Human development has been described by Selim Jahan (head of the UNDP program) as “development of the people (capital), for the people (translated to the lives of people) and by the people (people are not only receiving but active participants in the process).” How have we done as a humanity to fulfill this hope originally manifested through the Gettysburg address? Does data science have a role to play in advancing the human condition? What role does complexity play in advancing our understanding of global human development processes and their multitude of dimensions? In order to predict valuable solutions to some of the world’s most intractable problems, will combined domain expertise from the perspective of computer science & statistics with global human development be sufficient, or is a new integrated paradigm needed? What hope do we have in selecting the best future path for humanity?

As Selim Jahan states, “Development of the people, for the people and by the people” is the enhancement of an organization’s capabilities and performance, which is necessary for the growth and development of a company. Following the Gettysburg address, we have done relatively well in fulfilling this hope; however, we don’t live in a perfect world and we still have a lot to improve on in today’s society. There are two main dimensions of human development: the first focuses on directly enhancing human abilities, which consists of long and healthy lives, knowledge, and a decent standard of living. In this respect, we have seen poverty and famine diminish and higher access to healthcare in the last couple of centuries. The second dimension focuses on creating conditions for human development, which incorporates participation in political and community life, environmental sustainability, human security and rights, and gender equality. Human development has also allowed access to education, which can alleviate poverty and improve economic success.

Ultimately, human development allows people to make decisions and provides them with opportunities. As Amartya Sen states, “Development can be seen as a process of expanding the real freedoms that people enjoy”, which we have successfully done as we’ve expanded our social and political freedoms, giving people access to basic resources and meeting basic needs. According to Harvard psychologist Steven Pinker, “We have seen substantial improvements in life expectancy, access to livelihood and enhanced well-being across the world coexist with pervasive poverty, disempowerment, unconscionable inequalities, major environmental degradation and democracy, and governance crisis.” In other words, although we have made tremendous progress since the Gettysburg address “of the people, for the people and by the people,” we still have a long way to go both in the United States and as a global society.

To build on our progress so far, data science plays an important role in our everyday lives to advance the human condition. One of the most important advancements in which data science has globally impacted society is healthcare. In many aspects, data science has advanced our knowledge of human health and has helped our medical community, health care professionals and, in keeping with Jahan’s interpretation, it has helped people themselves make more insightful decisions about their health and treatment options. With the help of scientific methods, algorithms, structured and unstructured data, as well as technological advancements, we now have access to virtual assistance, medical imaging, and predictive analytics. In some instances, thanks to data science, patients can even administer self-tests at home (e.g. through a blood pressure monitor patients can track and plot their blood pressure), unleashing the power of predictive analytics to know if they need to seek professional medical help for additional analysis. Data science also provides us with more insight on genomics, drug discovery, and disease prevention and tracking, which allow us to keep our society healthy.

Because of the complexity of certain systems (for example the human body or the environment), data science has a very big role to play in helping scientists understand how different factors within a system may or may not be connected. In traditional science, the scientific method tests one variable while holding everything else constant (the control). We know this method of scientific inquiry—the one we have been using for centuries—does not take into account the complexity of a system because only one variable can be tested at a time. Now, using data science, we can quickly explore many factors at the same time using algorithms and artificial intelligence. What would have taken us decades to learn through trial and error using the traditional scientific method will hopefully take only months or weeks using data science. If this proves to be true, we will be able to predict valuable solutions to some of the world’s most intractable problems. But in my opinion, combined domain expertise from the perspective of computer science and statistics with global human development will not be sufficient to solve all our problems, especially those multi-factor problems that cross over many disciplines. To solve those, we will need a new paradigm.

A new paradigm to solve the most complicated multi factor problems, such as climate change, will need to be multidisciplinary, flexible, and have a very long-term international focus. It will need to be multi-disciplinary since tackling climate change from one discipline, for example from a scientific perspective, will not be enough to solve the problem since climate change is also an economic problem, a social problem and a political problem. So only a multi-disciplinary approach will work. The new paradigm needs to be flexible enough to adapt to how the problem may change as it is being solved; otherwise, we may be solving a problem that no longer exists in many years’ time. Finally, the paradigm will have to be international since no one nation can solve it on its own, and the paradigm will need to have a very long-term focus (decades not years) since complex problems such as climate change do not come to be in a few years and they probably will not be solved in a shorter time than that. If we can use data science with this new paradigm then we may be able to choose the best future path for humanity.