Week 2
Choice overload, the human nature of the design process, thinking like a child and how to optimally stop searching for something.
Whew. Quite a hectic week.
Studied human behavior, worked on finishing my onboarding project at TinkerLabs, played a LOT of badminton, and did a bunch of reading. Feels like I’m finally settling in, getting to terms with my adult life, and shaping how I want it to be.
Sometimes I wonder about the time when people stand at a crossroads, having to choose between their teenage life and getting sucked into adulthood. So many individuals, bursting with creativity and passion once upon a time, now trapped in adulthood.
People who once made innovative projects, now struggling to check off their daily task lists. Radical thinkers, now politely nodding along. Loud voices, now silenced. Thinkers, now doers. Writers, now readers. Energetic, now obese. Alive, now barely.
I wonder when that time comes and whether you make a conscious decision; or does it seep into your life slowly, like a vile poison. People around me often dismiss energy and passion as a product of my youth. It is agitating. Saddening, even, to think about the fact that they were once just like this but something went wrong somewhere, something horrible.
I wish that never happens to me and I guess efforts such as this blog, to remain a lifelong student, will aid in my resilience against the mundanity of adulthood.
[Study] Avoiding Choice Overload
One of my coworkers has a rather peculiar choosing problem: she can’t decide what to eat for lunch.
Choice overload is not new in modern-day society. With the number of options for any given thing at a steady rise, the task of choosing something over the other is almost paralyzing. A study by Caltech experimented with this phenomenon and analyzed fMRI (functional magnetic resonance imaging) scans of people choosing from a set of choices (varied with the number of choices available).
The study revealed that as the number of options increased, the potential reward also increases, but then begins to level off due to the law of diminishing returns (in case you’re not familiar with the economics term, you can read up here).
The conclusion of the study is that the ideal number of options for a person to choose is estimated to be somewhere around 8-15, but this varies due to factors such as the perceived reward, difficulty of evaluating options, and others.
[Thoughts] Biases In The Design Process
This week, I also geeked out on cognitive biases in order to familiarise myself with the TinkerLabs approach.
As I looked at some of these biases, I drew a connection between how the creative process is heavily biased and error-prone due to human frailties. For example:
Frequency Illusion (also referred to as the Baader-Meinhof Phenomenon) says that once something is noticed, then every instance of that thing is noticed. This leads to the belief that it has a high frequency of occurrence. This is something we do in design all the time and anchor ourselves to a piece of information that might not have been important.
Anchoring bias refers to anchoring on one train or piece of information when making decisions, usually the first one. Although anchoring bias is needed to progress in the creative process, as well as anything for that matter, it might still have been affected by the frequency illusion; rendering the basis of your anchor weak.
Apophenia refers to the act of making meaningful connections between unrelated things (which, honestly, is the entirety of design).
Others such as the salience bias (ignoring objects that are not prominent), effort justification (attaching greater value to something that they put effort into achieving), confirmation bias (interpreting information in a way that confirms one’s preconceptions), and many more affect the extremely humane process of design.
An interesting thought to develop upon.
[Projects] Dollar Street
Dollar Street by Gapminder is a very cool project to visualize the world as a street ordered by income. The poorest people from different countries are shown on the left and the richest ones on the right.
There are different filters that one can use to sort the list. One can even sort it according to objects such as beds, stoves, and, my favorite, toothbrushes.
[Article] Why Do People Forget?
Over the past week, I was also studying why people forget. This medically reviewed article by Kendra Cherry on Verywell Mind summarises it beautifully.
Decay: Unused memories often decay away and those that aren’t retrieved over time are eventually lost.
Interference: Old or new information such as old memories or distractions in your environment can often interfere with what you were originally thinking about; leading you to forget. Even the act of trying to remember something can act as interference.
Failure to store: Memory tends to oversimplify things and, therefore, you begin to forget the details. Or a memory never made it to your long-term memory.
Other factors such as alcohol, stress, depression, medication, forcefully forgetting trauma, lack of sleep, and more can also play a part in the forgetting of memories or information.
[People] Rauno Freiberg
Rauno Freiberg is a design engineer, introduced to me by Navya (a college junior of mine).
Rauno is passionate about interfaces and interaction. I highly recommend his UI Playbook, User Interface Gallery, and Flow project.
[Self-Realisations] I Naturally Think Like A Child
This past week as I was onboarding at TinkerLabs, I was introduced to the concept of Ideation Prompts. Before this, I’d always considered them as gimmicks and was pleasantly surprised to see that these were being used in the real world; to facilitate projects and workshops.
Although they have merit as parts of a larger concept to facilitate creative thinking (recommended by the Board Of Innovation), some of these stood out. For example, one prompt read what if you were a superhero?
I have never used ideation prompts in my life and resorted to my own process of zoning out and brainstorming. When I reached a saturation point and sat down to examine my ideas, I realized that I never have to use the prompts because I naturally think that way. My ideas are often free from any sort of real-world factors that bog down creativity, such as the ones that deal with viability and feasibility.
I naturally included superhero abilities and later realized that the idea wasn’t feasible. Now, I’ve realized how important it is to be able to think like a child; to temporarily tune out your adult voice dampening your creativity with reality.
[Resource] Dimensions.com
Dimensions.com is an extremely cool open-access reference database of dimensioned drawings and models that document measurements & sizes of everyday objects and spaces.
[Learnings] Optimal Stopping, 37%, and The Power of 3.
When do you stop looking for something?
This question came to be of interest to mathematicians around the world in the 1940s and became a separate class of mathematical puzzles. These are called Optimal Stopping problems and spread like wildfire through the mathematical circles of the 1950s and 60s.
The secretary problem is the most popular version of the optimal stopping problem which Brian Christian explains rather succinctly in his book, Algorithms to Live By.
Imagine that you’re interviewing a set of people to hire a new secretary. Now, in your search for a secretary, there are two ways you can fail: stopping early and stopping late. When you stop too early, you leave the best applicant undiscovered. When you stop too late, you hold out for a better applicant who doesn’t exist. The optimal strategy will clearly require finding the right balance between the two, walking the tightrope between looking too much and not enough.
Brian goes on to explain how probability favors 37% as the ideal number of candidates to screen before choosing one, in order to have the highest chance of getting the best secretary, while still picking from a large enough sample size.
An even greater learning was the power of 3. Brian explains how 3 choices can be the most optimal. He says, "When we see the first applicant, we have no information—she’ll always appear to be the best yet. When we see the third applicant, we have no agency—we have to make an offer to the final applicant, since we’ve dismissed the others. But when we see the second applicant, we have a little bit of both: we know whether she’s better or worse than the first, and we have the freedom to either hire or dismiss her. What happens when we just hire her if she’s better than the first applicant, and dismiss her if she’s not? This turns out to be the best possible strategy when facing three applicants; using this approach it’s possible, surprisingly, to do just as well in the three-applicant problem as with two, choosing the best applicant exactly half the time."
This kind of knowledge could tie in really well with my earlier study on choice overload.