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No news is good news? Think again
Information economics suggests that "no news" means somebody is hiding something. But people are bad at noticing that.
- An experiment in information sharing shows that no news often means people have something to hide.
- Other people seem to be blissfully unaware of this.
- The results suggest that market forces are insufficient to "close the information gap" between buyers and sellers.
A proverb that never seems to die is the oft-heard, "No news is good news." However, a new study published in the American Economic Journal: Microeconomics suggests that this not only goes against logic but also reduces returns in an information sharing game.
A marketplace for information
According to the principles of information economics, most firms have an incentive to release information on their products if the cost of doing so is low. The belief is that customers will treat firms that don't release information as being the same, so the one that does provide information — say, about the quality of the manufacturing — looks better in comparison for doing so. Over time, this should lead to more information being disclosed voluntarily as people try to cash in on the effect. An "unraveling" effect also occurs, with customers assuming the worst about those keeping secrets.
However, like a lot of ideas in economics, this one rests on the assumption that consumers will behave rationally or according to theory. Sometimes, people just don't catch on to the fact that some businesses might have an incentive only to reveal good news or to brush unflattering details under the rug.
To help shed light on how people actually behave and why they do so, the researchers set up an experiment based on an information sharing game where participants could win cash prizes for using information economics to their advantage.
An experiment in information economics
The main set of experimental sessions involved two randomly matched players, one as an information sender and one as an information receiver. The sender would be given a secret number between one and five by a computer. They then had a choice to reveal this number to the receiver or not. Lying was not allowed.
The receiver, who either saw the number or a blank space on their screen, then reported what they thought the secret number was. While the senders always saw and submitted whole numbers, receivers could guess any half unit between 1 and 5.
Sender players earned rewards as receiver guesses went higher, no matter what the secret number actually was. Receivers earned more for accuracy, with perfect determination of the secret number getting the most money.
The experimental set-up matches the theory; namely, the best "moves" are for the sender to always show the number unless it is one, and the receiver should always guess the number is one if they don't see a number.
Theory meets reality
But, things get muddy when theory meets reality.
After 45 rounds of play, senders tended to be between 3 and 7 percent off from the highest possible payouts, while receivers were 9 to 13 percent off. Numbers that you would expect to have been shown by the senders remained secret. Receivers made strange guesses, sometimes not trusting the values they saw (despite being told lying was against the rules) or guessing higher than they should have when shown a blank screen.
The authors mention that the receivers often seemed "insufficiently skeptical of nondisclosure" and failed to realize that the sender was probably hiding something from them. This effect could be somewhat mitigated by providing them feedback, though it had to be offered repeatedly for their improvement to be sustained.
They also opined that some receivers might have been confused by the rules of the game and played poorly as a result.
For the first time in a study like this, the researchers also asked the senders what they thought about the receivers. Their choices to reveal the number or not were often driven by a belief that the receivers would respond to not getting any information by guessing just below the middle of the number range rather than the lowest value as they should have.
As it turns out, they were right, with the average blind guess being above two. While the senders were not following the theory by acting this way, neither were their opponents — and thus, they were playing the game optimally.
It seems you really should play your opponent and not your hand.
Market forces are insufficient to close the information gap
The authors summarize the possible real world application of these findings in their report:
"These findings suggest that unless buyers receive fast and precise feedback about mistakes after each transaction, market forces can be insufficient to close the information gap between sellers and buyers. For the products that naturally offer such feedback — say cereals that taste crunchy and t-shirts that hold color fast — voluntary disclosure may converge to the unraveling predictions after a buyer purchases the product many times. However, for product attributes with less immediate feedback — such as the fat content of salad dressing and the cleanliness of a restaurant kitchen — voluntary disclosure may not converge to the unraveling results. In these situations, mandatory disclosure may be necessary if the policy goal is complete disclosure."
Oh, before you go, I promise that I didn't leave out any information from the study. Nothing important anyway.
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Scientists find routes using arches of chaos that can lead to much faster space travel.
- Researchers discovered a route through the Solar System that can allow for much faster spacecraft travel.
