When I’m writing this note, India is facing an unprecedented crisis - struggling to cope up with the 2nd wave of Covid-19 pandemic. The number of new cases peaked to a little more than 400,000 per day, putting the healthcare infrastructure in many cities and towns under tremendous stress, as they scour for beds, oxygen cylinders, medicines and other critical supplies. Most states in the country have imposed lockdowns to contain the viral spread and the country is collectively doing their best to come out of this stronger.
We all remember the “flatten the curve” graph that got really popular worldwide during the first wave of Covid-19, that explains succinctly why it’s important to adopt measures like lockdown during a pandemic. It explains how they help us contain the spread and thereby equip us to deal with the pandemic better - it’s about preventing emergency cases that might go unattended because of the limited healthcare system capacity in every city, state or country.
Last few weeks, naturally so, it has become a habit for most people who have access to internet or television to keep a track of number of new cases of coronavirus on a daily basis. And it’s common to hear people around us say, “Why are the numbers not going down, despite having the lockdown?” And that’s where I feel a quick refresher on feedback loop helps.
What is a feedback loop?
The term feedback loop is thrown around a lot but the first time I heard about it as a concept was during my undergraduate studies, in a course called “Control Systems”, that’s mandatory for engineering students to enrol into, but something that’s more contextual for Chemical Engineering and other disciplines that delve into more depth on how engineering processes operate. As Wikimedia puts it:
“A feedback loop is a common and powerful tool when designing a control system. Feedback loops take the system output into consideration, which enables the system to adjust its performance to meet a desired output response.”
It means that the outcome of a reaction or a process acts as a feeder to the input stage of the reaction so as to regulate the quality of process and produce more of the output that’s quantitatively or qualitatively desirable.
Let’s take an example to understand this better. Imagine a chemical engineering process that converts a few reactants or input into a desired output under certain conditions and it takes 30 mins to do so. At 9 AM, a batch of input is put together and at 9:30 AM, we get the resulting output. Now the system deduces the quality of the output is at 95%, above the permissible 94% but that raising the temperature of the boiler by 2 degrees would produce output of 98% quality without compromising on anything. This data or the feedback signal is sent back to the input and automatically increases the temperature of the boiler with the new batch of input. I hope this explains how feedback loops help in building systems that can self-correct and maintain quality.
Feedback loops everywhere
Feedback loops come into play in any system or game where the outcome can be used to improve the future outcome by changing the input parameters for the process. Let’s look at a few examples in real life:
Food habits: You are having a stressful time at work and end up eating a lot of fast food of late. The output being a state where you’ve gained a bit of extra weight a few weeks later. This information can be a feedback signal for you to cut down on fast food and follow a healthier diet with the desired outcome of losing some weight.
Driving: You are speeding at 100 miles / hour in your car and you see the brake lights of the car in front of you lit up. You take that as a feedback signal and apply your brakes immediately to avoid a collision and continue having a safe car journey without any accidents.
They are everywhere around us and influence how we act in most of the circumstances.
Feedback loops and Time
As we start looking at feedback loops in a more nuanced manner, it’s helpful to understand how it has a temporal element to it. Different process take different amounts of time to give you an idea of the output so that you can act on that information (feedback loop). The two real life examples discussed above are good examples to explain this point. The food habits example clearly takes a longer period of time for the person to understand what’s happening to him / her as a result of a continued action. On the other hand, the driving one is an example for how the signal is transmitted and processed almost instantly leading to a life-saving action.
If you were to straighten out the time dimension, the same diagram can be interpreted as a linear workflow where the feedback at the end of each output acts as the feedback element for the next input as shown in the diagram below.
In many cases, we struggle to understand the function of time in the feedback loops we deal with, in our life. In many dopamine motivated urges that we succumb to, we do things that give us the reward instantly, like eating an ice cream, checking social media for updates etc. They are processes with instant gratification - the outcome (release of dopamine in the brain) almost immediately follows the cue and the routine (act of checking social media for what’s happening with people around you), with the feedback loop acting immediately. On the other hand, we are poor at evaluating efforts that have delayed gratification, where the output takes a lot of time for us to be able to appreciate the input and the process. Examples are saving money or investing in a pension scheme - they are all likely to help you on a rainy day later and don’t reward you immediately.
Back to the Covid-19 Lockdown
Why do we feel that lockdowns are not working? It’s because we struggle to have a sense of the process’s temporal aspect. The Covid-19 cases that are reported on a given day were mostly a cumulative result of the community’s actions 4 to 7 days back, when they actually contracted the virus. What does that imply? If you start following lockdown or other measures to reduce the spread of the virus today, it’s not going to change the numbers you see tomorrow. It will however impact the number of cases that are reported a week later. That’s when the administrators will evaluate the outcome and decide what to do with the result (feedback loop) - imposing further restrictions or continuing with the same measures or easing them up based on what they learn.
The 2nd wave of Covid-19 took all of us by brutal shock and this time, it really hit home with many of us, our close family and friends being impacted by the crisis. It’s a sense of helplessness that most of us have not felt ever before in our lives. During these difficult times, it’s also natural for many of us to be anxious about the number of cases not going down despite the measures we take. I hope this read would’ve given you a perspective to clear your thoughts and help your close ones be at ease by conveying the importance of waiting - for the process to take effect and the output to show, which can then act as a feedback for further improvements. Take care and stay safe. We are in this together.
Feedback Loops
Thanks for the clear perspective. Well explained.
Very well explained