A program that teaches US Air Force personnel the basics of artificial intelligence | MIT News

A new academic program developed at the Massachusetts Institute of Technology aims to teach US Air and Space Forces personnel to understand and use artificial intelligence technologies. lately Peer review studyProgram researchers found this approach to be effective and well-received by employees with diverse professional backgrounds and roles.

The project, which was funded by the Air Force’s Artificial Intelligence Accelerator Division at MIT, seeks to contribute to educational research for artificial intelligence, particularly regarding ways to broadly maximize learning outcomes for people from a variety of educational backgrounds.

The experts at MIT Open Learning have built a curriculum for three general types of military personnel—leaders, developers, and users—using MIT’s educational materials and resources. They also created new, more experimental training courses aimed at leaders of the Air and Space Forces.

Then, MIT scientists led a research study to analyze the content, evaluate the experiences and outcomes of individual learners during the 18-month trial, and suggest innovations and ideas that would ultimately enable the program.

They used interviews and several questionnaires, given to both program learners and staff, to assess how 230 Air and Space Forces personnel interacted with the course materials. They also collaborated with MIT faculty to conduct a content gap analysis and determine how to further improve curricula to address desired skills, knowledge, and mindsets.

Ultimately, the researchers found that military personnel responded positively to hands-on learning. value asynchronous and time-saving learning experiences to fit their busy schedules; He highly commended the team-based experience, and learning by making content, but sought content that included more professional and soft skills. Learners also wanted to know how AI can be directly applied to their daily work and the broader mission of the Air and Space Forces. They were also interested in more opportunities to interact with others, including peers, coaches, and AI experts.

These are the findings of the program’s researchers recently Participated in the IEEE Frontiers in Education conferenceThe team is increasing educational content and adding new technical features to the web portal for the next iteration of the study, which is currently underway and will extend through 2023.

“We’re delving deeper into expanding what we think are learning opportunities, driven by our research questions and also by understanding the science of learning around this kind of scale and complexity of a project. But ultimately we’re also trying to deliver some real transformational value to the Air Force and the Department of Defense. This work makes a real impact. For them, this is really exciting,” says Principal Investigator Cynthia Brizel, MIT Dean for Digital Learning, Director of MIT RAISE (Responsible Artificial Intelligence for Social Empowerment and Education), and Chair of the Personal Robotics Research Group at the Media Lab.

Building learning journeys

At the beginning of the project, the Air Force gave the program team a set of profiles that captured the educational backgrounds and job functions of six primary categories of Air Force personnel. The team then created three prototypes that it used to build “learning journeys” – a series of training programs designed to impart a set of AI skills to each profile.

The Lead-Drive archetype is the individual making strategic decisions; Create-Embed archetype is a technical agent who implements AI solutions; The Facilitate-Employ prototype is an end user of AI-enhanced tools.

Convincing the lead-drive model of the importance of this program was a priority, says lead author Andrés Felipe Salazar-Gomez, a research scientist at MIT Open Learning.

“Even within the Department of Defense, leaders have been questioning whether training in AI is worth it,” he explains. “First we needed to change the mindset of the leaders so they would allow learners, developers and other users to go through this training. At the end of the pilot we found that they had embraced this training. They had a different mindset.”

The three learning journeys, spanning six to 12 months, included a combination of current AI courses and materials from MIT Horizon, the MIT Lincoln Lab, the MIT Sloan School of Management, the Computer Science and Artificial Intelligence Laboratory (CSAIL), and the Media Lab. and MITx MicroMasters. Most modules have been delivered entirely online, either synchronously or asynchronously.

Each learning journey included different content and formats based on users’ needs. For example, the Create-Embed journey included a five-day in-person training course taught by a research scientist at Lincoln Laboratory that provided a deep dive into the subject matter of AI technology, while the Facilitate-Employment journey included self-paced, asynchronous, material-based learning experiences. MIT Horizon designed for a more general audience.

The researchers also created two new courses for the Lead-Drive group. First, a concurrent online course called The Future of Leadership: Human-AI Collaboration in the Workforce, Developed in collaboration with Esme Learning, leaders desire more training on ethics and human-centered AI design and more content on human-AI collaboration in the workforce. The researchers also crafted a three-day, experimental, personal training course called Learning Machines: Arithmetic, Ethics, and Politics, which immersed leaders in a construction-style learning experience where teams worked together on a series of hands-on activities using autonomous robots that culminated in an escape room-style culmination competition brought together. All together.

Brizel says the machine learning course has been hugely successful.

“At MIT, we learn through teamwork and through teamwork. We thought, what if we let executives learn about AI this way?” she explains. “We find that the engagement is much deeper, and they gain a stronger intuition about what makes these technologies work and what it takes to implement them responsibly and aggressively. I think this will profoundly inform how we think about the implementation education of these types of disruptive technologies in the future.”

Collect feedback and improve content

During the study, the MIT researchers checked on the learners using questionnaires to get their feedback on the content, teaching methods, and techniques used. They also have MIT faculty analyze each learning journey to identify educational gaps.

In general, the researchers found that learners wanted more opportunities to engage, either with peers through team-based activities or with faculty and experts through concurrent components of online courses. And while most employees found the content interesting, they wanted to see more examples that applied directly to their day-to-day work.

Now in the second iteration of the study, the researchers are using this feedback to improve learning journeys. They are designing knowledge checks that will be part of the asynchronous, self-driving courses to help learners engage with the content. They are also adding new tools to support live Q&A events with AI experts and help build more community among learners.

The team is also looking to add specific examples from the Department of Defense across the tutorial modules, and include a scenario-based workshop.

“How do you raise the skills of a 680,000-strong workforce across diverse work roles, all levels, and at scale? This is an MIT-sized problem, and we’re capitalizing on the world-class work that MIT Open Education has been doing since 2013—improving Democratize education on a global scale, says Maj. John Radovan, deputy director of the DAF-MIT AI Accelerator.”By leveraging our research partnership with MIT, we are able to research optimal teaching methods for our workforce through focused pilots. We can then multiply the positive unexpected results and focus on the lessons learned. This is how you accelerate positive change for our pilots and parents.”

As the study progresses, the program team is increasing their focus on how this training program can reach a broader reach.

“The US Department of Defense is the largest employer in the world. When it comes to AI, it’s really important that all of their employees speak the same language,” says Kathleen Kennedy, director of MIT Horizon and executive director of the MIT Center for Collective Intelligence. “But the challenge now is to scale this up so that learners as individuals get what they need and stay engaged. And that will definitely help in knowing how to use the different MIT platforms with other types of large groups.”

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