- The path takes advantage of "arches of chaos" within space manifolds.
- The scientists think this "celestial superhighway" can help humans get to the far reaches of the galaxy.
Humanity could be making its way through the Solar System much faster thanks to the discovery of a new superhighway network among space manifolds. Don't get your engines roaring along this "celestial autobahn" just yet, but the researchers believe the new pathways can eventually be used by spacecraft to get to the outer reaches of our Solar System with relative haste.
The celestial highway could get comets and asteroids from Jupiter to Neptune in less than a decade. Compare that to hundreds of thousands or even millions of years it might ordinarily take for space objects to traverse the Solar System. In a century of travel along the new routes, a 100 astronomical units could be covered, project the scientists. For reference, an astronomical unit is the average distance from the Earth to the Sun or about 93 million miles.
The international research team included Nataša Todorović, Di Wu, and Aaron Rosengren from the Belgrade Astronomical Observatory in Serbia, the University of Arizona, and UC San Diego. Their new paper proposes a dynamic route, going along connected series of arches within so-called space manifolds. These structures, coming into existence from gravitational effects between the Sun and the planets, stretch from the asteroid belt to past Uranus.
The most pronounced of these structures are linked to Jupiter by its strong gravitational pull, explained UC San Diego's press release. They influence the comets around the gas giant as well as smaller space objects called "centaurs," with are like asteroids in size but exhibit the composition of comets.
This animation shows space manifolds over a hundred years. Each frame of the animation shows how the arches and substructures appear over three-year increments.
Credit: Nataša Todorović, Di Wu and Aaron Rosengren/Science Advances
"Space manifolds act as the boundaries of dynamical channels enabling fast transportation into the inner- and outermost reaches of the Solar System," write the researchers. "Besides being an important element in spacecraft navigation and mission design, these manifolds can also explain the apparent erratic nature of comets and their eventual demise."
A closer image of the manifolds showing colliding and escaping objects.
Credit: Science Advances
The researchers discovered the structures by analyzing collected numerical data on the millions of orbits in the Solar System. The scientists figured out how these orbits were contained within known space manifolds. To detect the presences and structure of the space manifolds, the team employed the fast Lyapunov indicator (FLI), used to detect chaos. The scientists ran simulations to compute how the trajectories of particles approaching different planets like Jupiter, Uranus and Neptune would be affected by possible collisions and the manifolds.
While the results are encouraging, the next step is to figure out how these arches can be used by spacecraft for much speedier travel. It's also not clear how similar manifolds work near Earth. Also unclear is how they impact our planet's run-ins with asteroids and meteorites or any of the man-made objects floating up in space near us.
Check out the new paper "The arches of chaos in the Solar System" in Science Advances.
Tips from neuroscience and psychology can make you an expert thinker.
This article was originally published on Big Think Edge.
Problem-solving skills are in demand. Every job posting lists them under must-have qualifications, and every job candidate claims to possess them, par excellence. Young entrepreneurs make solutions to social and global problems the heart of their mission statements, while parents and teachers push for curricula that encourage critical-thinking methods beyond solving for x.
It's ironic then that we continue to cultivate habits that stunt our ability to solve problems. Take, for example, the modern expectation to be "always on." We push ourselves to always be working, always be producing, always be parenting, always be promoting, always be socializing, always be in the know, always be available, always be doing. It's too much, and when things are always on all the time, we deplete the mental resources we need to truly engage with challenges.
If we're serious about solving problems, at work and in our personal lives, then we need to become more adept at tuning out so we can hone in.
Solve problems with others (occasionally)
A side effect of being always on is that we are rarely alone. We're connected through the ceaseless chirps of friends texting, social media buzzing, and colleagues pinging us for advice everywhere we go. In some ways, this is a boon. Modern technologies mediate near endless opportunities for collective learning and social problem-solving. Yet, such cooperation has its limits according to a 2018 study out of Harvard Business School.
In the study, participants were divided into three group types and asked to solve traveling salesman problems. The first group type had to work on the problems individually. The second group type exchanged notes after every round of problem-solving while the third collaborated after every three rounds.
