18 August 2021: While natural language processing AIs are becoming increasingly accurate in how they respond to questions, their ability to explain how they arrived at their answers has been limited. As The Doctor reveals, confronting a rogue AI in the Green Death, ‘Why?’ remains, perhaps, the hardest question for machine intelligence. IBM’s AI Horizons Network is developing a method to enable AIs to explain their reasoning with a common sense data set.1
Why it’s Important.
Today, virtual service agents, both customer facing and internal IT held-desks, are effective and very efficient FAQs. They can identify a context from natural language and then provide answers to questions, as well as provide follow up answers based on the original context. However, they cannot provide details as to how they arrived at any given answer, which generally leads to a request for human manual intervention.
Specialists who develop conversation virtual service agents, work around these limitations by programmatically refining the answers AIs have available (i.e. curating the FAQ) to include reasons. E.g. “Your transaction has been declined because of XYZ.”
IBMs work to allow AIs to report back on their reasons, may not only minimise the programming effort needed to develop virtual agents, but allow them to report decision-making in ways that organisations have not considered.
While AI development will remain a niche activity for most Australian organisations, AI will increasingly find its way into enterprise SaaS products. Natural language AIs coupled with machine learning over knowledge assets held in core enterprise systems will see a rapid increase in the use of virtual agents, both for internal and external services.
- AI specialists
- Service automation / customer experience teams
- ICT strategy leads
The rapid improvements in AI quality, coupled with their integration into most enterprise SaaS products, will make them ubiquitous for customer service delivery within the next 2-5 years.
Organisations need to start exploring the AI service agent capabilities already available in their SaaS products, and develop plans for how to leverage such capabilities. The goal should not be to deliver an ‘all-singing and dancing’ virtual agent experience, but rather to incrementally introduce capabilities over time, learning how clients and staff wish to interact, and continually leveraging advances in technology as they become available.
Related IBRS Advisory
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- BMC Adds AI to IT Operations
- Trends for 2021-2026: No new normal and preparing for the fourth-wave of ICT
- Software Agents Maturity Model
- Artificial intelligence Part 2: Deriving business principles
1. COMMONSENSEQA: A Question Answering Challenge Targeting Commonsense Knowledge, 2019 Association for Computational Linguistics