Manufacturing Consensus


Essay by M. Anthony Mills: “…Yet, the achievement of consensus within science, however rare and special, rarely translates into consensus in social and political contexts. Take nuclear physics, a well-established field of natural science if ever there were one, in which there is a high degree of consensus. But agreement on the physics of nuclear fission is not sufficient for answering such complex social, political, and economic questions as whether nuclear energy is a safe and viable alternative energy source, whether and where to build nuclear power plants, or how to dispose of nuclear waste. Expertise in nuclear physics and literacy in its consensus views is obviously important for answering such questions, but inadequate. That’s because answering them also requires drawing on various other kinds of technical expertise — from statistics to risk assessment to engineering to environmental science — within which there may or may not be disciplinary consensus, not to mention grappling with practical challenges and deep value disagreements and conflicting interests.

It is in these contexts — where multiple kinds of scientific expertise are necessary but not sufficient for solving controversial political problems — that the dependence of non-experts on scientific expertise becomes fraught, as our debates over pandemic policies amply demonstrate. Here scientific experts may disagree about the meaning, implications, or limits of what they know. As a result, their authority to say what they know becomes precarious, and the public may challenge or even reject it. To make matters worse, we usually do not have the luxury of a scientific consensus in such controversial contexts anyway, because political decisions often have to be made long before a scientific consensus can be reached — or because the sciences involved are those in which a consensus is simply not available, and may never be.

To be sure, scientific experts can and do weigh in on controversial political decisions. For instance, scientific institutions, such as the National Academies of Sciences, will sometimes issue “consensus reports” or similar documents on topics of social and political significance, such as risk assessment, climate change, and pandemic policies. These usually draw on existing bodies of knowledge from widely varied disciplines and take considerable time and effort to produce. Such documents can be quite helpful and are frequently used to aid policy and regulatory decision-making, although they are not always available when needed for making a decision.

Yet the kind of consensus expressed in these documents is importantly distinct from the kind we have been discussing so far, even though they are both often labeled as such. The difference is between what philosopher of science Stephen P. Turner calls a “scientific consensus” and a “consensus of scientists.” A scientific consensus, as described earlier, is a relatively stable paradigm that structures and organizes scientific research. By contrast, a consensus of scientists is an organized, professional opinion, created in response to an explicit political or social need, often an official government request…(More)”.

If We Can Report on the Problem, We Can Report on the Solution


David Bornstein and Tina Rosenberg in the New York Times: “After 11 years and roughly 600 columns, this is our last….

David Bornstein: Tina, in a decade reporting on solutions, what’s the most important thing you learned?

Tina Rosenberg: This is a strange lesson for a column about new ideas and innovation, but I learned that they’re overrated. The world (mostly) doesn’t need new inventions. It needs better distribution of what’s already out there.

Some of my favorite columns were about how to take old ideas or existing products and get them to new people. As one of our columns put it, “Ideas Help No One on a Shelf. Take Them to the World.” There are proven health strategies, for example, that never went anywhere until some folks dusted them off and decided to spread them. It’s not glamorous to copy another idea. But those copycats are making a big difference.

David: I totally agree. The opportunity to learn from other places is hugely undertapped.

I mean, in the United States alone, there are over 3,000 counties. The chance that any one of them is struggling with big problems — mental health, addiction, climate change, diabetes, Covid-19, you name it — is pretty much 100 percent. But the odds that any place is actually using one of the most effective approaches to deal with its problems is quite low.

As you know, I used to be a computer programmer, and I’m still a stats nerd. With so many issues, there are “positive deviants” — say, 2 percent or 3 percent of actors who are getting significantly better results than the norm. Finding those outliers, figuring out what they’re doing that’s different, and sharing the knowledge can really help. I saw this in my reporting on childhood traumachronic homelessness and hospital safety, to name a few areas….(More)”

Are we really so polarised?


Article by Dominic Packer and Jay Van Bavel: “In 2020, the match-making website OkCupid asked 5 million hopeful daters around the world: “Could you date someone who has strong political opinions that are the opposite of yours?” Sixty per cent said no, up from 53% a year before.

