Line of Effort 4: Talent and Training
The challenge
Effective implementation of AI will require the right people with the right training in the right place at the right time. The future DND/CAF workforce will require diverse personnel with a broad range of both technical and non-technical skills. These include multidisciplinary specialists with advanced skills, such as machine learning engineers, data engineers, data scientists, cyber security specialists, and AI product managers. It will also require those with soft skills including ethical reasoning, systems thinking, creativity, problem solving, communications, and human-centred design. In addition, it will also need personnel in the fields of IT, law, policy, human resources, procurement, and finance with the skills and knowledge to support AI initiatives and a diversity of identities, backgrounds, and perspectives. This talent must be identified, cultivated, and used to its fullest potential when and where it is needed.
DND/CAF recruitment, retention, training and deployment are not yet equal to this challenge. Overall levels of data literacy are low, AI skills are scarce, and personnel with AI knowledge are in short supply. While the CAF recognizes its own need for AI skills, it often struggles to make use of those specialized personnel it already has. Members have described their specialization in AI and related fields as career limiting and speak of having to choose between remaining within their technical field and a career path that would lead to promotion. Unsurprisingly, the frustration this produces leads members to release, or transfer to the reserves.
What we must do
We must identify and plan for our workforce needs. DND/CAF must identify the skills, perspectives, and competencies its personnel, both military and civilian, will need to ensure they can understand new technologies, absorb them into the battle space and corporate space, and develop the new operating concepts, organizations, and strategies to use them effectively and ethically. This process will require identifying what must be cultivated within the organization and what can both safely and effectively be contracted out. It should also consider the adequacy of recognized competencies and existing trades, classifications, and occupations, and how the trades, career management, and staffing may need to be revised to make them able to accommodate AI. Given the rapid pace of technological development, this cannot be a one-time exercise but must be ongoing to ensure that we have the balance of skills required by these technologies, and that our training equips our people to procure, sustain, and use it effectively and safely. Once these needs are identified, they must inform robust planning for military recruitment and civilian human resources. This must give consideration for the impact of such changes on organizational inclusion and diversity.
We must cultivate AI readiness among our existing people. This must begin with ensuring adequate data and digital literacy: without these skills, achieving AI implementation will be impossible. We must be ready to invest in continuous development of the skills of our existing and future workforce to help them keep pace with AI development outside the enterprise, accelerate the acquisition of expertise, and enable them to progress within their career and adapt to new roles in the future. Comprehensive and high-quality AI training is widely available, often free or at minimal cost from software providers, but DND/CAF will need to allow personnel to take training within working hours. It will also need to offer opportunities to learn by doing and to use the skills learned so they are not lost. More specific training to address the skills to support AI use may need to be developed in-house or co-created with the Canada School of Public Service (CSPS) or private providers. These include training for leaders and decision makers in the opportunities, risks, and limitations of AI and how to assess and maintain appropriate human involvement in system decisions. They also include the soft skills needed for communication, ethics, ideation, and design, and the administrative skills to procure, staff and sustain AI tools. Moreover, these skills must be regularly reviewed and adapted as strategic circumstances, capabilities, and technology change. Existing professional military education programs must be reviewed and adapted to incorporate these skills, and to address issues such as the ethics and military implications of data and advanced technology. As we automate repetitive tasks too, we must plan to upskill and redeploy those personnel who previously performed them to more challenging and rewarding tasks that require human judgement.
We must find new ways to bring critical skills into the enterprise–and to retain and use them. AI and data skills are in high demand in the private sector, and we will need to compete with the private sector to recruit and retain personnel with these skills. Militaries worldwide are experimenting with new ways of identifying and recruiting talent to the regular, reserve, and civilian workforce, and as embedded contractors, and we should learn from them. We must explore flexible, streamlined, and non-traditional pathways to bring world-class AI talent into the organization and expand access to outside expertise, including short-term exchanges with industry and academia. Career pathways, development and management of CAF members will need to be reviewed and adapted to support attraction and retention of AI-related talent and provide pathways for its professional advancement. Finally, we must consider ways to make use of the depth of skills present among current and potential members of the Reserve Force. This could include the creation of technical reserves and routes to identify and reward technical talent outside traditional ranks. We must offer Canadians ways to bring their skills to DND/CAF on a part-time basis in roles that offer opportunities to make an impact using leading AI technologies to solve consequential problems.
How we will do this
- Review DND/CAF workforce needs for AI. DND/CAF must review its AI workforce requirements to identify the skills, competencies, and personnel required to implement AI successfully. This must include not only subject matter experts in AI, but also staff whose roles support the AI lifecycle, including civilian and military leadership. Such a review must include GBA Plus to assess the impact of these changes on workforce inclusivity and diversity.
- Identify priority AI workforce training requirements and develop or procure curricula to meet them. DND/CAF must identify and plan to meet its priority needs through in-house curriculum development, external procurement, and academic partnerships. This review should consider training needs at all levels and new options for both academic and professional training to ensure a talent pipeline catered to future needs.
- Explore and identify processes to recruit and retain AI talent, and to use it where it is needed. DND/CAF must explore non-traditional routes and processes to identify and place talent, such as short-term exchanges, the creation of technical reserves, and more flexible career pathways allowing for talent attraction above entry level.
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