There is a greater emphasis on math, statistics, and computing in these programs.

What’s at stake:

A study has found that data scientists’ undergraduate training is described as the most beautiful career in this century by Harvard Business Review – falls short in the ability to prepare students for the ethical use that data science can provide.

Data science is situated at the intersection of computer science and statistics applied to specific fields such as astronomy or the psychology of linguistics, medicine, or sociology. The concept behind data crunching is to use large amounts of data to solve complex problems, such as how healthcare professionals can develop customized medicine based on the patient’s genetics and how companies can create purchases based on customer behavior.

The U.S. Bureau of Labor Statistics predicts an increase of 15% in careers in data science between 2019 and 2029 that is in line with the increasing demand for education in data science. Colleges and universities have responded to this demand with new programs or revising existing ones. The number of undergraduate data science courses within the U.S. jumped from 13 in 2014 to a minimum of 50 by September 2020.

As teachers and researchers working in data science, we were intrigued by the growing number of education programs to look into what is included and not in undergraduate data science training.

In our research, we examined the curriculum for data science at the undergraduate level with expectations for the training of data science students at an undergraduate level set in the National Academies of Sciences, Engineering, and Medicine. These expectations include instruction in ethics. 

We found that most programs devote substantial time to math, statistics, and computer science; however, they did not provide any training in ethical concerns like privacy and bias in systems. Only a 50percent of the degree programs we studied included any course in ethics.

Here’s why it matters:

Like any other powerful tool using data science, the ethical use of data science needs training in the application of data science and understanding its effects. Our findings align with earlier research which found that little consideration is given to ethics in degrees in data science. This suggests that undergrad studies in data science may result in a workforce lacking the education and experience required to apply data science methods ethically.

It’s not difficult to find instances of reckless usage in data science. 

For example, policing models with a built-in bias to data could result in more police officers in historically over-policed areas. Another example is that algorithms employed to manage healthcare providers within the U.S. healthcare system are biased in a manner that causes Black people to be denied treatment as white patients with similar demands.

We believe that explicit training on ethical behavior will better prepare a Data science workforce that is socially responsible.

There is still much to learn:

Although data science is still a relatively new field, it is still being defined as a discipline guidelines exist for educating students at the undergraduate level in the field data science. These guidelines raise the question: What training should we expect from the first year of a bachelor’s degree?

The National Academies recommend training in 10 areas, including ethical problem-solving and communication, and data management. Our research focused on the degree of data science for undergraduates at institutions classified as R1; that is, they participate in significant research activities. 

Future research should investigate the extent of training and preparation for different aspects of data science, particularly at Masters or Ph.D. levels, as well as the type of instruction in data science at universities with different research levels.

Because most data science programs are brand new, there’s an opportunity to evaluate the instruction students receive with employers’ expectations.

In a Nutshell:

Our study will be expanded upon by investigating the pressures driving curriculum development in other disciplines experiencing similar growth in the job market.

https://www.suryasys.com/data-science-in-2021-what-you-need-to-know/