Finding The Balance Between Intelligent Machines And Talented Humans

While technology evolves, there's a sound of the unavoidable warship between the automation of jobs and interactive humans. As some people trust technology will be replacing an average human worker, the obvious outcome is probably not as simple as this since human interactions remain superior in a number of facets. Such of these instances is the field of customer service. Identifying the right balance of human/digital service to increase the effect of the customer experience remains an open question for businesses.

Technology Integrate Into The Customer Experience For Initiating Humans

Technology facilitates everyday life experiences as humans - in places of work, play, learning, and connecting. The chances fostered through technologies of artificial intelligence, augmented reality or cloud computing gives an instigating range of options for businesses to leverage. In the world of customer experience, technology grants customers to engage and interact with organizations in new ways. As e-commerce and online retail stores are on the increasing side, technology is also offering new ways for offline stores to connect with customers. As businesses engage in personalization at scale through new technology, consumers can enjoy unique and satisfying customer experiences that speak to them. But, while technology allows companies to provide rapid, convenient service, customers ultimately demand human connections. According to a PwC Consumer Intelligence Series survey, it was found that 75 per cent of shoppers desire more human interaction in the future. This marks the importance of the human touch in providing an authentic customer experience for consumers. When adopting new technologies, businesses should consider if they are seamless and frictionless for customers and employees. While it is important to stay notches ahead of the curve, avoiding the use of automation for its own sake will help companies create the most meaningful customer experiences.

Humans Assisting Machines

Humans need to execute three crucial roles. They must assist machines with training for performing certain tasks; explaining the outcomes of those tasks, most of the time when the results are counterintuitive or controversial. Sustaining the responsible use of machines such as the prevention of robots from harming humans.

Training

Machine-learning algorithms must be provided with codes on how to perform the work they’re designed to do. In that code, huge training data sets are amalgamated to teach machine-translation apps for handling idiomatic expressions, medical applications for the detection of diseases, and recommendation engines for supporting financial decision-making. In addition, AI systems must be coded on how best to interact with humans. While organizations in different sectors are now in the primitive stages of filling trainer roles, leading tech companies and research groups are filled with mature training staff and expertise.

Key Findings •

The age of humans + intelligent machines has truly reached. Eighty-two per cent of respondents cited intelligent machines as the number one effect on the work future in the next five years. Companies state that 70 per cent of their workforce will be prepared for working with intelligent machines during the same period.

• The intelligent machines economics is an unstoppable force. Intelligent machines are expected to propel revenue growth while gathering costs down. Leaders are bullish on unlocking new performance thresholds, with expectations for a 20 per cent increase in workforce productivity in the following five years.

• The message is loud and clear: Invest or be left behind. On average, companies plan to spend 13.5 per cent of their revenue on developing and managing intelligent machines in the next five years. The more you invest, the more you make.

• Preparation for change is crucial. Only 35 per cent of the organizations we surveyed feel fully prepared to handle working with intelligent machines, and only 42 per cent are confident about their ability to integrate AI with existing business processes. The foremost three challenges are misalignment of workforce strategy with business goals (72 per cent), lack of IT infrastructure readiness (71 per cent) and a shortage of required talent and knowledge (70 per cent).

Balance

As AIs ensure their reachable conclusions through processes that are opaque, which are known as the so-called black-box problem, they require human experts in the field to the explanation of their behaviour to non-expert users. These are called ‘Explainers’ particularly important in evidence-based industries, such as law and medicine, where a practitioner needs to understand how an AI weighed inputs into sentencing and medical recommendation. Explainers are equally important in helping insurers and law enforcement understand why an autonomous car took actions that led to an accident or in words - failed to avoid one. And explainers are developing as integral in regulated industries—indeed, in any consumer-facing industry where a machine’s output could be challenged as unfair, illegal, or just plain wrong. For example, the European Union’s new General Data Protection Regulation (GDPR) empowers consumers with the right to receive an explanation for any algorithm-based decision, such as the rate offered on a credit card or mortgage.