from the world's big
The smart move: We learn more by trusting than by not trusting
Yet interpersonal trust is at its lowest point in 50 years.
We all know people who have suffered by trusting too much: scammed customers, jilted lovers, shunned friends. Indeed, most of us have been burned by misplaced trust.
These personal and vicarious experiences lead us to believe that people are too trusting, often verging on gullibility.
In fact, we don't trust enough.
Take data about trust in the United States (the same would be true in most wealthy democratic countries at least). Interpersonal trust, a measure of whether people think others are in general trustworthy, is at its lowest in nearly 50 years. Yet it is unlikely that people are any less trustworthy than before: the massive drop in crime over the past decades suggests the opposite. Trust in the media is also at bottom levels, even though mainstream media outlets have an impressive (if not unblemished) record of accuracy.
Meanwhile, trust in science has held up comparatively well, with most people trusting scientists most of the time; still, in some areas at least, from climate change to vaccination, a share of the population doesn't trust science enough – with devastating consequences.
Social scientists have a variety of tools to study how trusting, and how trustworthy, people are. The most popular is the trust game, in which two participants play, usually anonymously. The first participant is given a small amount of money, $10 say, and asked to decide how much to transfer to the other participant. The amount transferred is then tripled, and the second participant chooses how much to give back to the first. In Western countries at least, trust is rewarded: the more money the first participant transfers, the more money the second participant sends back, and thus the more money the first participant ends up with. In spite of this, first participants on average transfer only half the money they have received. In some studies, a variant was introduced whereby participants knew each other's ethnicity. Prejudice led participants to mistrust certain groups – Israeli men of Eastern origin (Asian and African immigrants and their Israeli-born offspring), or black students in South Africa – transferring them less money, even though these groups proved just as trustworthy as more esteemed groups.
If people and institutions are more trustworthy than we give them credit for, why don't we get it right? Why don't we trust more?
In 2017, the social scientist Toshio Yamagishi was kind enough to invite me to his flat in Machida, a city in the Tokyo metropolitan area. The cancer that would take his life a few months later had weakened him, yet he retained a youthful enthusiasm for research, and a sharp mind. On this occasion, we discussed an idea of his with deep consequences for the question at hand: the informational asymmetry between trusting and not trusting.
When you trust someone, you end up figuring out whether your trust was justified or not. An acquaintance asks if he can crash at your place for a few days. If you accept, you will find out whether or not he's a good guest. A colleague advises you to adopt a new software application. If you follow her advice, you will find out whether the new software works better than the one you were used to.
By contrast, when you don't trust someone, more often than not you never find out whether you should have trusted them. If you don't invite your acquaintance over, you won't know whether he would have made a good guest or not. If you don't follow your colleague's advice, you won't know if the new software application is in fact superior, and thus whether your colleague gives good advice in this domain.
This informational asymmetry means that we learn more by trusting than by not trusting. Moreover, when we trust, we learn not only about specific individuals, we learn more generally about the type of situations in which we should or shouldn't trust. We get better at trusting.
Yamagishi and his colleagues demonstrated the learning advantages of being trusting. Their experiments were similar to trust games, but the participants could interact with each other before making the decision to transfer money (or not) to the other. The most trusting participants were better at figuring out who would be trustworthy, or to whom they should transfer money.
We find the same pattern in other domains. People who trust the media more are more knowledgeable about politics and the news. The more people trust science, the more scientifically literate they are. Even if this evidence remains correlational, it makes sense that people who trust more should get better at figuring out whom to trust. In trust as in everything else, practice makes perfect.
Yamagishi's insight provides us with a reason to be trusting. But then, the puzzle only deepens: if trusting provides such learning opportunities, we should trust too much, rather than not enough. Ironically, the very reason why we should trust more – the fact that we gain more information from trusting than from not trusting – might make us inclined to trust less.
When our trust is disappointed – when we trust someone we shouldn't have – the costs are salient, and our reaction ranges from annoyance all the way to fury and despair. The benefit – what we've learnt from our mistake – is easy to overlook. By contrast, the costs of not trusting someone we could have trusted are, as a rule, all but invisible. We don't know about the friendship we could have struck (if we'd let that acquaintance crash at our place). We don't realise how useful some advice would have been (had we used our colleague's tip about the new software application).
We don't trust enough because the costs of mistaken trust are all too obvious, while the (learning) benefits of mistaken trust, as well as the costs of mistaken mistrust, are largely hidden. We should consider these hidden costs and benefits: think of what we learn by trusting, the people whom we can befriend, the knowledge that we can gain.
