Generative AI is a type of machine learning algorithm. These models synthesize massive amounts of information and generate unique output, including text, audio, images, and video. ChatGPT is the most famous example, but many others, like Bard, Midjourney, DALL·E 2, and ElevenLabs, are emerging almost weekly. And market opinion suggests AI will soon be irrevocably part of our work.
Bias-free
AI is only as good as the data it learns from, and that’s not always in your control. It may reproduce both clearly harmful content; and output that works against diversity, equity, and inclusion efforts more subtly. Moreover, human errors can produce unintended consequences, like misinterpreting positive language as negative. So it’s imperative to check results to ensure AI performs
as intended.
Needs assessment: Discern learner needs and organizational goals to choose the right solution to meet them.
Storytelling: Understand and connect pain points to business needs to engage learners and make training actionable.
Learning design: The art and science of crafting sound learning that drives behavioral change.
Triage: Identify business needs and solutions to increase productivity, innovate, and customize to impact further.
Collate: AI’s ability to synthesize and summarize is handy when pulling information from varied source documents or inputs.
Brainstorm: As a draft thought partner, AI is the MVP. Generate scenario ideas, starter topics, or a dozen quiz questions.
Sourcing: Train AI to draw the right information at the right time.
Modify: Use AI to switch up tone, language, or style.
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