New AI capabilities that can recognize context, concepts, and meaning are opening up surprising new pathways for collaboration between knowledge workers and machines. Experts can now provide more of their own input for training, quality control, and fine-tuning of AI outcomes. Machines can augment the expertise of their human collaborators and sometimes help create new experts. These systems, in more closely mimicking human intelligence, are proving to be more robust than the big data-driven systems that came before them. And they could profoundly affect the 48% of the US workforce that are knowledge workers—and the more than 230 million knowledge-worker roles globally. But to take full advantage of the possibilities of this smarter AI, companies will need to redesign knowledge-work processes and jobs.
Using AI to Make Knowledge Workers More Effective
Humans and machines can make each other better.
April 19, 2019
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Summary.
New AI capabilities that can recognize context, concepts, and meaning are opening up surprising new pathways for collaboration between knowledge workers and machines. As knowledge workers embark on the job of reimagining how to better leverage knowledge work through AI, they should focus on telling the AI what’s important to them rather than letting the AI decide what it thinks they want to know; training the AI to have common sense; and helping the AI understand how human experts think and work.