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Generative AI - merging human and artificial intelligence by Dr Hanlie Smuts

Knowledge production and management are inherently human-centered. Therefore, the most effective roles assigned to generative AI in KM will mostly augment humans rather than replace them. Generative AI cannot make something from nothing – it is trained on existing data and information. Thereby achieving collaborative intelligence, in which generative AI and humans enhance the complementary strengths.

Generative artificial intelligence (AI) is artificial intelligence capable of generating text, images, or other media, using generative models e.g. OpenAI’s DALL-E 2 (text-to-image model). We know already that:

  • AI will impact knowledge work, knowledge management and streamlining work, however the pace of the change has critical implications

  • Fast-paced creation of content (in our already information-overloaded workplaces)

  • Generative AI is trained on large corpuses of information, which encode the biases of that material

  • Impact our skills, from generating text to being a good editor, deciding what to keep and what needs to change (e.g. fact-checking AI generated text and spotting visual flaws)

Knowledge is at the core of innovation, and enhancing KM practices help accelerate the flow of ideas and collaboration. However, organisations struggle with the time and effort required to capture and maintain knowledge to create a thriving KM practice, drive employee productivity and ensure people can find organisational knowledge. Therefore, moving KM toward agility helps driving its success! Agile in the KM context means rapid implementation and results, being adaptive to culture, context, and the business environment, and focused on changing knowledge sharing mindsets and behaviours.


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