Scholars used to worry that societies might not be polarised enough. Without clear differences between political parties, they thought, citizens lack choices, and important issues don’t get deeply debated. Now this notion seems rather quaint as countries have fractured along political lines, reflected in everything from dating preferences to where people choose to live.

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Just how stark has political polarisation become? Well, it depends on where you live and how you look at it. When social psychologists study relations between groups, they often find that whereas people like their own groups a great deal, they have fairly neutral feelings towards out-groups: “They’re fine, but we’re great!” This pattern used to describe relations between Democrats and Republicans in the US. In 1980, partisans reported feeling warm towards members of their own party and neutral towards people on the other side. However, while levels of in-party warmth have remained stable since then, feelings towards the out-party have plummeted.

The dynamics are similar in the UK, where the Brexit vote was deeply divisive. A 2019 study revealed that while UK citizens were not particularly identified with political parties, they held strong identities as remainers or leavers. Their perceptions were sharply partisan, with each side regarding its supporters as intelligent and honest, while viewing the other as selfish and close-minded. The consequences of hating political out-groups are many and varied. It can lead people to support corrupt politicians, because losing to the other side seems unbearable. It can make compromise impossible even when you have common political ground. In a pandemic, it can even lead people to disregard advice from health experts if they are embraced by opposing partisans.

The negativity that people feel towards political opponents is known to scientists as affective polarisation. It is emotional and identity-driven – “us” versus “them”. Importantly, this is distinct from another form of division known as ideological polarisation, which refers to differences in policy preferences. So do we disagree about the actual issues as much as our feelings about each other suggest?

Despite large differences in opinion between politicians and activists from different parties, there is often less polarisation among regular voters on matters of policy. When pushed for their thoughts about specific ideas or initiatives, citizens with different political affiliations often turn out to agree more than they disagree (or at least the differences are not as stark as they imagine).

More in Common, a research consortiumthat explores the drivers of social fracturing and polarisation, reports on areas of agreement between groups in societies. In the UK, for example, they have found that majorities of people across the political spectrum view hate speech as a problem, are proud of the NHS, and are concerned about climate change and inequality…(More)”.

‘Is it OK to …’: the bot that gives you an instant moral judgment


Article by Poppy Noor: “Corporal punishment, wearing fur, pineapple on pizza – moral dilemmas, are by their very nature, hard to solve. That’s why the same ethical questions are constantly resurfaced in TV, films and literature.

But what if AI could take away the brain work and answer ethical quandaries for us? Ask Delphi is a bot that’s been fed more than 1.7m examples of people’s ethical judgments on everyday questions and scenarios. If you pose an ethical quandary, it will tell you whether something is right, wrong, or indefensible.

Anyone can use Delphi. Users just put a question to the bot on its website, and see what it comes up with.

The AI is fed a vast number of scenarios – including ones from the popular Am I The Asshole sub-Reddit, where Reddit users post dilemmas from their personal lives and get an audience to judge who the asshole in the situation was.

Then, people are recruited from Mechanical Turk – a market place where researchers find paid participants for studies – to say whether they agree with the AI’s answers. Each answer is put to three arbiters, with the majority or average conclusion used to decide right from wrong. The process is selective – participants have to score well on a test to qualify to be a moral arbiter, and the researchers don’t recruit people who show signs of racism or sexism.

The arbitrators agree with the bot’s ethical judgments 92% of the time (although that could say as much about their ethics as it does the bot’s)…(More)”.

AI Generates Hypotheses Human Scientists Have Not Thought Of


Robin Blades in Scientific American: “Electric vehicles have the potential to substantially reduce carbon emissions, but car companies are running out of materials to make batteries. One crucial component, nickel, is projected to cause supply shortages as early as the end of this year. Scientists recently discovered four new materials that could potentially help—and what may be even more intriguing is how they found these materials: the researchers relied on artificial intelligence to pick out useful chemicals from a list of more than 300 options. And they are not the only humans turning to A.I. for scientific inspiration.

