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What is Data Science?
Data science is rapidly becoming a new paradigm for research and discovery, integrating approaches from computer science, statistics, applied mathematics, visualization as well as communication and many application domains. So what is data science used for? Data science seeks to extract knowledge and insight from datasets that are often large and/or messy. It helps organizations make sense of the information they gather from their customers, business partners and their own operations, to then make better informed choices.
But how do data science and machine learning work together? Innovations in the methods for exploratory data analysis (EDA), visualizing and interpreting data — such as artificial intelligence and machine learning — are core to extracting these insights. The far-reaching possibilities of data science and machine learning have highlighted how critical the field is to data-intensive discovery across all research domains.
What is Responsible Data Science?
Responsible data science means systematically reflecting on and addressing the ethical and societal implications of every decision in the data life cycle, including but not limited to power, bias, privacy and security concerns.
Development and use of responsible data science approaches are still limited by two main elements:
- The general lack of integration of trained socio-technical data scientists and social science concepts into data science research and education.
- The need for foundational changes to how we “do science,” from how we recognize intellectual contributions to how we infuse responsible, ethical practice in every aspect of data science teaching and research.
What About Artificial Intelligence?
Artificial intelligence is a powerful tool that data scientists use to solve research, business and operational problems. While AI has been around for many decades, recent advances have brought AI to the forefront, and data scientists are paying attention. The Academic Data Science Alliance and the academic data science community engage with AI in its many forms, for applications in medicine, physical and biological sciences, and beyond.
Here at UNC-Chapel Hill we are also committed to understanding the ethical dimensions of using AI tools in data science, and to examining how data scientists can advocate for ethical applications of data analysis and machine learning in their research. That’s why the ethical use of AI tools is emphasized throughout the program — when exploring the use of machine learning or examining trending topics in data science.
What Do Data Scientists Do?
Data scientists are tasked with developing and implementing a set of techniques or analytics applications to transform raw data into meaningful information for organizations. Using data-oriented programming languages and visualization software, data scientists utilize data mining, data modeling, natural language processing and machine learning to extract and analyze information.