Artificial intelligence and thinking computers are a prominent plot device for Hollywood. Movies such as with 2001 Space Odyssey, Alien, and Terminator, come to mind. Let alone current day examples, such as I Robot, Ex Machina, and Transcendence.
These pop culture examples underscore the fears and challenges we face as we attempt to program natural behavior and interact with intelligent technology. I think about this whenever I read the growing list of examples of how bots are becoming more pervasive.
The truth is that it’s very hard to teach a computer to think and process nuanced information, but smart bots that can personalise interaction are key for brands to successfully leverage artificial intelligence.
For those of you just coming up to speed, a bot is a software application, which runs automated Internet scripts that gather, analyse, and file information. One of the earliest bots, created in 1997, was created to track stock market trends and supposedly could predict future events through keyword analysis. Today, these automated bots are being created for a myriad of uses by some of the largest companies on the planet.
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But, current day examples, such as CNN’s news bots or HP’s printing bot, are simplistic examples, and are not much more than glorified alerts and simple data and platform integrations. The goal of these efforts is to create applications that can solve problems of much deeper complexity, and that resonate with users on a more personal level.
The biggest challenge in building an effective bot is to solve the issue of personalisation. The bot has to know and understand you (who you are and what you want) in order to process and retrieve things the way you want it. This means understanding your needs and expectations in all their complexity so that your experience is both satisfying and delightful.
The most meaningful bot activities happen when they help us solve for complex decisions rather than a simple search string. Solving these problems requires a bot to know you and your situation: like a trusted personal assistant who anticipates and makes initial decisions on your behalf, and knows the types of answers or information you are looking for.
How does a real personal assistant learn these things? They interact with you, they watch what you like and don’t like, and take your feedback and apply it through an aggregate knowledge base that grows more nuanced over time.
Eventually, bots will also learn enough to make complex and interconnected decisions involving a wide range of variables: revealing the true promise and potential for bot technology.
But these things will never come to fruition until we solve the challenge of giving these bots the appropriate data so they can learn who we are and what we like. Yes, bots can correlate initial data such as my geo location, initial profile data such as gender and address, and then cross-check and crowd-source data to make assumptions based on 'people like me.'
But these approaches will not be as accurate as most of us would like. This is all the more challenging given the aforementioned media-inspired paranoia and distrust around artificial computing and computer-based personas. We need so solve this on an emotional level, as well as technical and logistical.
The companies that are solving for personalisation are going to be the leaders in creating meaningful bots, because personal knowledge allows the bot to be more intuitive and insightful.
As a result, companies need to look for ways to drive repeat engagement, whether it’s frequent purchases and search queries, surveys that reveal deeper insights, or the creation of groups and communities that aggregate people with common attributes and desires, which will allow crowd-based learning.
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At the heart of all of this is the need to create a construct that people want to use. People need to understand bots and engage with them, repeatedly, over time. No matter how intuitive your system is, the real benefits of bot personalisation unfold over time.
You may hire a savvy personal assistant, but they will be exponentially more effective after working with you for a year than they will on day one. And getting this long term traction requires a brilliant experience that meets the core needs of users.
As their relationship with their bot deepens, customers need to feel comfortable sharing their personal preferences, not be shocked or suspicious when it proves to be insightful, and be willing to build a relationship with the interface, the brand, and the technology.
Does this sound familiar? For most CMOs, this is exactly the kind of dynamic they want to establish between their audience and their brand. On a broad level, the bot becomes an extension of the brand, perhaps even the face of the brand. Don’t believe me? Consider the chaos and brand implications of the failed Microsoft TAY chatbot system.
Sourced from Daniel Giordan, Digital Practice Partner, Wipro Digital