# The Phenomenal World

## About the Phenomenal World

The Phenomenal World is a new publication that publishes 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; and evolving institutions. We also post our weekly newsletter, a roundup of recommended reading from across the social sciences. Posts are wide-ranging in subject matter, length, and style.

The 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.

## CLAIMS THAT CAN'T BE TESTED

### What policy lessons can we derive from UBI experiments?

Political philosopher KARL WIDERQUIST of Georgetown has published a 92-page book examining historical and current basic income pilots, the difficulties of extrapolating from policy research to policy, and “the practical impossibility of testing UBI.”

In his introduction, Widerquist mentions that the challenges for translating research into policy stem not only from the science, but also from the audience’s moral preferences and judgments, which are particularly heightened in the basic income discourse:

“Except in the rare case where research definitively proves a policy fails to achieve its supporters’ goals, reasonable people can disagree whether the evidence indicates the policy works and should be introduced or whether that same evidence indicates the policy does not work and should be rejected. This problem greatly affects the UBI discussion because supporters and opponents tend to take very different moral positions. Many people, including many specialists, are less than fully aware of the extent to which their beliefs on policy issues are driven by empirical evidence about a policy’s effects or by controversial moral evaluation of those effects. For example, mainstream economic methodology incorporates a money-based version of utilitarianism. Non-money-based utilitarianism was the prevailing ethical framework when basic mainstream economic techniques were developed but it lost prominence decades ago.”

Widerquist also writes lucidly on considerations for how to communicate scientific caveats and takeaways. The full book is available here. ht Lauren who comments: "It’s incredibly difficult to test every aspect of many, many policies (including most that are currently at full national scale). Testing a given welfare policy arguably only has to get decision makers to a point where it can be determined that the policy substantially helps those who need it and doesn’t hurt anyone as a result."

• Activist Stanislas Jourdan spoke at the European Parliament in September about a basic income for Europe. Video of the presentation is here; slides are here. On the financing question, Jourdan proposes VAT ("already the most harmonized tax at EU level, large and reliable tax base"), as well as a European Corporation Tax, carbon taxes, and "quantitative easing for the people."

## 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.

## HARD CAPS

### Economic growth vs. natural resources

A recent Foreign Policy op-ed by JASON HICKEL examines “green growth,” a policy that calls for the absolute decoupling of GDP from the total use of natural resources. Hickel synthesizes three studies and explains that even in high-efficiency scenarios, economic growth makes it impossible to avoid unsustainably using up natural resources (including fossil fuels, minerals, livestock, forests, etc).

“Study after study shows the same thing. Scientists are beginning to realize that there are physical limits to how efficiently we can use resources. Sure, we might be able to produce cars and iPhones and skyscrapers more efficiently, but we can’t produce them out of thin air. We might shift the economy to services such as education and yoga, but even universities and workout studios require material inputs. Once we reach the limits of efficiency, pursuing any degree of economic growth drives resource use back up.”

The op-ed sparked debate about the state of capitalism in the current climate crisis, most notably in an Bloomberg op-ed by NOAH SMITH, who claims that Hickel is a member of “a small but vocal group of environmentalists telling us that growth is no longer possible—that unless growth ends, climate change and other environmental impacts will destroy civilization.” Though Smith’s op-ed doesn’t directly engage with many of Hickel’s points, his general position prompted a clarifying (and heated)response from Hickel:

“Noah is concerned that if we were to stop global growth, poor countries would be ‘stuck’ at their present level of poverty. But I have never said that poor countries shouldn’t grow—nor has anyone in this field of study (which Noah would know had he read any of the relevant literature). I have simply said that we can’t continue with aggregate global growth.

...
While poor countries may need some GDP growth, that should never—for any nation, rich or poor—be the objective as such. The objective should be to improve human well-being: better health, better education, better housing, happiness, etc. The strategy should be to target these things directly. To the extent that achieving these goals entails some growth, so be it. But that’s quite different from saying that GDP needs to grow forever.”

• From a study on the limits of green growth: “GDP cannot be decoupled from growth in material and energy use. It is therefore misleading to develop growth-oriented policy around the expectation that decoupling is possible. GDP is increasingly seen as a poor proxy for societal wellbeing. Society can sustainably improve wellbeing, including the wellbeing of its natural assets, but only by discarding GDP growth as the goal in favor of more comprehensive measures of societal wellbeing.” Link.
• In a recent article, Juan Moreno-Cruz, Katharine L. Ricke, and Gernot Wagner discuss ways to approach the climate crisis and argue that “mitigation (the reduction of carbon dioxide and other greenhouse gas emissions at the source) is the only prudent response.” Link.

## 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.

## MIDDLE WAGE

### Questioning the great transition into a "global middle class"

Economist STEVE KNAUSS, in a new paper published by the CANADIAN JOURNAL OF DEVELOPMENT STUDIES, examines the "myth" of the global middle class and the claim that the \$2/day measurement tells us anything substantive about poverty and inequality around the world.

"On the defensive in recent years, advocates of globalization have taken to highlighting achievements in developing countries, where globalization has supposedly pulled the majority out of poverty and catapulted them into the swelling "global middle class" remaking our world. This article provides a critical look at this interpretation. Carefully reviewing the global income distribution data behind such claims, it presents original calculations that generate new stylized facts for the globalization era.

