Semi-autonomous cars with self-driving navigation features to help drivers navigate traffic. Media outlets that use intelligent software to pre-write articles for human editorial review. Robots that work alongside astronauts to retrieve space junk.
These are not the storylines of sci-fi novels, but real world examples of how companies are stretching their boundaries to embrace humans and machines as team members in a future collaborative workforce. In the push to go digital, these businesses are recognizing that people and machines working together have the potential to achieve better results and tackle bigger challenges than either could separately.
For example, NASA is teaming astronauts and robots together to face the difficult task of cleaning up derelict satellites. Outfitted with advanced analytics algorithms and stereoscopic cameras, robot spheres are analyzing space junk to quickly map each piece’s spin, velocity, trajectory and center of mass—allowing astronauts to capture it safely.1
We explore this blended workforce trend more fully in the “Workforce Reimagined” chapter of the Accenture Technology Vision 2015. Benefits include the ability to automate tasks, improve processes and contribute to a positive feedback loop—driving increased intelligence, performance and productivity across the enterprise.
If you think about, this intersection between humans and machines is already beginning to happen all around us. This phenomenon is based on three technology advancements:
More natural interfaces—Developments in natural language processing (NLP) and speech recognition are making it much easier to communicate and interact with technology. Voice searches on mobile phones are increasing in popularity because speech recognition is now more reliable. By making unstructured conversations, written or spoken, searchable in real-time, NLP is acting as the enabler behind speech recognition.
Expect Labs’ MindMeld is further leveraging advancements in NLP with its “anticipatory computing” app that listens to voice conversations and surfaces relevant information in real-time.2 Customer service agents could use MindMeld technology, for instance, to suggest effective responses for the agent. This type of human-machine collaboration could enhance the customer experience, while reducing call time.
Wearables—Wearable technology is now collecting more data via sensors, communicating more information through displays and helping companies improve operational efficiency and worker safety. For instance, Accenture’s Life Safety Solution outfits workers in oil and gas refineries or chemical plants with a lapel-based wireless four-gas detector, in addition to a panic button and a motion sensor.3 By continuously monitoring the environment, companies can mitigate risks.
Wearable technology can provide further value by displaying critical information in unobtrusive ways. With smartglasses, doctors can look directly at their patients while maintaining a constant view of vital patient data. Surgeons at Indiana University Health Methodist Hospital are doing this now by using Google Glass assistance during the removal of abdominal tumors.4
Smart machines—As the field of robotics continues to advance, more machines are becoming capable of physically working side by side with humans. This has powerful ramifications for boosting process productivity. In an auto manufacturing trial, a human-robot team was able to assemble the frame of a car 10 times faster than a team of three professionals. How? For simple welds, a robot with a video projector would show a human where to place a specific part; then the robot would make perfect welds in five seconds per weld. For more difficult welds, however, the robot would defer to its human partner to perform better.5
In order to build this new workforce, companies must prioritize the training of the blended workforce, helping their human talent grow the skills needed to complement machine capabilities. Furthermore, companies must start making technology more approachable and usable to a broader set of employees. Another way to improve interactions between people and machines is to “democratize” technology—finding ways to categorize and shift skill sets so that employees can approach tasks that were previously reserved for specialists.
How will your digital enterprise recognize and respond to the shift from a labor-driven and technology-enabled paradigm to a digital-driven and human-enabled model?6
To find more about this year’s Accenture Technology Vision, you can read the full text, view the accompanying videos, visit our microsite, and keep checking this blog to see more in-depth discussion of these trends.
Using Cameras and Fancy Algorithms to Track Spinning Space Junk,’ Wired, September 11, 2014.
“More AI for developers as Expect Labs releases the MindMeld API,” Gigaom, February 19, 2014.
“Accenture Life Safety Solution Named New Product of the Year,” Accenture press release, October 23, 2012
“Google Glass Helped to Enhance the Way that a Surgeon Can Perform Various Procedures,” Mobile Commerce Press, February 21, 2014.
“The Future of Computer Intelligence Is Everything but Artificial,” Wired, June 11, 2014.
“Gartner Reveals Top Predictions for IT Organizations and Users for 2015 and Beyond,” Gartner press release, October 7, 2014.