Giving people a chance isn't only the moral thing to do. It's also the smart thing to do.
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Andy Samberg and Cristin Milioti get stuck in an infinite wedding time loop.
- Two wedding guests discover they're trapped in an infinite time loop, waking up in Palm Springs over and over and over.
- As the reality of their situation sets in, Nyles and Sarah decide to enjoy the repetitive awakenings.
- The film is perfectly timed for a world sheltering at home during a pandemic.
Richard Feynman once asked a silly question. Two MIT students just answered it.
Here's a fun experiment to try. Go to your pantry and see if you have a box of spaghetti. If you do, take out a noodle. Grab both ends of it and bend it until it breaks in half. How many pieces did it break into? If you got two large pieces and at least one small piece you're not alone.
But science loves a good challenge<p>The mystery remained unsolved until 2005, when French scientists <a href="http://www.lmm.jussieu.fr/~audoly/" target="_blank">Basile Audoly</a> and <a href="http://www.lmm.jussieu.fr/~neukirch/" target="_blank">Sebastien Neukirch </a>won an <a href="https://www.improbable.com/ig/" target="_blank">Ig Nobel Prize</a>, an award given to scientists for real work which is of a less serious nature than the discoveries that win Nobel prizes, for finally determining why this happens. <a href="http://www.lmm.jussieu.fr/spaghetti/audoly_neukirch_fragmentation.pdf" target="_blank">Their paper describing the effect is wonderfully funny to read</a>, as it takes such a banal issue so seriously. </p><p>They demonstrated that when a rod is bent past a certain point, such as when spaghetti is snapped in half by bending it at the ends, a "snapback effect" is created. This causes energy to reverberate from the initial break to other parts of the rod, often leading to a second break elsewhere.</p><p>While this settled the issue of <em>why </em>spaghetti noodles break into three or more pieces, it didn't establish if they always had to break this way. The question of if the snapback could be regulated remained unsettled.</p>
Physicists, being themselves, immediately wanted to try and break pasta into two pieces using this info<p><a href="https://roheiss.wordpress.com/fun/" target="_blank">Ronald Heisser</a> and <a href="https://math.mit.edu/directory/profile.php?pid=1787" target="_blank">Vishal Patil</a>, two graduate students currently at Cornell and MIT respectively, read about Feynman's night of noodle snapping in class and were inspired to try and find what could be done to make sure the pasta always broke in two.</p><p><a href="http://news.mit.edu/2018/mit-mathematicians-solve-age-old-spaghetti-mystery-0813" target="_blank">By placing the noodles in a special machine</a> built for the task and recording the bending with a high-powered camera, the young scientists were able to observe in extreme detail exactly what each change in their snapping method did to the pasta. After breaking more than 500 noodles, they found the solution.</p>
The apparatus the MIT researchers built specifically for the task of snapping hundreds of spaghetti sticks.
(Courtesy of the researchers)
What possible application could this have?<p>The snapback effect is not limited to uncooked pasta noodles and can be applied to rods of all sorts. The discovery of how to cleanly break them in two could be applied to future engineering projects.</p><p>Likewise, knowing how things fragment and fail is always handy to know when you're trying to build things. Carbon Nanotubes, <a href="https://bigthink.com/ideafeed/carbon-nanotube-space-elevator" target="_self">super strong cylinders often hailed as the building material of the future</a>, are also rods which can be better understood thanks to this odd experiment.</p><p>Sometimes big discoveries can be inspired by silly questions. If it hadn't been for Richard Feynman bending noodles seventy years ago, we wouldn't know what we know now about how energy is dispersed through rods and how to control their fracturing. While not all silly questions will lead to such a significant discovery, they can all help us learn.</p>
What happens if we consider welfare programs as investments?
- A recently published study suggests that some welfare programs more than pay for themselves.
- It is one of the first major reviews of welfare programs to measure so many by a single metric.
- The findings will likely inform future welfare reform and encourage debate on how to grade success.