The global income distribution approach does potentially have much to offer in terms of revealing the complexity of these changes, but in order to do so, greater attention and resources should be devoted to deepening our knowledge of the socio-historical changes underpinning the new realities of class formation and how they relate to the observed changes in global incomes. Instead of, or in addition to, constructing groups according to income thresholds, or national/global based deciles, ventiles or percentiles, more research should start from the other end, identifying national and global groups based on similarities in class formation and then attempting to trace such trajectories through the global income distribution."

Link to the article, and link to an ungated manuscript version. Jason Hickel comments:

"The question is: does their new petty income from the informal sector compensate for their loss of rural land, livestock, etc? It is not clear that it does. Therefore, we cannot say that this is a straightforward narrative of 'progress'—at least not in all regions."

• Development economist Morten Jerven with a 2010 paper diving into the metrics question in the context of poverty in Africa: "The article therefore concludes that it is futile to use GDP estimates to prove a link between income today and existence of pro-growth institutions in the past, and recommends a searching reconsideration of the almost exclusive use of GDP as a measure of relative development." Link.

## Cash and Income Studies: A Literature Review of Theory and Evidence

What happens when you give people cash? How do they use the money, and how does it change their lives? Every cash study on this list is different: the studies vary in intervention type, research design, location, size, disbursement amount, and effects measured. The interventions listed here include basic income and proxies--earned income tax credits, negative income tax credits, conditional cash transfers, and unconditional cash transfers. The variety present here prevents us from being able to make broad claims about the effects of universal basic income. But because of its variety, this review provides a sense of the scope of research in the field, capturing what kinds of research designs have been used, and what effects have been estimated, measured, and reported. The review also allows us to draw some revealing distinctions across experimental designs.

If you’re interested in creating a UBI policy, there are roughly three levels of effects (after ODI) that you can examine.

## MATERIAL UNDERSTANDING

### The full resource stack needed for Amazon's Echo to "turn on the lights"

In a novel new project, KATE CRAWFORD and VLADAN JOLER present an "anatomical case study" of the human labor, data, and planetary resources necessary for the functioning of an Amazon Echo. A 21-part essay accompanies an anatomical map (pictured above), making the case for the importance of understanding the complex resource networks that make up the "technical infrastructures" threaded through daily life:

"At this moment in the 21st century, we see a new form of extractivism that is well underway: one that reaches into the furthest corners of the biosphere and the deepest layers of human cognitive and affective being. Many of the assumptions about human life made by machine learning systems are narrow, normative and laden with error. Yet they are inscribing and building those assumptions into a new world, and will increasingly play a role in how opportunities, wealth, and knowledge are distributed.

The stack that is required to interact with an Amazon Echo goes well beyond the multi-layered 'technical stack' of data modeling, hardware, servers and networks. The full stack reaches much further into capital, labor and nature, and demands an enormous amount of each. Put simply: each small moment of convenience – be it answering a question, turning on a light, or playing a song – requires a vast planetary network, fueled by the extraction of non-renewable materials, labor, and data. The scale of resources required is many magnitudes greater than the energy and labor it would take a human to operate a household appliance or flick a switch."

Link to the full essay and map.

• More on the nuanced ethical dilemmas of digital technology: "Instead of being passive victims of (digital) technology, we create technology and the material, conceptual, or ethical environments, possibilities, or affordances for its production of use; this makes us also responsible for the space of possibilities that we create." Link.
• As shared in our April newsletter, Tim Hwang discusses how hardware influences the progress and development of AI. Link.

## 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.

## THE JANUS FACE

### The paradoxical outcomes of university-centered economic growth

A recent paper by RICHARD FLORIDA and RUBEN GAETANI takes an empirical look at the role of research universities in anchoring local economies and driving economic growth. The paper examines the density of patenting and financial investment within the internal geographies of specific American cities and argues that knowledge agglomeration exacerbates economic, occupational, and spatial segregation.

“Although universities certainly affect national levels of innovation and growth, research has shown that they tend to affect innovation and growth by operating through more localized channels. The roles played by Stanford University in the rise and economic performance of Silicon Valley and of MIT in the Boston-Cambridge ecosystem are cases in point.

Universities constitute a rare, irreproducible asset at the local level. At the same time, it is increasingly clear that the knowledge-economy metros and so-called college towns suffer from relatively high levels of inequality and segregation.”

Set to be released in the October issue of MANAGERIAL & DECISION ECONOMICS, the paper presents a nuanced exploration of agglomeration economies and complicates the use of universities as levers for economic revitalization, job creation, and mutual prosperity.

Link to the working paper.

• As spotlighted in a November newsletter, Lyman Stone discusses national problems with the role of the US higher education system: “The problems we face are: (1) the regional returns to higher education are too localized, (2) the price of higher education is bid up very high, (3) the traditional entrepreneurial player, state governments, is financially strained or unwilling, (4) private entrance is systematically suppressed by unavoidable market features.” Link.
• At CityLab, Richard Florida examined venture-capital invested start-ups and found they disproportionately clustered in metropolitan regions with high-performing universities. Link.
• For a deep dive into the role universities play in economic and spatial development, see Margaret O’Mara’s book on Cold War era “Cities of Knowledge." Link.