Collaborative Intelligence: Human and Machines are forming a League

Collaborative Intelligence: Human and Machines are forming a League

Electricity is the greatest invention in history because it opened people up to a whole new world. In this information epoch, Artificial Intelligence is doing the same, i.e. adding light to the world and creating solutions to the most modern problems of the world. There is a reasonable fear that AI (so-called an immortal dictator from which we can never escape) will ultimately replace the human workforce from the economy, but it is inevitable, at least till we’re the masters.

It’s researched that firms achieve the most significant performance improvements when humans and machines work together. Through collaborative intelligence, we disrupt cognition, productivity, efficiency, customer satisfaction and so on. A machine can not possess a great sense of humour just as a human can not crunch gigabytes of data, business needs the consortium of both’s capabilities.

Human Augmenting Machines


Even a human can not learn everything when s/he comes into existence. Same manner,  a machine learning program espouses the myriad of training data to perform the work they’re designed to do. A robust AI design should consist of training of ethical behaviour towards work along with the workforce.

Consider Microsoft’s AI assistant, Cortana. The bot required extensive training to develop just the right personality: confident, caring, and helpful but not bossy. Apple’s Siri is trained to permeate the company’s vision and the sassiness when she talks to the user.

AI assistants are now being trained to display even more complex and subtle human traits, such as sympathy. Ranchi man Ranjit Srivastava, 38, has developed an Indian version of ‘Sophia,’ a social humanoid robot developed by a Hong Kong-based company, named Rashmi which can speak Hindi, Bhojpuri and Marathi along with English. Rashmi can analyse the conversation to extract the response and help to commiserate. She can work as a bank receptionist, helper, a friend of lonely people and others.


Though a machine can learn ‘How’, but not the ‘Why’. A machine can not explain its course of action for what it is responsible for. Hence, Human Explainer poses the ‘Why’ part of the machine. These “explainers” are particularly important in evidence-based industries, such as law and medicine, where a practitioner needs to understand how an AI weighted inputs into, say, a sentencing or medical recommendation. Explainers are similarly important in helping insurers and law enforcement understand why an autonomous car took actions that led to an accident—or failed to avoid one.

Machines Augmenting Human


AI has revolutionized the cognitive ability of human either it is analytics or decision making. There are lots of ‘Data’ around us that contains very useful information especially regarding consumer based industry, and it is not feasible for us to extract that information.

Amazon’s biggest breakthroughs have been to show you can use big data as a service, and you can also use big data to personalize your offerings with agility to millions of people.

Tools like Autodesk Dreamcatcher are even more impressive. By applying algorithms to any set of parameters, the app produces numerous iterations of a design, allowing designers to choose the best one for recombination.


Human and Machines are also joining the force to interact with their employees and customers to interact with them in the most efficient manner. SBI, a leading PSB of India, has launched an artificial intelligence (AI)-powered chat assistant SIA for State Bank of India (SBI) to address customer enquiries. SIA can enhance the grievance mechanism and simplifying the customer’s lives on multiple customer interaction platforms.

In order to get the most out of this collaboration, businesses need to redesign their operations, i.e. identifying the area which has to be improved, deploying the AI assistance to the human workforce. AI can be envisioned as the ‘Catalyst’ in an emerging economy, where sustainability will be subjected to a ‘Robust Collaborative Intelligence’.

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