Artificial intelligence has made remarkable progress in performing tasks that were once exclusive to humans, like diagnosing diseases, language translation, and customer service. However, this has led to concerns that AI will eventually replace human workers in various industries. But this is not necessarily the case. Today, digital tools have become highly responsive to human needs, and we have become equally responsive to them. While AI will transform how we work and who does the work, it will primarily complement and augment human abilities, rather than replace them.
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While some companies have implemented AI to automate tasks, those that use it solely to replace employees will only see short-term productivity gains. Our research involving 1,500 companies showed that the most significant performance improvements occur when humans and machines work collaboratively. By combining their strengths, humans and AI can enhance each other’s complementary abilities, including leadership, teamwork, creativity, and social skills for humans, and speed, scalability, and quantitative capabilities for machines. Some tasks that come naturally to people, such as telling jokes, can be challenging for machines, while analyzing gigabytes of data, which is straightforward for machines, is virtually impossible for humans. Therefore, businesses require both human and machine capabilities to thrive.
Collaboration: The Key to Unlocking AI's Potential
To fully benefit from the power of artificial intelligence, companies must embrace collaboration between humans and machines. Five principles can guide companies towards successful integration: reimagining business processes, promoting experimentation and employee involvement, actively directing AI strategy, responsibly collecting data, and redesigning work to incorporate AI and cultivate related employee skills. In fact, a survey of 1,075 companies across 12 industries found that the more principles adopted, the better the performance of AI initiatives in terms of speed, cost savings, revenues, and other operational measures.
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To optimize this partnership, companies need to understand how humans can best augment machines, how machines can enhance human skills, and how to redesign business processes to support the collaboration. Our research and work in the field has led us to develop guidelines for companies to achieve this and put collaborative intelligence to work.
Humans Assisting Machines
Humans play three critical roles in this collaboration. They must train machines to perform certain tasks, explain outcomes (especially when they are counterintuitive or controversial), and sustain the responsible use of machines (preventing robots from harming humans, for example).
Training is essential. Machine learning algorithms must be taught how to perform the work they are designed to do. This requires huge data sets to teach machine translation apps to handle idiomatic expressions, medical apps to detect disease, and recommendation engines to support financial decision-making. AI systems must also be trained to interact with humans effectively. Although many organizations are in the early stages of filling trainer roles, leading tech companies and research groups already have mature training staff and expertise.
Microsoft’s AI assistant, Cortana, for example, required extensive training to develop the right personality, which took countless hours of attention from a team that included a poet, a novelist, and a playwright. Similarly, human trainers were needed to develop the personalities of Apple’s Siri and Amazon’s Alexa to accurately reflect their companies’ brands. For example, Siri has just the right amount of sassiness, as expected from Apple’s brand.
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Artificial intelligence (AI) is now being trained to display more complex and subtle human traits such as sympathy. The MIT Media Lab offshoot, Koko, has developed technology to help AI assistants seem to commiserate with users. For example, if a user is having a bad day, Koko’s system doesn’t reply with a canned response such as “I’m sorry to hear that.” Instead, it may ask for more information and offer advice to help the person see their issues in a different light.
As AI increasingly reaches conclusions through opaque processes, human experts are needed to explain their behavior to non-expert users. These “explainers” are particularly important in evidence-based industries such as law and medicine. Similarly, AI systems require “sustainers” who work to ensure that they function properly, safely, and responsibly.
Various experts, sometimes referred to as safety engineers, focus on preventing harm by AI. They ensure that industrial robots working alongside humans recognize humans nearby and do not endanger them. If AI causes harm, they may review analysis from explainers. Other groups of sustainers ensure that AI systems uphold ethical norms, such as data compliance officers who ensure that data feeding AI systems comply with consumer-protection regulations like the GDPR. The aim is to improve the user experience while protecting individual privacy.
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AI can boost analytic and decision-making abilities and heighten creativity. However, AI needs human trainers to teach it how to perform specific tasks, explain AI outcomes to non-expert users, and sustain responsible use by ensuring that AI systems function properly, safely, and ethically.
How machines are assisting humans
Smart machines are revolutionizing the way humans work by amplifying our cognitive strengths, interacting with customers and employees to free us for higher-level tasks, and embodying human skills to extend our physical capabilities.
- Amplifying:
Artificial intelligence can enhance our analytical and decision-making abilities by providing relevant information at the right time. Moreover, AI can also foster creativity. For instance, Autodesk’s Dreamcatcher AI provides designers with thousands of designs that match their criteria, often sparking new ideas that the designer might not have initially considered. This frees the designer to focus on deploying their professional judgment and aesthetic sensibilities.
- Interacting:
Collaboration between humans and machines has enabled companies to interact with employees and customers more effectively. AI agents, like Cortana, can facilitate communication between people or on behalf of people. They can provide routine customer service to large numbers of people simultaneously and handle natural-language conversations. For example, SEB, a major Swedish bank, uses a virtual assistant called Aida to interact with millions of customers. Aida has access to vast stores of data and can answer frequently asked questions, ask follow-up questions, and analyze a caller’s tone of voice to provide better service.
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- Embodying:
In many applications, AI is embodied in a robot that augments a human worker. With their sophisticated sensors, motors, and actuators, AI-enabled machines can recognize people and objects and work safely alongside humans in factories, warehouses, and laboratories. In manufacturing, for instance, robots are evolving into context-aware “cobots” that can handle repetitive actions that require heavy lifting, while humans perform tasks that require dexterity and judgment. Hyundai is extending the cobot concept with exoskeletons, which are wearable robotic devices that adapt to the user and location in real-time, enabling industrial workers to perform their jobs with superhuman endurance and strength.
Conclusion
Currently, many human-machine interactions require individuals to learn new skills and to approach tasks in novel ways (such as training a chatbot and utilizing it to enhance customer service). However, only a limited number of companies have taken steps to revamp their business processes and fully optimize the power of collaborative intelligence. It is evident that organizations that view machines solely as a means of replacing human labor through automation will fail to capitalize on the true potential of AI. This approach is fundamentally flawed. The leaders of tomorrow will be those who embrace collaborative intelligence and revolutionize their operations, markets, industries, and, importantly, their workforce.
