Katherine Ensor

This thought was true in 2015 when it was included in an ASA Board statement on the role of statistics and data science, and it remains true today. When the statement was issued, the ASA promised to be the “Big Tent for Statistics and Data Science.” I would like to share the work we are doing to fulfill this promise and extend our leadership by highlighting three important initiatives: the formation of the Committee on Data Science and Artificial Intelligence; our ongoing efforts to participate in data science program accreditation; and the NSF-funded National Data Mine Network project.

Data Science and Artificial Intelligence

I had the pleasure of working with Mark Glickman on the ad hoc Data Science Advisory Committee Task Force. The committee specifically focused on generating ideas for the ASA to consider that fell into two main categories. The first category consisted of ideas related to providing greater data science exposure and initiatives to ASA members. The second consisted of ways in which the ASA could become more of a home for data scientists who were not already ASA members. As the board discussed the committee’s recommendations, we recognized it was important to draw upon individuals who could advise us on opportunities and strategic moves.

I am delighted to announce that Mark has agreed to chair the newly approved Committee on Data Science and Artificial Intelligence. The committee’s charge is the following:

Recognizing the importance of statistics to data science and artificial intelligence and recognizing that these domains are an integral component of our society that will continue to grow in their contributions and influence, the committee will advise the board of directors and the ASA in general in this arena.

“I am thrilled to have the opportunity to chair the ASA Committee on Data Science and AI,” said Mark. “Our committee is a diverse group of experts from academia, industry, and government who are enthusiastic about making a real impact. I am looking forward to meeting with the committee on a regular basis to develop ways to improve data science and AI resources for ASA members and to attract the involvement of non-ASA data scientists in ASA-led activities.”

This committee will fill an important role, ensuring statisticians are at the data science and artificial intelligence leadership table in all sectors.

CSAB Update

On April 21, 2021, the American Statistical Association became a full member of the CSAB, joining the world’s two largest professional and technical societies for computing—the Association for Computing Machinery (ACM) and the IEEE Computer Society (IEEE-CS). As the lead ABET member society for computing, CSAB is responsible for developing accreditation criteria and selecting, training, and assigning program evaluators in computer science, cybersecurity, data science, information systems, information technology, and software engineering. I am privileged to represent the ASA on the CSAB board of directors. Our participation has been enthusiastically welcomed by the other CSAB members.

Programs in data science and data analytics, which have previously not fallen under ABET’s accreditation umbrella, are now eligible for ABET accreditation. There are two distinct ABET groups working on data science program accreditation criteria: the Applied and Natural Sciences Accreditation Commission (ANSAC) and Computing Accreditation Commission (CAC).

Representing our community as a member of the curriculum committees of both ANSAC and CAC is Dave Hunter, professor and former chair of the statistics department at Penn State. Guided by input from many of you, Dave has been able to contribute the perspective of our community. Our efforts led to the criteria reflecting the essential contributions of statistics, and we will continue to advocate for our profession. I encourage you to review and share comments on the draft criteria.

The accreditation process requires a self-study, which is submitted by the department seeking accreditation. A review team is assigned to review the self-study and, ultimately, a site visit is scheduled. As part of our involvement, we will identify individuals to serve as program evaluators. This is an important role, and I am deeply grateful to Ben Baumer of Smith College and Mine Çetinkaya-Rundel of Duke University, who are serving as program evaluators. We are planning an information session at JSM 2022. To stay informed about our efforts, sign up to receive periodic updates.

National Data Mine Network

In an effort to continue our work in data science, we have won a three-year, $1.5 million grant from the National Science Foundation to ensure students from historically underrepresented groups have access to cutting-edge data science courses, research opportunities, and industry partnerships. Mark Daniel Ward (Purdue University) is the principal investigator (PI) for the project, with support from co-PIs Monica Jackson (American University), Donna LaLonde (American Statistical Association), Talitha Washington (Atlanta University Center Data Science Initiative), and me (Rice University).

Our goal is to create an educational ecosystem that makes data science knowledge and skills accessible and attractive to students. As Mark [Ward] shared, “Data science is exceedingly interdisciplinary, and this gives us a great opportunity both to engage students and also address the need for diversity in the workforce.”

Students in the National Data Mine Network will use high-performance computing to solve data-driven challenges that arise in every sector of industry, including biomedical engineering, health care engineering, image processing, manufacturing, supply chain management, and transportation. A hallmark aspect of this program is the ability to work on real-world projects with mentors from industry.

The network will directly fund 300 undergraduate students at a cross-section of minority-serving institutions with 100 research stipends per year. To learn more about the project and ways you might contribute, sign up for updates.

I am immensely excited about the future of all three of the AI and data science undertakings. These initiatives reinforce and strengthen the contributions of statisticians to these important areas. A heartfelt thank you to our leaders committing their valuable time, energy, and insight to advance our community’s perspective.

Sending well wishes for a wonderful April. I look forward to hearing from you.