Welfare as an investment<p>The <a href="https://scholar.harvard.edu/files/hendren/files/welfare_vnber.pdf" target="_blank">study</a>, carried out by Nathaniel Hendren and Ben Sprung-Keyser of Harvard University, reviews 133 welfare programs through a single lens. The authors measured these programs' "Marginal Value of Public Funds" (MVPF), which is defined as the ratio of the recipients' willingness to pay for a program over its cost.</p><p>A program with an MVPF of one provides precisely as much in net benefits as it costs to deliver those benefits. For an illustration, imagine a program that hands someone a dollar. If getting that dollar doesn't alter their behavior, then the MVPF of that program is one. If it discourages them from working, then the program's cost goes up, as the program causes government tax revenues to fall in addition to costing money upfront. The MVPF goes below one in this case. <br> <br> Lastly, it is possible that getting the dollar causes the recipient to further their education and get a job that pays more taxes in the future, lowering the cost of the program in the long run and raising the MVPF. The value ratio can even hit infinity when a program fully "pays for itself."</p><p> While these are only a few examples, many others exist, and they do work to show you that a high MVPF means that a program "pays for itself," a value of one indicates a program "breaks even," and a value below one shows a program costs more money than the direct cost of the benefits would suggest.</p> After determining the programs' costs using existing literature and the willingness to pay through statistical analysis, 133 programs focusing on social insurance, education and job training, tax and cash transfers, and in-kind transfers were analyzed. The results show that some programs turn a "profit" for the government, mainly when they are focused on children:
This figure shows the MVPF for a variety of polices alongside the typical age of the beneficiaries. Clearly, programs targeted at children have a higher payoff.
Nathaniel Hendren and Ben Sprung-Keyser<p>Programs like child health services and K-12 education spending have infinite MVPF values. The authors argue this is because the programs allow children to live healthier, more productive lives and earn more money, which enables them to pay more taxes later. Programs like the preschool initiatives examined don't manage to do this as well and have a lower "profit" rate despite having decent MVPF ratios.</p><p>On the other hand, things like tuition deductions for older adults don't make back the money they cost. This is likely for several reasons, not the least of which is that there is less time for the benefactor to pay the government back in taxes. Disability insurance was likewise "unprofitable," as those collecting it have a reduced need to work and pay less back in taxes. </p>
What are the implications of all this?<div class="rm-shortcode" data-media_id="ceXv4XLv" data-player_id="FvQKszTI" data-rm-shortcode-id="3b407f5aa043eeb84f2b7ff82f97dc35"> <div id="botr_ceXv4XLv_FvQKszTI_div" class="jwplayer-media" data-jwplayer-video-src="https://content.jwplatform.com/players/ceXv4XLv-FvQKszTI.js"> <img src="https://cdn.jwplayer.com/thumbs/ceXv4XLv-1920.jpg" class="jwplayer-media-preview" /> </div> <script src="https://content.jwplatform.com/players/ceXv4XLv-FvQKszTI.js"></script> </div> <p>Firstly, it shows that direct investments in children in a variety of areas generate very high MVPFs. Likewise, the above chart shows that a large number of the programs considered pay for themselves, particularly ones that "invest in human capital" by promoting education, health, or similar things. While programs that focus on adults tend to have lower MVPF values, this isn't a hard and fast rule.</p><p>It also shows us that very many programs don't "pay for themselves" or even go below an MVPF of one. However, this study and its authors do not suggest that we abolish programs like disability payments just because they don't turn a profit.</p><p>Different motivations exist behind various programs, and just because something doesn't pay for itself isn't a definitive reason to abolish it. The returns on investment for a welfare program are diverse and often challenging to reckon in terms of money gained or lost. The point of this study was merely to provide a comprehensive review of a wide range of programs from a single perspective, one of dollars and cents. </p><p>The authors suggest that this study can be used as a starting point for further analysis of other programs not necessarily related to welfare. </p><p>It can be difficult to measure the success or failure of a government program with how many metrics you have to choose from and how many different stakeholders there are fighting for their metric to be used. This study provides us a comprehensive look through one possible lens at how some of our largest welfare programs are doing. </p><p>As America debates whether we should expand or contract our welfare state, the findings of this study offer an essential insight into how much we spend and how much we gain from these programs. </p>
Finding a balance between job satisfaction, money, and lifestyle is not easy.
- When most of your life is spent doing one thing, it matters if that thing is unfulfilling or if it makes you unhappy. According to research, most people are not thrilled with their jobs. However, there are ways to find purpose in your work and to reduce the negative impact that the daily grind has on your mental health.
- "The evidence is that about 70 percent of people are not engaged in what they do all day long, and about 18 percent of people are repulsed," London Business School professor Dan Cable says, calling the current state of work unhappiness an epidemic. In this video, he and other big thinkers consider what it means to find meaning in your work, discuss the parts of the brain that fuel creativity, and share strategies for reassessing your relationship to your job.
- Author James Citrin offers a career triangle model that sees work as a balance of three forces: job satisfaction, money, and lifestyle. While it is possible to have all three, Citrin says that they are not always possible at the same time, especially not early on in your career.