The researchers found that lone problem-solvers invented a diverse range of potential solutions. However, their solutions varied wildly in quality, with some being true light bulb moments and others burnt-out duds. Conversely, the always-on group took advantage of their collective learning to tackle more complex problems more effectively. But social influence often led these groups to prematurely converge around a single idea and abandon potentially brilliant outliers.
It was the intermittent collaborators who landed on the Goldilocks strategy. By interacting less frequently, individual group members had more time to nurture their ideas so the best could shine. But when they gathered together, the group managed to improve the overall quality of their solutions thanks to collective learning.
In presenting their work, the study's authors question the value of always-on culture—especially our submissiveness to intrusions. "As we replace those sorts of intermittent cycles with always-on technologies, we might be diminishing our capacity to solve problems well," Ethan Bernstein, an associate professor at Harvard Business School and one of the study's authors, said in a press release.
These findings suggest we should schedule time to ruminate with our inner geniuses and consult the wisdom of the crowd. Rather than dividing our day between productivity output and group problem-solving sessions, we must also create space to focus on problems in isolation. This strategy provides the best of both worlds. It allows us to formulate our ideas before social pressure can push us to abandon them. But it doesn't preclude the group knowledge required to refine those ideas.
And the more distractions you can block out or turn off, the more working memory you'll have to direct at the problem.
A problem-solving booster
The next step is to dedicate time to not dealing with problems. Counterintuitive as it may seem, setting a troublesome task aside and letting your subconscious take a crack at it improves your conscious efforts later.
How should we fill these down hours? That's up to you, but research has shown time and again that healthier habits produce hardier minds. This is especially true regarding executive functions—a catchall term that includes a person's ability to self-control, meet goals, think flexibly, and, yes, solve problems.
"Exercisers outperform couch potatoes in tests that measure long-term memory, reasoning, attention, problem-solving, even so-called fluid-intelligence tasks. These tasks test the ability to reason quickly and think abstractly, improvising off previously learned material to solve a new problem. Essentially, exercise improves a whole host of abilities prized in the classroom and at work," writes John Medina, a developmental molecular biologist at the University of Washington.
One such study, published in the Frontiers in Neuroscience, analyzed data collected from more than 4,000 British adults. After controlling for variables, it found a bidirectional relationship between exercise and higher levels of executive function over time. Another study, this one published in the Frontiers in Aging Neuroscience, compared fitness data from 128 adults with brain scans taken as they were dual-tasking. Its findings showed regular exercisers sported more active executive regions.
Research also demonstrates a link between problem-solving, healthy diets, and proper sleep habits. Taken altogether, these lifestyle choices also help people manage their stress—which is known to impair problem-solving and creativity.
Of course, it can be difficult to untangle the complex relationship between cause and effect. Do people with healthy life habits naturally enjoy strong executive functions? Or do those habits bolster their mental fitness throughout their lives?
That's not an easy question to answer, but the Frontiers in Neuroscience study researchers hypothesize that it's a positive feedback loop. They posit that good sleep, nutritious food, and regular exercise fortify our executive functions. In turn, more potent executive decisions invigorate healthier life choices. And those healthy life choices—you see where this is going.
And while life choices are ultimately up to individuals, organizations have a supportive role to play. They can foster cultures that protect off-hours for relaxing, incentivize healthier habits with PTO, and prompt workers to take time for exercise beyond the usual keyboard calisthenics.
Nor would such initiatives be entirely selfless. They come with the added benefit of boosting a workforce's collective problem-solving capabilities.
Live and learn and learn some more
Another advantage of tuning out is the advantage to pursue life-long learning opportunities. People who engage in creative or problem-solving activities in their downtime—think playing music, puzzles, and even board games—show improved executive functions and mental acuity as they age. In other words, by learning to enjoy the act of problem-solving, you may enhance your ability to do so.
