Focus 4: Broadening Participation and Workforce Development

Education and workforce development and broadening participation are intertwined

Each member of the senior leadership team is deeply committed to improving the diversity of both AI and ES workforces.  This is shown in our extensive broadening participation and workforce development and outreach plans, where we are reaching out to underrepresented populations from K-12 through community college. 

AI2ES leadership is deeply committed to improving equity and to be inclusive and welcoming to all.  As part of this commitment, we have created a strong Code of Ethics and Code of Conduct for AI2ES members.

AI2ES has three overarching goals for both Broadening Participation and Workforce Development.  These goals aim to increase the opportunities for students of all backgrounds to learn more about AI, environmental science, and AI for environmental science.

  • Build a diverse AI for ES workforce by implementing and evaluating an applied AI for ES curriculum at the Community College Level and pilot test at an HSI/MSI
  • Develop and share AI/ES curriculum for K-20 and workforce retraining
  • Broaden and train AI for ES through targeted internships, mentoring and recruitment.

Broad Goals

1. Build a diverse AI for ES workforce by implementing and evaluating an applied AI for ES curriculum at the Community College Level and pilot test at an HSI/MSI

Del Mar College AI Award

The first goal centers on the design and implementation of a new Community College AI program, being developed at DMC and in conjunction with TAMUCC. The award is designed as a multi entry program for professionals to augment their skills, for high school students as a next step in their education, for direct employment. Plans are for classes to start in the fall of 2021 and help start other such programs around the nation.

The South Texas location of the new Community College AI educational program will contribute to the diversification of the AI workforce and test a model to create an Applied AI workforce along with creating a new educational pipeline. The model will be exported nationwide through a collaboration with the Advanced Technological Education (ATE) program of two-year community colleges. AI2ES will work with the directors and principal investigators of ATE national centers to disseminate the new curriculum materials through the networks and workshops. AI2ES will push diversity through its recruiting, hiring, outreach, public events and other communication. AI2ES has ambitious goals for diversity recruitment for its team members and will improve its chances to meet these goals through talks and recruiting through SACNAS, CUAHSI and other conferences and organizations promoting entry into STEM and AI for underrepresented populations in our field. 

AI Award Curriculum

AI Award details

Curriculum of the Del Mark Community College AI Certificate

AI Award is Stackable at DMC

Stackable AI award

The AI certificate is stackable in the community college and university curriculum. 


Year 2
Community College AI Programs
  • DMC completed the new Introduction to AI course and other courses development underway.
  • Team presented program plans at the 2020 Virtual ATE Conference “Broadening the AI Workforce through a Community College Program to start national expansion.
  • New pipeline of incoming students established
  • New pipeline of graduates transferring to TAMUCC
  • New computing hardware installed in lab
AI/ML Certificate and Courses
  • Successfully completed first cohort through 2 of 3 new GeoAI courses, set for graduation in fall 2022
  • Successfully completed first GeoAI course for second cohort
  • Completed the advanced GeoAI course labs and lecture materials
  • Established F2F pipeline with local schools and government agencies for recruitment of students
  • Created pipeline of transfer students between Del Mar College and TAMUCC partners
  • Updated the new GeoAI course curriculums
  • Success in enrolling sustainable cohort of students for 2022


Leaders: Davis (DMC), Tissot (TAMUCC)
Members: Barrett (DMC/TAMUCC), Betz (DMC), Caruso (DMC), Ebert-Uphoff (CSU), Kennington (DMC/TAMUCC), King (TAMUCC), Nelson (DMC), O’Cinneide (DMC/TAMUCC), Starek (TAMUCC)

2. Develop and share AI/ES curriculum for K-20 and workforce retraining

AI2ES is actively developing modules for AI and ES for K-12, as well as tutorials for undergraduate and graduate students and workforce retraining.  Many of our outreach efforts are targeted specifically at women, under-represented minorities, low socioeconomic-status students, and first-generation students.

Our specific goals are to:

  • Develop K-12 education modules for AI & ES and share online
  • Develop and teach K-12 modules to low socioeconomic status, first generation, and URM students
  • Develop and teach AI and trustworthy AI tutorials aimed at undergraduates and graduate students for AI & ES and share online
  • Publish at least 4 tutorial papers and shared data and code on AI for ES
  • Publish at least 3 talks for the NCAR Explorer Series per year after year 1
  • Host public demonstrations of AI for ES at events such as the National Weather Festival, Weather Fest, and NCAR Super Science Saturday.
    • This is on hold until the COVID-19 pandemic restrictions are eased.
  • Make targeted partnerships to increase the impact of our education and workforce development modules as well as career training.
  • Develop and share an AI ethics curriculum which includes ES ethics.