Creating hypotheses has long been a purely human domain. Now, though, scientists are beginning to ask machine learning to produce original insights. They are designing neural networks (a type of machine-learning setup with a structure inspired by the human brain) that suggest new hypotheses based on patterns the networks find in data instead of relying on human assumptions. Many fields may soon turn to the muse of machine learning in an attempt to speed up the scientific process and reduce human biases.

In the case of new battery materials, scientists pursuing such tasks have typically relied on database search tools, modeling and their own intuition about chemicals to pick out useful compounds. Instead a team at the University of Liverpool in England used machine learning to streamline the creative process. The researchers developed a neural network that ranked chemical combinations by how likely they were to result in a useful new material. Then the scientists used these rankings to guide their experiments in the laboratory. They identified four promising candidates for battery materials without having to test everything on their list, saving them months of trial and error…(More)”.

Countries’ climate pledges built on flawed data


Article by Chris Mooney, Juliet Eilperin, Desmond Butler, John Muyskens, Anu Narayanswamy, and Naema Ahmed: “Across the world, many countries underreporttheir greenhouse gas emissions in their reports to the United Nations, a Washington Post investigation has found. An examination of 196 country reports reveals a giant gap between what nations declare their emissions to be versus the greenhouse gases they are sending into the atmosphere. The gap ranges from at least 8.5 billion to as high as 13.3 billion tons a year of underreported emissions — big enough to move the needle on how much the Earth will warm.

The plan to save the world from the worst of climate change is built on data. But the data the world is relying on is inaccurate.

“If we don’t know the state of emissions today, we don’t know whether we’re cutting emissions meaningfully and substantially,” said Rob Jackson, a professor at Stanford University and chair of the Global Carbon Project, a collaboration of hundreds of researchers. “The atmosphere ultimately is the truth. The atmosphere is what we care about. The concentration of methane and other greenhouse gases in the atmosphere is what’s affecting climate.”

At the low end, the gap is larger than the yearly emissions of the United States. At the high end, it approaches the emissions of China and comprises 23 percent of humanity’s total contribution to the planet’s warming, The Post found…

A new generation of sophisticated satellites that can measure greenhouse gases are now orbiting Earth, and they can detect massive methane leaks. Data from the International Energy Agency (IEA) lists Russia as the world’s top oil and gas methane emitter, but that’s not what Russia reports to the United Nations. Its official numbers fall millions of tons shy of what independent scientific analyses show, a Post investigation found. Many oil and gas producers in the Persian Gulf region, such as the United Arab Emirates and Qatar, also report very small levels of oil and gas methane emission that don’t line up with other scientific data sets.

“It’s hard to imagine how policymakers are going to pursue ambitious climate actions if they’re not getting the right data from national governments on how big the problem is,” said Glenn Hurowitz, chief executive of Mighty Earth, an environmental advocacy group….(More)”.

Embrace Complexity Through Behavioral Planning


Article by Ruth Schmidt and Katelyn Stenger: “…Designing for complexity also requires questioning assumptions about how interventions work within systems. Being wary of three key assumptions about persistence, stability, and value can help behavioral designers recognize changes over time, complex system dynamics, and oversimplified definitions of success that may impact the effectiveness of interventions.

When behavioral designers overlook these assumptions, the solutions they recommend risk being short-sighted, nonstrategic, and destined to be reactive rather than proactive. Systematically confronting and planning for these projections, on the other hand, can help behavioral designers create and situate more resilient interventions within complex systems.

