Challenges and Opportunities in the AI User Interface

While the general integration of artificial intelligence into business processes is likely to have a profound effect, one area common to all applications will be particularly impacted–the User Interface (UI). We have already seen the beginning of  AI in digital assistants such as Alexa (see Digital Assistants Coming of Age with Alexa) that interpret natural language commands and respond with speech or actions. While this type of Conversational Interface (CI) is likely to become ubiquitous, there are other significant UI impacts that may be at least as important.

Today, capabilities of applications have grown geometrically and complexity continues to increase. Meanwhile, mobile platforms have limited display space and fewer controls. This leads to a new need for simplification. The choices presented to the user in menu upon menu within office products, for example can be exhaustive and make it difficult to locate specific actions. Yet there is great demand for additional processing to meet the needs of new use cases.

AI to the Rescue 

Natural language processing provides a start for simplifying access to the deeper complexities of programs by understanding commands and responding without a keyboard. But the conversational interface is also evolving as AI progresses. We are still at a rudimentary stage, returning to the need to memorize commands like the old TTY interfaces. What is needed is to address the selection of actions based upon context. This is the beginning of a new form of interface in which AI is able to translate a human request for a desired result into a command sequence to one or more applications to perform tasks that will meet the user’s ultimate goal.

An AI User Interface

For example, someone might ask “Should I go to the office today?”. The system might then assess health information, determine if there is an illness; check the weather for extremes; check databases of current natural disasters that might be applicable; check holiday schedules; check company instructions and so forth, all in an instant. But to do this, the AI needs a broader range of knowledge and data than is commonly available for current AI applications, and a capacity to understand what such a request might entail. In fact, as with many such puzzles, there is the beginnings of a requirement for an artificial general intelligence which would think across a wide range of territory rather than within the simple parameters of a question. The AI would think about thinking.

Such an interface demands situational awareness and an understanding of the overall context in which a question is posed. The AI needs to define the specifics of where information would be found; it also needs to understand how to convey and/or act upon that intelligence, and make complex choices.

Implications of an AI UI

As software continues to grow in  complexity, it is certain that AI will provide a bridging interface between human and machine. This interface will become more flexible and more powerful, and it will evolve to perform more duties. Just as simplification of the UI makes it possible to perform complex tasks on the computer with only a basic understanding of operating principles, people will begin to interact with computers in a conversational way and evolve information requests to meet an increasingly sophisticated interaction. The growing sophistication of this interaction and will feed the development of further AI UI capabilities.

Development of a sophisticated AI-based UI is not solely about natural language processing, however. All computer interactions can likely be improved by the addition of an AI layer. While conversation is a priority, AI will be able to  to reduce the clutter and confusion of menu-based interactions by providing selection based upon context, and capability to interact based on desired results rather than tool selection. In effect, this is much like movements in  software development, such as the growing Agile and DevOps movements. Writing software to meet specific customer needs is much better than coding based around technology. This same rule must apply to the actions of programs themselves.

Into the Future

AI will also be applied to the processes of developing artificial intelligence. We have already seen programs that read a user interface screen image and convert it directly into code. In the next iteration, we can expect to see AI solutions which turn actions into instructions which may feed multiple AI systems to further a desired operation. While such a general intelligence creates its own issues, it will arrived in incremental steps. Increasing complexity of AI routines, increasing integration, and increasing componentization will open the way for AI to operate across a broader range of data and make decisions about thinking and about interaction that can generally be applied across all computer systems.


 


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