Jain Family Institute, an applied research organization that works to bring just research and policy from theoretical conception to actual implementation in society. We welcome submissions. Please see our About page for more information on submitting, and for the sign-up form for our newsletter.

Thank you for reading.

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