In a recent article, we explored why behavioral science is still learning to grapple with complexity, what it loses when it doesn’t, and what it could gain by doing so in a more strategic and systematic way. This approach—which we call “behavioral planning”—borrows from business strategy practices like scenario planning that play out assumptions about plausible future conditions to test how they might impact the business environment. The results are then used to inform “roughly right” directional decisions about how to move forward…(More)”

How 12th-century Genoese merchants invented the idea of risk


Essay by Karla Mallette: “Lately, we have all become risk assessment and risk management experts, thinking, talking and Tweeting about the chances we take when we engage in once-mundane activities. It’s hard to imagine doing without risk: the analytical instrument we use to calculate the advisability of undertakings that can result in gain or loss. Yet when the word risk entered the languages of western Europe during the 12th century (at roughly the same time as other words used to jigger the scales of Fortune: hazard and chance), it took some time to catch on. Niccolò Machiavelli (1469-1527) and Francesco Guicciardini (1483-1540) – the two great writers of the Italian 15th and 16th centuries who wrote about contingency and power while everything was collapsing around them – did not use the Italian rischio in the works for which they are best remembered, even though the Italians were early adopters of the word and the speculative behaviours it names.

The first known usage of the Latin word resicum – cognate and distant ancestor of the English risk – occurs in a notary contract recorded in Genoa on 26 April 1156. The captain of a ship contracts with an investor to travel to Valencia with the sum invested. The contract allocates the ‘resicum’ to the investor. In a typical arrangement, the captain received 25 per cent of the profit at the end of the journey. The investor or investors pocketed the resicum payout: the remaining 75 per cent. This contract also reminds us that the medieval Italian ship’s crew was an egalitarian society. It specifies that the voyage would be extended from Valencia to trade at Alexandria before returning to Genoa, but only if a majority of the men on board agreed.

Resicum worked a kind of practical magic in these early contracts. Canon law forbade the payment of interest on loans in medieval Europe (as Islamic law did in the eastern and southern Mediterranean). By inventing a bonus paid to the investor in the event of the successful completion of a journey, the resicum provided a workaround for venture capitalists and for the captain seeking capital. It also gave those who could not journey an opportunity to earn investment income. A small but significant proportion of the investors in these maritime contracts were retired seamen or women. Finally, it parcelled out the risk assumed by those who undertook the trans-Mediterranean journey…(More)”.

A Vision for the Future of Science Philanthropy


Article by Evan Michelson and Adam Falk: “If science is to accomplish all that society hopes it will in the years ahead, philanthropy will need to be an important contributor to those developments. It is therefore critical that philanthropic funders understand how to maximize science philanthropy’s contribution to the research enterprise. Given these stakes, what will science philanthropy need to get right in the coming years in order to have a positive impact on the scientific enterprise and to help move society toward greater collective well-being?

The answer, we argue, is that science philanthropies will increasingly need to serve a broader purpose. They certainly must continue to provide funding to promote new discoveries throughout the physical and social sciences. But they will also have to provide this support in a manner that takes account of the implications for society, shaping both the content of the research and the way it is pursued. To achieve this dual goal of positive scientific and societal impact, we identify four particular dimensions of the research enterprise that philanthropies will need to advance: seeding new fields of research, broadening participation in science, fostering new institutional practices, and deepening links between science and society. If funders attend assiduously to all these dimensions, we hope that when people look back 75 years from now, science philanthropy will have fully realized its extraordinary potential…(More)”.

How behavioral science could get people back into public libraries


Article by Talib Visram: “In October, New York City’s three public library systems announced they would permanently drop fines on late book returns. Comprised of Brooklyn, Queens, and New York public libraries, the City’s system is the largest in the country to remove fines. It’s a reversal of a long-held policy intended to ensure shelves stayed stacked, but an outdated one that many major cities, including Chicago, San Francisco, and Dallas, had already scrapped without any discernible downsides. Though a source of revenue—in 2013, for instance, Brooklyn Public Library (BPL) racked up $1.9 million in late fees—the fee system also created a barrier to library access that disproportionately touched the low-income communities that most need the resources.

That’s just one thing Brooklyn’s library system has done to try to make its services more equitable. In 2017, well before the move to eliminate fines, BPL on its own embarked on a partnership with Nudge, a behavioral science lab at the University of West Virginia, to find ways to reduce barriers to access and increase engagement with the book collections. In the first-of-its-kind collaboration, the two tested behavioral science interventions via three separate pilots, all of which led to the library’s long-term implementation of successful techniques. Those involved in the project say the steps can be translated to other library systems, though it takes serious investment of time and resources….(More)”.