Currently, computational capacity is doubling roughly every 18 months. The pace of this development, amplified by rapid improvements in software, has resulted in artificial intelligence (AI) and advanced algorithms that are quickly evolving to understand and interpret some of our most complex natural processes.
At the same time, the ability to access this capacity is multiplying due to sharp increases in bandwidth, improvements in latency and other quality of service parameters with technologies such as 5G. Interfaces are also becoming more seamless due to advances in cloud computing as well as visual, tactile, and verbal interface technologies.
These exponential improvements have brought what, just over a decade ago, were considered industrial-strength processing and communication capabilities into the homes and hands of individuals everywhere. As industries adopt these technologies to modernize and automate their business processes to increase value chain efficiency and effectiveness, a new service-based concept for the technology has emerged. The self-driving or autonomous car is an example of this new concept. Eventually cars will no longer have drivers, a fundamental change in the concept of a car. The passenger of such a vehicle will interact with it on a much higher and abstract level as a service. When we apply this concept to the telecom sector, i.e. creating a “self-driving network”, AI technology will be the brains behind this change. This presents two main challenges for those developing the concept and service:
- The conceptual shift from today’s understanding of what a network is, becoming something more abstract than what it is today, operating on new parameters.
- The fact that a user of such a service will interact with the system on a much higher, more abstract level.
Therefore, the understanding of the business goals and the user of the system is key to success. With the role of users shifting from drivers to passengers and from operators to managers, designers will need to create highly collaborative solutions allowing tangible and reliable interaction between AI technology and the user.
In light of this, the Experience Design team at Ericsson has been researching and developing how to design trustworthy, AI-powered services for telecom operators. Through designing the Cognitive Operation Support System service concept, we have identified four components of human trust that can be applied to AI powered systems. These four pillars – competence, benevolence, integrity and charisma – are the key areas designers and business owners need to address to be successful when it comes to the adoption of AI.