In his podcast, “What is human development?”, Selim Jahan goes to great lengths to emphasize the idea that human development goes beyond measuring the economy, and is instead, “the process of enlarging human choices.” He states that human development is much more holistic, and it encompasses aspects like a long and healthy life, knowledge, and decent standard of living - these are all referred to as “focus measures”. These three measures help to make up the Human development index (HDI), along with the brit measures that he touches on, such as unemployment rate and infant mortality rate, etc. Jahan compares the breadth measure to house, and the focus measures to a door of the house. He says that you should not just stop at the door of the house, and instead consider the entire house. I think this is a crucial point, as it captures the idea that even the HDI cannot capture the totality of human development.
One interesting issue that Jahan touches on is that we as a society need to rethink how we view work. Work goes beyond jobs and unemployment, when it comes to human development. It encompasses creative and artistic work, care work within families and communities, and volunteer work. These other types of work contribute to social cohesion, and play a big role in increasing general welfare. Some other issues that require work also include youth employment, gender-roles work, work associated in the agricultural and informal sector, and post-crisis work.
Han’s Rosling’s talk,” The best stats you’ve never seen”, was very fascinating, and he explained how health is the precursor to wealth. This idea is definitly one that is overlooked and should be given more attention. A healthy society is able to implement human development changes that are necessary for wealth. Rosling proves this by showing that the speed of development is very different for countries, and there is a faster speed of development if the country is healthy first rather than wealthy first. On example fo this is how Rosling displayed the rate of development for South Korea, Uganda, and Brazil. Brazil had the highest GDP per capita starting point, and yet, South Korea has a much faster rate of development rate. Rosling indicated that this was because South Korea had a healthier society. Another interesting example was the United Arab Emirates. Their development trend went in the opposite direction - they had very slow development, and even had their GDP per capita decrease as they approached a higher child survival rate. This is because, as Rosling put it, “health cannot be bought at the supermarket.” Countries must invest in health, and educate staff personel, etc.
Another interesting point from Rosling’s talk is that he warned against just looking at countries’ averages to determine the development of the country. This is because there is tremendous variation within these regions. For example, if comparing GDP per capita and child survival rate, Africa may seem low on the graph. However, when Africa is split apart into different countries, Mauritus takes a very high place on the graph - even higher than some European countries. On the other hand, Sierra Leone is placed very low on the graph. This is the issue with looking at averages - it may misrepresent individual, smaller countries or regions. Human development needs to be looked at very contextualized. Even a regional level is too large to look at.
In their podcasts, Jahan and Rosling are both trying to prove the same idea: Human development needs to be thought of much more holistically. It’s interesting because Jahan and Rosling both show that the measures they are talking about can’t entirely encapsulate the extent of human development. Jahan even mentions this when he says, “Even the HDI cannot capture the totality of human development.” This realization is important because it’s something data scientists need to be aware of, so that they don’t make incorrect assumptions about a region. These podcasts tell us that data scientists need to look at development at a localized area, otherwise there is too much variation, and not just analyze the economy, but understand the welfare of the people.
In brief, both podcasts were very fascinating. Jahan and Rosling cause us to rethink the way we view data science. Instead of just numbers and averages, we are reminded that there are real life people being represented by these numbers.