In my last post, I mentioned a HBR article on Collaborative Intelligence that put me on the path to embrace AI as a set of emerging tools and technologies that can augment my human tasks, from creativity to ideation to personal and professional effectiveness.
This notion of augmentation is at the heart of Markus Bernhardt's recent article in the January edition of the TD Magazine from the Association of Talent Development.
Bernhardt discusses both generative and non-generative AI and helpfully provides a clear differentiation of the two and how they can be used by those in talent development, learning and development and Human Resources. Generative AI, Bernhardt writes, offers creative possibilities to strengthen personalized learning and performance support:
In TD, that can translate to tools that craft training content tailored to individual needs—more generally and long term, based on learners' previous interactions and feedback, or more short term, in the moment of need, for performance support.
Nongenerative AI, or machine learning tools, can:
In the context of TD... automatically map out learning content and resources—in line with skills frameworks or learning objectives—quickly, highly efficiently, and at scale.
As Bernhardt helpfully points out:
For TD professionals who look to deploy AI tools, the key lies in creating balance. Leverage the creative prowess of generative models while grounding decisions in the analytical strengths of nongenerative ones. You must comprehend the underlying mechanics, note the potential pitfalls, and use the tools to augment—not replace—human intuition and expertise. Deploy AI tools in targeted and specific use cases, with clear outcomes and goals in mind, one step at a time.
I have highlighted Bernhardt's usage of augmentation and not replace of human skills and competencies, which echo the views of the authors of "Collaborative Intelligence." Bernhardt goes on to describe specific opportunities for such augmentation in supporting onboarding and training, developing and managing continuous learning and development frameworks, and offering performance support. In all, the emphasis on how the leveraging of AI tools can enhance the capacities of TD professionals to train and support new hires, create automated tools to support personalized learning and development plans and provide targeted guidance in areas that need improvement. Bernhardt's point is to not remove the human touch of a skilled TD or LD professional, but to augment the services and supports this professional can offer to others on a team or in an organization. In that sense, Bernhardt reiterates the thesis of human collaboration with AI, yes, with the potentially benefits of increased productivity and efficiencies, but also of tailored and personalized supports that could increase and maximize human potential, arguably the ultimate goal of TD professionals.