Human-Machine Collaboration

Relying on generative AI tools to boost human efficiency can lead to more homogenous, less-original work outputs.

Organizations can develop effective digital twins despite limited training data by combining AI and human knowledge.

Apply these techniques when crafting prompts for large language models to elicit more relevant responses.

Prompting users to spot errors when using generative AI to complete reports improves the accuracy of the final product.

On the Me, Myself, and AI podcast, Stitch Fix’s Jeff Cooper explains how generative AI enables employees to gain more efficiencies while still connecting with customers.

Understanding large language models’ limitations can help users discern which tasks they are and are not well suited for.

On the Me, Myself, and AI podcast, learn how social scientists help facilitate human-machine collaboration at Intel.

Consumer fears of losing autonomy hinder smart-product adoption and use. But there are ways to boost customer control.

To succeed with AI, design applications and workflows that tap the best of what people and machines have to offer.