The future of AI is collaboration, not automation - The EE

The future of AI is collaboration, not automation

Emma Kendrew of Accenture Technology

Artificial intelligence (AI) has received a mixed reception over the past few years. In one corner there are those who hype its capabilities far beyond reality. In the other are the pessimists, fearful of the mass unemployment it could unleash. And, says Emma Kendrew, intelligent engineering services lead for Accenture Technology, that’s not to mention the downright dystopian, swayed by years of disquieting sci-fi films. The possibility of a finer balance, that does not pit human skills directly against AI, is often ignored.

Recently it looked like round one might be won by the pessimists. Many enterprises have focused on automation alone and are struggling to scale AI out of the pilot stage. But the COVID-19 outbreak has seen the other side make a comeback. In healthcare, projects like the COVID-19 Open Research Dataset are pooling data provided by humans so that AI systems can look for patterns to accelerate discovery. Contact centres are using AI chatbots to deal with routine responses so that human agents can handle the spike in trickier enquiries. And AI tools are helping to keep people healthy and informed, from virtual healthcare assistants to AI-powered thermal cameras for fever detection.

In many diverse settings we’re seeing the benefits of the technology and our fears are beginning to subside in the face of experience. These projects bring together AI’s capacity to use limitless amounts of data to explore new possibilities with people’s ability to direct and refine ideas.

Digital Human Brain Covered with Networks

We’re finally seeing the true potential of AI in the spotlight: human-AI collaboration. When people collaborate with AI the technology can be more than just another tool. Instead, it can become an agent of change in the business, interacting and adapting to its environment and the people around it.

Collaboration comes through effective communication

At the heart of successful collaboration is effective communication. Of course, the accuracy of the data must be ensured – AI can only be as good as the data it receives – but the way it receives it is just as crucial.

Several recent developments in the field have made this possible. Natural language processing (NLP), explainable AI and extended reality (XR) are all unlocking pathways for interaction. Advancements in NLP allow machines to better understand contexts and nuances of language that previously fell between the cracks. But it is image recognition and machine learning in XR environments that is catalysing the movement toward human-AI collaboration, by allowing programmes to recognise and understand their surroundings.

Businesses must prepare employees to understand how they can take advantage of AI

However, despite these advances, only 23% of organisations are preparing their workforce for collaborative, interactive and explainable AI-based systems, according to Accenture’s 2020 Technology Vision report.

If businesses are to push beyond deploying AI for automation alone, then steps must be taken to give employees a better understanding of how AI systems work. As people become more familiar with AI through interactive experience they will be better equipped to use the results, such as strategic recommendations, in their role.

That’s not to say everyone has to become an expert in the technology, the onus is still on enterprises to democratise it. This means they must create the context for people throughout the organisation to use the technology, no matter what department they work in.

This will allow employees to couple their unique talent and knowledge together with AI. Take OpenAI’s MuseNet, an AI that collaborates with humans to compose music. A human provides a starting sample, a target style and instrument preferences. MuseNet then uses what it has learned from hundreds of thousands of musical files to make suggestions about the next segment of a composition. It is a relationship of interaction and collaboration, human and machine bouncing off one another, to create an output that neither would have generated in isolation.

The new COVID-shaped world is ready for human-AI collaboration

There is little doubt that AI integration is already high on the agenda of businesses, with 73% of organisations piloting or adopting AI in at least one business unit. But cost-saving and time-cutting through automation is generally the focus.

This may be the moment that permanently alters the common mindset towards AI. A 2019 global Accenture study on AI found that one of the top roadblocks to scaling the technology is lack of employee adoption. But as people directly benefit through virtual healthcare assistants and AI-powered thermal cameras, a new trust has begun to develop. Businesses can take advantage of this unique moment by integrating true human-AI collaboration now and showing off the technology at its best.

The next few months will continue to accelerate the integration of AI as businesses realise its usefulness and value separately from the immediate necessity. But only those that focus on collaboration, not just automation, will build the next generation of intelligent businesses — where humans and AI systems work together to reimagine what’s possible.

The author is Emma Kendrew, intelligent engineering services lead for Accenture Technology.

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