AI technology needs a dose of empathy
As AI becomes interwoven into our lives through smart speakers or IoT devices, the potential to gauge customer sentiments and emotional signals from the emerging data is an untapped opportunity
In Star Wars, C-3PO, a humanoid, is devastated to hear the news of the ‘death’ of R2-D2, its fellow humanoid comrade. As R2 is taken away to be repaired, C-3PO exclaims, “You've got to come back. You wouldn't want my life to be boring, would you?”
It’s notable that in the year 1977, director George Lucas envisioned artificial intelligence with a high emotional quotient. Today, we are still pondering the prospect of “machines with emotions”. Can technology evolve to catalyse human agency with automated decisions that are warmer and “empathetic”?
Today, we are more 'connected' than ever and have an array of channels to communicate. However, there is still a void. The ever-evolving technology around us doesn’t exhibit any emotional traits. After all, the software follows instructions, even if it means bombarding your phone repeatedly with notifications.
Although we have seen intermittent progress to enable human-like qualities in technology, such as Duplex mimicking human conversations, we have just started this journey. As AI becomes interwoven into our lives through smart speakers or IoT devices, the potential to gauge customer sentiments and emotional signals from the emerging data is an untapped opportunity. Data analysis and AI application can help make interactions compassionate—for example, only sending offers that the customer might want and is able to afford. AI will guide enterprises towards the next best action in every customer situation, which sometimes might actually be not taking any action at all.
Apart from customer service, marketing and sales functions can also benefit from intelligent empathy. Through AI technology that seamlessly connects these functions, organisations can now operationalise empathy at scale. This can be done by categorising various elements of empathy into customer objects and business objectives towards ensuring a mutually beneficial relationship between the two sides:
- Intent: Have we considered all the reasons behind a customer’s request?
- Mood: Is the current customer’s frame of mind ideal for selling?
- Context: Can historic data or current environment signals show us how to improve the conversation?
- Relevance: Does the offer match the customer’s current interests?
- Suitability: Is the offer appropriate for the customer, including their current financial situation?
- Value: Can it drive value for the customer and benefit the business as well?
- Risk: Are the recommended offers compliant with existing regulations & ethics?
Customers must be assured that organisations aren’t trading purpose for profit. These are testing times for the business world, and it’s time AI innovation fights back to win customer’s hearts again.
The writer is MD of Pegasystems India.