Similarly, lifelong learners are often interdisciplinary thinkers. By diving into various subjects, they can come to understand the nuances of different skills and bodies of knowledge to see when ideas from one field may provide a solution to a problem in another. That doesn't mean lifelong learners must become experts in every discipline. On the contrary, they are far more likely to understand where the limits of their knowledge lie. But those self-perceived horizons can also provide insight into where collaboration is necessary and when to follow someone else's lead.
In this way, lifelong learning can be key to problem-solving in both business and our personal lives. It pushes us toward self-improvement, gives us an understanding of how things work, hints at what's possible, and, above all, gives us permission to tune out and focus on what matters.
Cultivate lifelong learning at your organization with lessons 'For Business' from Big Think Edge. At Edge, more than 350 experts, academics, and entrepreneurs come together to teach essential skills in career development and lifelong learning. Heighten your problem-solving aptitude with lessons such as:
- Make Room for Innovation: Key Characteristics of Innovative Companies, with Lisa Bodell, Founder and CEO, FutureThink, and Author, Why Simple Wins
- Use Design Thinking: An Alternative Approach to Tackling the World's Greatest Problems, with Tim Brown, CEO and President, IDEO
- The Power of Onlyness: Give Your People Permission to Co-Create the Future, with Nilofer Merchant, Marketing Expert and Author, The Power of Onlyness
- How to Build a Talent-First Organization: Put People Before Numbers, with Ram Charan, Business Consultant
- The Science of Successful Things: Case Studies in Product Hits and Flops, with Derek Thompson, Senior Editor, The Atlantic, and Author, Hit Makers
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The Rijksmuseum employed an AI to repaint lost parts of Rembrandt's "The Night Watch." Here's how they did it.
- In 1715, Amsterdam's Town Hall sliced off all four outer edges of Rembrandt's priceless masterpiece so that it would fit on a wall.
- Neural networks were used to fill in the missing pieces.
- An unprecedented collaboration between man and machine is now on display at the Rijksmuseum.
Robert Erdmann, a senior scientist working for the Rijksmuseum, cannot help but smile when I ask him to explain — in as much detail as possible — how exactly he used artificial intelligence to recreate long-lost portions of Rembrandt van Rijn's most famous painting, The Night Watch (1642). "Most people just want the elevator pitch," he tells me over Zoom.
The Night Watch is a mammoth of a painting, and it used to be even bigger. In 1715, it came into the possession of the bureaucrats in charge of Amsterdam's Town Hall. In order to fit it on their wall, they sliced off all four outer edges of Rembrandt's priceless masterpiece, inadvertently creating the compromised version we know today.
Rembrandt's "The Night Watch," with the missing edges shown in black.Credit: Courtesy of Robert Erdmann / Rijksmuseum
The missing pieces of "The Night Watch" were never recovered, but we know what they looked like thanks to Gerrit Lundens, a contemporary of Rembrandt who copied the painting when it was complete. These missing sections depict the top of the arch, a balustrade at the bottom, and two soldiers of Frans Banninck Cocq's militia company that stood at the far left.
Though the absence of these elements does not make "The Night Watch" any less impressive, their presence greatly alters the painting's look and feel. The balustrade emphasizes the company's movement forward. Together, the four missing pieces shift the principal figures — Cocq and Willem van Ruytenburch — to the right, creating a more compelling composition.
Copy of "The Night Watch" by Gerrit Lundens.Credit: Courtesy of Robert Erdmann / Rijksmuseum
As part of Operation Night Watch, a multimillion-dollar restoration mission, the Rijksmuseum set out to recreate these missing pieces of the painting to show visitors The Night Watch as Rembrandt had originally constructed it. One easy way to do this would be to upload the smaller Lundens copy into Photoshop, blow it up by a factor of five, print it out, and call it a day.
Easy, but far from adequate. As Erdmann puts it: "There's nothing wrong with using an artist like that. However, the final product would still contain traces of that artist's own style." For Erdmann, the only viable solution was to create a series of neural networks — software that mimics the human brain through the use of artificial neurons — to transform the Lundens copy into an "original" Rembrandt.
