“Stop being a perfectionist. Embrace the fear that you'll make a mistake. Be vulnerable.”— Charles Plant
“He (the shaman) was telling me that his culture's belief is like a river; when a pathway opens up, that's a pathway for you to flow into - and it should be easy to go in that direction. And if there's a deep struggle in the direction, then that's not the path for you. You just have to move on a different way. When I heard him say I thought 'Geez, there are so many things we struggle with on daily basis. And maybe it's not the thing we should struggling for; maybe it's a lot simpler, you know? That's the way my decision-making goes. When I am exploring my intuition, it's like a river. If it feels right I move easily in that direction. There is no "Should I, shouldn't I?" or a pros-and-cons list-no debate. This is the way to make sense to what to do. And that's the way I pretty much lead my life.”—Stana Katic
Bad decisions arise from faulty information, not faulty brain circuits
Making decisions involves a gradual accumulation of facts that support one choice or another. A person choosing a college might weigh factors such as course selection, institutional reputation and the quality of future job prospects.
But if the wrong choice is made, Princeton University researchers have found that it might be the information rather than the brain’s decision-making process that is to blame. The researchers report in the journal Science that erroneous decisions tend to arise from errors, or “noise,” in the information coming into the brain rather than errors in how the brain accumulates information.
These findings address a fundamental question among neuroscientists about whether bad decisions result from noise in the external information — or sensory input — or because the brain made mistakes when tallying that information. In the example of choosing a college, the question might be whether a person made a poor choice because of misleading or confusing course descriptions, or because the brain failed to remember which college had the best ratings.
Previous measurements of brain neurons have indicated that brain functions are inherently noisy. The Princeton research, however, separated sensory inputs from the internal mental process to show that the former can be noisy while the latter is remarkably reliable, said senior investigator Carlos Brody, a Princeton associate professor of molecular biology and the Princeton Neuroscience Institute (PNI), and a Howard Hughes Medical Institute Investigator.
“To our great surprise, the internal mental process was perfectly noiseless. All of the imperfections came from noise in the sensory processes,” Brody said. Brody worked with first author Bingni Brunton, now a postdoctoral research associate in the departments of biology and applied mathematics at the University of Washington; and Matthew Botvinick, a Princeton associate professor of psychology and PNI.
The research subjects — four college-age volunteers and 19 laboratory rats — listened to streams of randomly timed clicks coming into both the left ear and the right ear. After listening to a stream, the subjects had to choose the side from which more clicks originated. The rats had been trained to turn their noses in the direction from which more clicks originated.
The test subjects mostly chose the correct side but occasionally made errors. By comparing various patterns of clicks with the volunteers’ responses, researchers found that all of the errors arose when two clicks overlapped, and not from any observable noise in the brain system that tallied the clicks. This was true in experiment after experiment utilizing different click patterns, in humans and rats.
The researchers used the timing of the clicks and the decision-making behavior of the test subjects to create computer models that can be used to indicate what happens in the brain during decision-making. The models provide a clear window into the brain during the “mulling over” period of decision-making, the time when a person is accumulating information but has yet to choose, Brody said.
“Before we conducted this study, we did not have a way of looking at this process without inserting electrodes into the brain,” Brody said. “Now thanks to our model, we have an estimation of what is going on at each moment in time during the formation of the decision.”
The study suggests that information represented and processed in the brain’s neurons must be robust to noise, Brody said. “In other words, the ‘neural code’ may have a mechanism for inherent error correction,” he said.
“The new work from the Brody lab is important for a few reasons,” said Anne Churchland, an assistant professor of biological sciences at Cold Spring Harbor Laboratory who studies decision-making and was not involved in the study. “First, the work was very innovative because the researchers were able to study carefully controlled decision-making behavior in rodents. This is surprising in that one might have guessed rodents were incapable of producing stable, reliable decisions that are based on complex sensory stimuli.
“This work exposed some unexpected features of why animals, including humans, sometimes make incorrect decisions,” Churchland said. “Specifically, the researchers found that errors are mostly driven by the inability to accurately encode sensory information. Alternative possibilities, which the authors ruled out, included noise associated with holding the stimulus in mind, or memory noise, and noise associated with a bias toward one alternative or the other.”
or “paralysis of analysis“ refers to over-analyzing (or over-thinking) a situation, so that a decision or action is never taken, in effect paralyzing the outcome.
- A decision can be treated as over-complicated, with too many detailed options, so that a choice is never made, rather than try something and change if a major problem arises.
- A person might be seeking the optimal or “perfect” solution upfront, and fear making any decision which could lead to erroneous results, when on the way to a better solution.
The sheer quantity of analysis overwhelms the decision-making process itself, thus preventing a decision.
“I found myself spending literally a half an hour, 30 minutes, in the cereal aisle of the supermarket, trying to choose between boxes of Cheerios. That's when I realized I had a problem.”—One year ago this week: Jonah Lehrer, on the pathologies of decision making.
Kapag gagawa ka ng desisyon palaging may PROS and CONS.
Simplehan natin ang pagpapaliwanag para maintindihan ng karamihan.
Sa lahat ng desisyon na gagawin mo sa buhay, hindi maaring pros lagi yan, Automatic yan kapag may PROS may CONS yan. Kung hindi mo alam ang PROS at CONS at nahihiya kang itanong eh sasagutin ko na rin para maintindihan mo. Para itong BIDA at KONTRABIDA, ADVANTAGE at DISADVANTAGE. Ganun ka simple.
Kunwari sa nag desisyon ka na magmamahal ka at pipili ka ng taong mamahalin mo. Ano nga ba ang mga PROS at CONS nito?
- May mag-aalaga na lagi sayo.
