What ‘AI and Me’ means for you in today’s workforce

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In the past few years, more and more enterprises are adopting artificial intelligence (AI) in their daily business.

In fact, our global survey of 6,074 business and IT C-level executives and directors at companies across 25 countries and 21 industries indicates that 73 percent of organizations are piloting or adopting AI in one or more business units.

While AI is increasingly being applied to bigger challenges, it’s still largely focused on automation, leading people to worry about losing their livelihoods.

Automation to collaboration

Accenture Technology Vision 2020 advocates a new approach.

AI and Me, one of the five trends in this year’s report, shows how artificial intelligence brings out the full power of people. Move beyond deploying AI for automation alone and push into the new frontier of co-creation between people and machines.

Consider autonomous vehicles.

These cars use a wide array of sensors and AI to “see” the world around them, but people are already aware of close calls during test situations and, in one case, a pedestrian fatality, giving rise to serious concerns and distrust around autonomous technology.

Volvo and Perceptive Automata are working together to build safer autonomous vehicles by pairing computer vision with behavioral science and neuroscience to understand the intention and awareness of pedestrians. By teaching autonomous vehicles about human intuition and why people might act the way they do, the companies are making it safer for these vehicles to operate on busy streets.

Fresh insights along the AI journey         

Even as enterprises embrace the power of AI, they are realizing that they can achieve only a fraction of their AI potential. Simply using AI to make organizations run faster and cheaper limits its impact.

Now, leaders are leveraging the potential of AI systems to transform not just how businesses work, but also what they actually do. By consciously structuring their organizations with human and machine collaboration at the core, pioneers are already positioning AI to be a driver of change.

Creating the symbiotic AI workforce

Meet Diarmuid Cahalane, Technology Research Principal at the Accenture Labs at The Dock, Accenture’s innovation hub in Dublin. Diarmuid is passionate about how we can do so much more with humans and artificial intelligence working together.

Through an experiment called Symbiosis, Diarmuid and team show how they are creating a symbiotic workforce of the future.

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The R&D team from Labs and The Dock partnered with a team of medical coders who worked with some of our health care clients. The medical coders analyzed patients’ medical charts, taking complex information about diagnoses, treatments and medications, validating the diagnostic codes the healthcare providers had applied to the charts. The coders were already consuming output from an AI system that helped them do this work.

As Diarmuid explains, “Understanding the medical expertise and the motivations of the coders pointed us to a win-win scenario—of having them also train the AI. So, we gave them a way to do that. In this manner, both the people and the machine played to their respective strengths—the machine dealing with relatively simple tasks at high volume and the people focusing on cases that required their deep expertise and skills in clinical decision-making.”

Diarmuid attributes the success of the project to having a very broad range of skills on the R&D team—software engineers, designers, data scientists and researchers. There was even a journalist hired to help understand the users, their team dynamics and their interactions with the AI system.

On the technical front, the project team had to look beyond the conventional machine learning and deep learning toolkit. They worked with knowledge graphs, belonging to the semantic branch of artificial intelligence technologies. “As human-AI collaboration becomes more pervasive in processes and decision-making, semantic approaches can help bridge the gap between the reasoning capabilities of humans and machines,” says Diarmuid.

The experiment itself wasn’t huge, but it taught managers and data scientists an important lesson—maximizing the value of AI means focusing on people. Transforming a team of passive users of an AI system into its domain expert trainers creates a feedback loop that enhances the skills and potential of both the people and the machine.

Skills are evolving and adjusting

Automation required designing the skills to get a job done, but collaboration demands the ability to communicate and iterate with partners. To foster human and AI collaboration, businesses will need to explore and master the tools and advancements that enable humans and machines to better engage each other.

Natural language processing (NLP), explainable AI and extended reality (XR) will all unlock new ways for humans to interact with machines and for machines to interact with us. In this scenario, we need people who are skilled at imagining, articulating and building out use cases that let both people and technology play to their strengths.

Technologists who are open to working with designers, researchers, psychologists and domain experts stand a better chance of co-creating successful human-machine collaborative solutions.

Are your skills ready to ride on this new wave of artificial intelligence?

Watch our Technology Vision 2020 Global Webcast for insights and examples on the five trends shaping the technology industry and what that means for today’s workforce. 

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