  The rapid advancement of artificial intelligence (AI) is changing our lives
in many ways. One application domain is data science. New techniques in
automating the creation of AI, known as AutoAI or AutoML, aim to automate the
work practices of data scientists. AutoAI systems are capable of autonomously
ingesting and pre-processing data, engineering new features, and creating and
scoring models based on a target objectives (e.g. accuracy or run-time
efficiency). Though not yet widely adopted, we are interested in understanding
how AutoAI will impact the practice of data science. We conducted interviews
with 20 data scientists who work at a large, multinational technology company
and practice data science in various business settings. Our goal is to
understand their current work practices and how these practices might change
with AutoAI. Reactions were mixed: while informants expressed concerns about
the trend of automating their jobs, they also strongly felt it was inevitable.
Despite these concerns, they remained optimistic about their future job
security due to a view that the future of data science work will be a
collaboration between humans and AI systems, in which both automation and human
expertise are indispensable.