- May maglalambing na lagi sayo.
- May magmamahal na palagi sayo.
- May mag tetext na lagi sayo.
- Mawawalan ka na ng oras sa ibang tao, dahil sa isang tao na lang ang atensyon mo.
- Lahat ng galaw mo dapat ipagpaalam mo na bilang respeto sa taong ka relasyon mo.
- Titigilan mo na ang hobby mong panlalandi sa karamihan dahil bawal na at meron ka ng iba.
- Required kang mag load lagi, magastos, madalas may proproblemahin ka pag nag away kayong dalawa.
Sa ibang dako naman tayo, lumayo tayo sa topic sa pag-ibig. Sa pagpapalit ng kurso.
Isang magandang Example dito eh kapag naisipan mong mag DOCTOR. Ano nga ba ang PROS and CONS kapag nag desisyon kang maging DOCTOR?
- Prestige ( Doktor ka eh, mataas ang tingin sayo ng tao )
- Maraming sisipsip sayo dahil nga sa ikaw ay isang Doktor.
- Ginagalang ka ng maraming tao.
- Pasasalamatan ka ng marami dahil sila ay napagaling mo.
- Nakakatulong ka sa kapwa mo mayaman man o mahirap.
- Malaki ang chance na sobrang professional din ang makaka partner mo sa buhay dahil sa pride ng mga ito.
- Lahat ng kumpanya/profession eh maaring bumagsak sa huli. Pero ang medicine course eh malabo, dahil lahat ng tao ay magkakasakit din.
- Kailangan mong isakripisyo ang oras, kailangan mong i give up ang mga hilig mo. Aral aral aral. Ganyan ang medicine course.
- Kung iisipin mo, sa tagal ng pag-aaral sa mga kursong ito, maiisip mo na mag shift pa ba ako? Parang mahirap ng lumipat dahil huli na ang lahat.
- Mga ka kompetensya.
- Almost 15 years of your life kang mag-aaral. Dahil 4 years sa College, 4 Years sa Med Course, den Intern, den ibat-ibang mga Profession pa.
- Isipin mo sa 15 years na yun, kung kumuha ka ng ibang kurso na 4 years at nakapagtrabaho sa loob ng 11 taon. Sa tingin mo ano ang buhay mo ngayon?
Sabi ko nga kanina eh gawin mong passion ang profession na gusto mo. If you work hard, the rest is easy. Sa lahat ng pag dedesisyon eh palagi mong iisipin ito. Walang swerteng tao na nag desisyon na walang kahalong CONS. Partner lagi yan. Hindi mawawala sa sirkulasyon sa buhay ng tao yan. Kaya dapat lahat ng decision mo sigurado ka. Para madali ka man sa huli ng mga CONS na yan, Ok lang. Kasi ginusto mo naman eh.
The Evaluability Hypothesis
Is it a good idea to ask people to rate products all at once?
I’ve just finished working on a project where we asked people how likely they would be to purchase a number of different products - a pretty standard market research thing to do. However I was worried - not staying up at night worried, just worried enough to do a bit of thinking worried - about how rating all the products together, rather than separately, would affect the results of my purchase question. I’ve done a bit of personal research and haven’t developed any concrete answers, but came across an interesting concept…
The evaluability hypothesis
The evaluability hypothesis was introduced by psychologist Christopher Hsee (1996) and is stated as follows:
“When two stimulus options involve a trade-off between a hard-to-evaluate attribute and a easy-to-evaluate attribute, the hard-to-evaluate attribute has a lesser impact in a separate evaluation than in a joint evaluation, and the easy-to-evaluate-attribute has a greater impact.”
What on earth does that mean?
The evaluability hypothesis breaks (product) attributes down into two types - easy-to-evaluate independently, and hard-to-evaluate-independently. Easy-to-evaluate attributes can be assessed by a person without needing to compare it to something else. Hard-to-evaluate attributes are difficult to assess without comparing themto something else.
If you have products which have a easy-to-evaluate attribute and a hard-to-evaluate attribute, when the products are evaluated independently people will place more emphasis on the easy-to-evaluate attribute. If the products are evaluated together then people will place more emphasis on the hard-to-evaluate attribute.
Seriously, what are you going on about?
An example might help explain where this is leading! Imagine we’re doing some research which involves looking at how much people are willing to pay for two cameras. We ask people how much they would be willing to pay for each of the camera’s assuming they had a budget of £10 - £150 to spend on a camera.
Mega-pixels Defects Camera 1 5 None Camera 2 10.2 Scuff on the case otherwise as new
If the cameras were rated separately in two conditions you would expect that Camera 1 would get the highest mean value (in terms of how much people would be willing to pay) because people may not be sure how good 5 mega-pixels is (hard-to-evaluate attribute). But they know no defects is good (easy-to-evaluate attribute). If the cameras where rated together you would expect Camera 2 to get the higher rating because people know no defects is good (easy-to-evaluate attribute) and that in comparison 10.2 mega-pixels is better than 5 mega-pixels (hard-to-evaluate attribute).
So, what does it all mean?
We can take out a couple of things out of the work of Hsee. When asking people to rate products or concepts think carefully about what attributes people are rating them on. Are the attributes easy-to-evaluate or hard-to-evaluate and how could this affect the data you collect? This work could also have a bearing on the recommendations we give to clients. For example should a product be advertised alone or in comparison with other products?
Christopher K. Hsee, The Evaluability Hypothesis: An Explanation for Preference Reversals between Joint and Separate Evaluations of Alternatives, Organizational Behavior and Human Decision Processes, Volume 67, Issue 3, September 1996, Pages 247-257, ISSN 0749-5978, DOI: 10.1006/obhd.1996.0077.