Creating autonomous agents for customer service that are capable and humanistic requires specialized cognitive models. These models need to be designed to exhibit certain key traits and capabilities:
Empathy and Emotional Intelligence: The AI needs to sense emotions and sentiment from cues like facial expressions, tone of voice and language. It should then demonstrate understanding and adapt its responses accordingly to resolve issues and build rapport. Architectures like neural networks offer promise for modeling emotional intelligence.
Dynamic Conversation: Scripted responses are limited, while the ability to converse flexibly shows understanding and care. Natural language processing has progressed enough to enable basic chatbots, but more work is needed to instill nuance. Conversation models should incorporate empathy, logic, personality and variability.
Ethics and Company Values: It is crucial that the AI's actions and recommendations align with ethical business practices as well as company values like sustainability and inclusion. This requires instantiating parameters and constraints at the architecture level rather than just training data. Integrating ethics into the cognitive model itself enables responsible AI.
Transparency: Black box AI can lead to harmful unintended consequences. Models should be interpretable, with clear explanations of the reasoning behind AI assistant actions. Explainability helps ensure appropriate recommendations and built trust through transparency.
Knowledge Representation: To quickly respond to customer needs, the AI needs broad access to information on company products, policies, previous interactions and more. Knowledge graphs and semantic ontologies can potentially enable robust information retrieval and synthesis.
Continuous Improvement: As customer needs and the competitive landscape evolve, so models must be continually updated and refined. It is essential that improvement methods are safe and controlled. Techniques like reinforcement learning may be valuable with strong governance.
Perceptible is focused on autonomous agents that are perceptive, prescient and compassionate. When we think of autonomous agents for customer service, we start with cognitive models that support business success but also broader communal goals.
