Affective computing will transform the customer experience and the capabilities of AI

Key Takeaways

The rise of affective computing and emotion AI is set to revolutionize human-machine interactions by enabling devices to understand and respond to human emotions, enhancing user experience.

Companies will face both opportunities and challenges in the ethical implementation of affective AI, necessitating careful consideration of data collection, user consent, and potential biases in technology.

As consumers become more accustomed to digital experiences, organizations must prioritize the ethical and effective adoption of technologies that leverage emotional data to improve customer interactions and satisfaction.

As our reliance on technology grows, devices are evolving to understand human emotions and offer a more personalised experience. The evolution of these platforms will hold benefits for customers, employees, clients and suppliers as technology will have the power to interact and behave in a more human way.

As our use of technology continues to grow, ai will be fundamental in ensuring that devices and platforms are able to respond to humans

The impact of the COVID-19 lockdown has changed many aspects of how we live our day-to-day lives. With large numbers of us now having worked at home for many weeks under lockdown, technology has become instrumental in helping us find new ways of connecting with our colleagues, our clients, our friends and our families. Further down the list, but arguably no less important, is the way that technology has allowed us to continue to receive the goods and services we rely on. Whether that’s booking a delivery slot or setting-up new subscriptions, I’ve become used to having a full digital experience throughout the process and expect that many of us will be more comfortable using these digital tools once we have come through the lockdown.

As our use of technology continues to grow, AI will be fundamental in ensuring that devices and platforms are able to respond to humans in a more personal way. Taking cars as an example, microphones and cameras embedded within vehicles may monitor cars’ movements as well as the driver’s voice and facial expressions which could then be analysed using a mixture of computer vision, voice recognition and deep learning. On a long car journey for instance, these inputs could determine whether the driver is getting tired and distracted and if so, lower the temperature and turn up the volume on the radio, with a conversational agent suggesting the closest location to stop for a coffee.

Making ‘affective computing’ effective

The development of these technologies that can detect physical and emotional states mark the next stage of human-machine interaction and are known as ‘affective computing’ or ‘emotion AI’. They have the potential to redefine how we interact with technology in myriad ways. Restaurant chains could tailor menus automatically depending on changes in the weather, apps may design custom products depending on the emotional reaction of the users, or AI-powered bots could offer personal customer interactions in retail environments. 

The ability to use emotionally intelligent platforms to identify and use emotional data at scale will be one of the most important opportunities for companies in the next 12 to 18 months, according to Deloitte’s 2020 Tech Trends report. The challenge in the development of these platforms will be to determine which responses and behaviours will resonate with a diverse group of users, and then develop a combination of affective and AI technology to deliver the appropriate reactions and experiences. 

In order to prepare for this, a growing number of companies are researching human empathy and looking at how to incorporate these insights into new technologies. Included in this are teams looking at neuroscientific research, human-centred design and, most importantly, how to roll out this technology while removing bias and emphasising values and ethics in its use.

Once developed, affective AI will be revolutionary for many businesses. Today many businesses have built data banks containing functional information such as the age, demographic and past transactions of their customers, allowing them to predict future demand for their services. Once the technology is further developed, they will be more responsive to the thoughts and feelings of their customers, and whether they are having a positive or negative customer experience.

Once the technology is further developed, they will be more responsive to the thoughts and feelings of their customers

For instance looking at automated calls, today businesses are able to see the transcripts for these calls and understand why their customer is getting in touch. We are already seeing automated calls having voice-recognition technology built-in to detect the emotions of the caller and to determine whether they have been agitated by the call or appreciative of the advice that has been offered. This helps to fine-tune interactions and direct callers to additional products or services if they appear receptive to the recommendations. Other solutions could be developed to understand body language of customers as they interact with people in-store, or at live entertainment venues, in order to understand the customer experience.

Ensure ‘affective computing’ is ethically adopted is of paramount importance

The growing popularity of technologies such as wearables, facial recognition and the ubiquitous use of smartphones will provide companies with the ability to collect this data. However, companies will need to think extremely carefully about the ethical use of these technologies and the data that it will have the ability to collect. For instance, in the call centre scenario it would be highly unethical for the technology to identify a vulnerable caller that would be more likely to buy additional services. 

Similarly, customers must be savvy to the data that is being collected, how it’s being used and the benefits they are receiving as a result of passing over their data. Up until now, many people have been reluctant to give away their financial data. It will be challenging to entice consumers to provide insight into their emotional states without a significant demonstration of benefits they will receive as a result. 

Technologies to make affective computing effective are already available in the form of wearables, sophisticated vision technologies such as facial recognition and voice recognition tools. Devices which track neuronal activity are also in development. The key now will be to ensure the ethical use of affective computing, and begin to communicate with consumers on the merits of its use. For companies, identifying the business challenges that affective AI will address and mapping how this will benefit customers should be a priority to ensure its future rollout is carefully considered and ethically implemented.