Humans, unlike computers, aren't able to make perfect copies. Faithful though Lundens' painting is — especially in its visual detail, for example, the number of buttons on a coat, plumes on a feather, or engravings on a halberd — it still contains a myriad of miniscule differences that prevented Erdmann from simply copy-pasting it onto the original.
Perspective was the first and arguably most important item on Erdmann's list. "The geometric correspondence is pretty good at the bottom of the copy," he says. "At the top, that correspondence starts to fall apart; the composition looks stretched out, supposedly because Lundens was unable to reach the top of the painting to get its precise measurements."
Lundens' copy, adjusted for perspective by the AI.Credit: Courtesy of Robert Erdmann / Rijksmuseum
After creating a neural network that could identify corresponding elements in both versions of The Night Watch — from faces and hands to clothing and weapons — Erdmann made a second neural network that could stretch, rotate, foreshorten, compress, and decompress the Lundens copy so that its measurements matched the Rembrandt original as closely as possible.
According to Erdman, this step was "a guide to where we should place the figures on the left, because they need to be consistent with the extrapolation from the original Night Watch." Aside from aligning the two paintings, Erdmann's adjustments also transformed the facial structure of figures like Cocq, bringing them closer to Rembrandt's expert rendering.
Detail of the Lundens copy before perspectival adjustments.Credit: Courtesy of Robert Erdmann / Rijksmuseum
Detail of the Lundens copy after perspectival adjustments.Credit: Courtesy of Robert Erdmann / Rijksmuseum
Just as a painter must tone their canvas before they can work on composition and color, so too did Erdmann have to get the dimensions right before he could move on to the third and final stage of his coding process. Erdmann's next part of the neural network involved — to paraphrase his elevator pitch — sending the artificial intelligence algorithm to art school.
"Not unlike how you might translate a text from Dutch to English, we wanted to see if we could transform Lundens' painterly style and palette into Rembrandt's," he explains, comparing the learning curve to a quiz. To educate it, the AI was given random tiles from the Lundens copy and asked to render the tiles in the style of Rembrandt.
As with any pedagogical situation, Erdmann evaluated the AI's efforts with a corresponding grade. The closer its output matched the contents of the original Night Watch, the higher the grade it received. When grading, Erdmann considered things like color, texture, and representation (i.e., how well does this frowning face resemble a frowning face, or this sword an actual sword?).
"Once you've defined what makes a good copy, you can train the network on thousands and thousands of these tiles," Erdmann goes on. There are 265 gigabytes of memory of thousands of attempts stored, which demonstrates improvement in quality over a very short time. Within less than a day, the error margin between the AI and the real Rembrandt grew so small it became insignificant; the training was complete.
Lundens copy when adjusted for perspective and Rembrandt's style by AI.Credit: Courtesy of Robert Erdmann / Rijksmuseum
Along the way, the AI had developed a thorough understanding of what made Rembrandt Rembrandt. When translating Lundens' copy, it used a less saturated color palette and thicker, sketchier brushstrokes. It even adopted the painter's signature use of chiaroscuro — a technique involving sharp contrasts between light and shadow.
Then it was time for the final exam. Using the knowledge gained from copying Rembrandt, Erdmann ordered the AI to transform the four outer edges of the Lundens copy — removed from the original Night Watch — into Rembrandt's signature style. The result, an unprecedented collaboration between man and machine, is now on display in the Eregalerij of the Rijksmuseum.
Detail of the completed "Night Watch." The two figures on the left were added from the adjusted Lundens copy.Credit: Courtesy of Robert Erdmann / Rijksmuseum
The missing pieces, resuscitated by AI, were printed onto canvas and varnished so that they had a similar gloss to the rest of the painting. The pieces were then attached to metal plates, which were placed in front of the original Night Watch at a distance of less than one centimeter, thus creating an optical illusion for visitors without actually touching Rembrandt's work.
While conservation science is evolving rapidly, the achievements of people like Erdmann are still eclipsed by the artistic genius of the painters whose work they try to preserve, which is a shame because Erdmann's software can be just as inventive as Rembrandt's brushwork. At the very least, Erdmann's problem-solving skills would have made the master proud.