Year 2
Trustworthy AI for Middle/High School
  • Core of AI code completed, will continue development/redevelopment as appropriate to fit AMS distribution model
  • Made contact with AMS education program director to begin coordination for deployment in Year 3
  • Identify appropriate programs, ideally targeting minority- and underserved middle and high school programs
Middle School Coding Camp
  • Successfully conducted five day Summer Code Camp, #Code_IT Camp(2021), for 15 middle school students.
  • Camp offers several levels of coding curriculum focused on spatial reasoning and computer programming, logic-based programming, and text-based coding for drones.
  • Each Team worked together towards the final project on the last day, the Ultimate Team Challenge; a competition that includes all four (4) coding projects.
  • Each camper took home a mBot Neo robot they individually built and coded to continue their STEM education.
  • Team centric approach allowed campers to improve on their technical, communication and leadership skills as they worked as a team to achieve camp objectives.
Year 1
  • Trustworthy AI for ES (TA4ES) Summer School for 2022 planning continued. The date has been set for June 27-July 1, and the website went live.
  • Site-wide meetings to full AI2ES membership continued. Topics included introductions and discussions with Industrial Partners, and “Probabilistic Assessment and Decisions”
  • Meetings were held to discuss potential collaborative educational opportunities with NOAA and with the AMS Education Programs.
  • Del Mar College is hosting Discovery Day for high schoolers. AI2ES is presenting one talk and an all-day demonstration of UAS and GIS technologies. About 900 attendees tofal (March 25, 2022).
  • Del Mar College is presenting at a NASA-funded STEM camp for secondary students on April 5 and May 21 discussing our AI2ES curriculum and projects.

Leaders: Gagne (NCAR), McGovern (OU), Rogers (CSU) 
Members: Barnes (CSU), Becker (NCAR), Betz (DMC), King (TAMUCC), Kumler (NOAA), Lagerquist (CSU/NOAA), Tissot (TAMUCC)

3. Broaden and train AI for ES through targeted internships, mentoring and recruitment

Our internal mentoring and internships will increase participation and provide research and educational opportunities to US citizens, nationals, and permanent residents, especially women and members of underrepresented groups who are undergraduate and graduate students, postdoctoral researchers, industrial fellows, faculty members from all colleges and universities, and others in the activities of AI2ES and its sub awardees. AI2ES will encourage them to pursue careers in science and engineering and will identify actions that will enhance and ensure ethnic/racial diversity throughout the life of the Institute.  Our specific goals for the internships and mentoring are listed below.

  • Mentor all AI2ES junior faculty, postdoctoral fellows, graduate students, and undergraduate students.
  • Create internships for AI & ES targeting to URMs in private industry partners
    • Due to the COVID-19 pandemic, internships will start in year 2
  • Support and hire SIParCS and SOARS internships every year
  • Hire REU students at all sites and work with existing REU programs such as National Weather Center REU program
  • Support immersive visits for postdoctoral researchers and graduate students
    • This is on hold until the COVID-19 pandemic restrictions are eased.


Year 2
Online Summer School: Trustworthy AI for Environmental Science (TAI4ES)
Short Courses and Tutorials
  • Risk Communication Tutorial
  • Deep Learning and HPC: Four-part crash-course/tutorial
  • Machine Learning Tutorial Papers for Operational Meteorology
    • Part I paper on traditional meteorology accepted with minor revisions:
    • Chase, R. J., D. R. Harrison, A. Burke, G. M. Lackmann, and A. McGovern, 2022: A machine learning tutorial for operational meteorology,part i: Traditional machine learning.,
    • Part II paper on neural networks in preparation
    • Sandbox meteorological dataset and AI models created for the aforementioned papers and the AI2ES 2022 Summer School
Diverse Students AI Pipeline
  • Hired and mentoring a diverse group of fourteen undergraduate research assistants at TAMUCC and DMC as well others AI2ES universities
  • Recruiting events for the AI2ES Community College program at local hispanic majority high schools and middle schools
  • AI2ES is mentoring REU students at OU, UA, NCAR, TAMUCC helped by IBM – 5 TAMU-CC students in internship summer 2022
  • Successfully completed two cohorts of learners in the GeoAI program at DMC
Year 1
Online Summer School: Trustworthy AI for Environmental Science (TAI4ES)
  • Industrial Partners shared internship opportunities.
  • 2 AI2ES SIParCS interns were hired at NCAR with a start date of mid-May.
  • An NCAR intern is working on short-term lightning prediction with GOES-16 data and U-Nets using NLDN lightning data from Vaisala.


Leaders: Hickey (Google), Williams (IBM), King (TAMUCC), Betz (DMC) 

Members: Barnes (CSU), Foster (Disaster Tech), Gagne (NCAR), Griffin (Disaster Tech), Hall (NVIDIA), Homeyer (OU), Kumler (NOAA), Lagerquist (CSU/NOAA), Medrano (TAMUCC), Musgrave (CSU), Snook (OU), Starek (TAMUCC), Tissot (TAMUCC), Tyle (Albany)