Government chatbots: five steps to getting it right
By Dan Kuenzig
Thursday, 05 April, 2018
In a world where digital consumer experiences represent the norm, citizens have become accustomed to the simplification of everyday transactions using smartphones and tablets. These innovative ‘self-service’ technologies have set a high benchmark for citizen expectations. Anything short of meeting this bar will risk leaving people with a negative experience.
Conversational user experiences (UX), powered by artificial intelligence (AI), provide an opportunity for government agencies to offer modern citizen engagement tools on par with the best commercial experiences — but they have to get the basics right. With that in mind, here is a five-step guide to help government IT professionals and agency program managers kick off their initiatives to use virtual personal assistants, often called ‘chatbots’.
1. Select your conversational user experiences wisely
Make sure you pick a ‘conversational’ UX platform that can fully support cross-channel consistency by leveraging enterprise knowledge management. This will help end users get the same information from chatbots as they do from more traditional channels like web and mobile.
2. Ensure your public chatbots can handle complex conversations
Agencies need to consider an enterprise approach to support complex conversations to best achieve cross-channel consistency across the web, mobile and call-centre agents. To be useful, chatbots need to access knowledge repositories (eg, where to file taxes) and take personal actions on behalf of citizens (eg, calculating social security benefits). If they can’t help citizens address their day-to-day concerns, they will be underutilised and become obsolete.
3. Make sure your chatbot is smart and can explain itself
In his MIT Technology Review article, senior editor Will Knight addresses the limitations of AI in formulating conclusions. He says that “… starting in the summer of 2018, the European Union may require that companies be able to give users an explanation for decisions that automated systems reach.”
Agencies need to be prepared and choose a chatbot platform that can easily explain its decisions in clear and understandable language. Over time, that will help increase public adoption and trust in the technology.
4. Choose a vendor-neutral architecture
I recently attended an AI hackathon in Washington, DC, and was surprised to see the number of agencies building chatbots for single vendors, such as Facebook Messenger or Amazon Echo. They were using vendor APIs directly, rather than a product that supports multiple vendors.
These developers were failing to remember the lessons from the mobile paradigm shift a decade ago. BlackBerry once owned close to 50% of the smartphone market in the United States. Want to guess their market share today?
Government agencies shouldn’t pick winners and losers in this market, but instead invest in chatbot vendors that support a write-once, deploy many deployment model (eg, the Echo, Facebook Messenger, WeChat, etc).
5. Don’t plan for failure
Like the early days of mobile app development, there are a lot of chatbot prototypes that quickly fail. According to Facebook, 70% of chatbots are considered a failure. There are many reasons for their lack of success, but here are a few additional thoughts to consider before you begin developing so your chatbot works like a pro from the start:
- Does our platform support rapid agility for creating and refining conversational user experiences?
- Does our platform enable the business to not only design simple conversations but also complex and meaningful conversations?
- Who will be the voice of our chatbots?
- Are we incorporating the right use case(s) for our chatbots?
- Does our chatbot architecture include controls to continuously monitor and quickly refine?
- Will our chatbots allow citizens to seamlessly escalate to a human?
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