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    • Artificial Intelligence
    • Article

    Hybrid intelligence

    Can a human-AI partnership be equal and collaborative?

    You have these already downloaded

    We have sent you a copy of the report to your email again.

    Highlights

    • AI has fundamentally changed how a task will be accomplished and who will do it
    • Operational procedures to benefit from human-machine collaboration teams.  
    • Countless use cases and possibilities for collaborative intelligence.
    • Differences between human and AI perception are bridged by machine learning.

    In this article

    Increased efficiency   inpage
    Parallel paths   inpage
    Playing to strengths   inpage
    Super-use cases   inpage
    The hopeful outcome?   inpage
    Increased efficiency inpage
    Parallel paths inpage
    Playing to strengths inpage
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    In this articleinpage
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    Increased efficiency Parallel paths Playing to strengths Super-use cases The hopeful outcome?

    Increased efficiency

    Magnifying the human-AI relationship

    Artificial intelligence (AI) gradually improves as it learns many "human" tasks, especially repetitive ones, such as medical diagnosis, language translation, or customer service. There are legitimate concerns that AI will eventually supplant human jobs across the economy, but it’s not a near-horizon consequence.

    AI has fundamentally changed how a task will be accomplished and who will do it. And while technologies that can automate processes and increase efficiency have received much attention, perhaps the more powerful facet of AI - humans and machines that complement and magnify each other's talents - hasn’t been as much the focus of scrutiny and scholarship.

    Parallel paths

    Creating a collaborative relationship

    Understanding the "and" between humans and computers, along with automation and augmentation will encourag one another to perform at higher levels.

    Businesses are starting to adapt their operational procedures to benefit from human-machine collaboration teams. C-suite professionals globally have weighed in across numerous surveys and most are operating with a strong conviction that AI will enable humans and machines to collaborate while maximizing individual strengths.

    Symbiotic partnership between machines and people is key to creating a collaborative relationship.

    Playing to strengths

    The nexus of collaborative intelligence

    "The recent attention in AI is about how we can automate various tasks and how we can use machines to accomplish things much quicker than average humans, or even replace them if needed," says Professor Jon Whittle, a software engineering expert specializing in human-computer communications. He is also the director of CSIRO Data61. "But we expect that there's more to be experienced from incorporating machines and humans to work cohesively by sticking to their relevant strengths."

    The nexus of collaborative intelligence lies in playing to a delineated suite of specialties: human leadership, teamwork, creativity; and AI’s speed, scalability, and quantitative capabilities. For machines, what comes easily to people can be challenging; for humans, what comes easily to machines is nearly impossible. The use cases and possibilities are countless. 

     

    Super-use cases

    Different points of view

    An AI-assisted strategy can accelerate the hunt for disease treatments, provide creative answers to environmental issues, and even start to tackle persistent societal biases. "This is the future of work ethics: advanced human brains collaborate with high-performing artificial intelligence to accomplish difficult tasks, create new possibilities and beautify the world," says Colin Harper, a tech reporter for Coin Desk.  

    Researchers have also been examining the difference between human perception and machine judgment to help humans and AI systems work together. Specific tasks require little uncertainty, while others, like creative tasks, may demand more risk-taking behavior. The way a machine sees and understands the environment is fundamentally different. Tom White, a lecturer in computational design at the University of Wellington in New Zealand, created a perception engine to demonstrate how the machine views the world, as reported in The Verge. His work highlights potential uses for the machine learning method to bridge gaps in human perception and impact societal values.

    The hopeful outcome?

    Enhancing decision-making with applied intelligence

    Prototypes of human-machine collaborations for enhanced judgment and decision-making have existed for decades. In the same way that machines depend on humans to advance, humans can accomplish more with machines than they can on their own – it’s applied intelligence.

    The hopeful outcome? Enterprise and initiatives where humans and machines coexist peacefully in a long-lasting, meaningful relationship. In the end, creating and integrating AI companions seems remarkably, well, human.

     

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