Distraction theory: how advances in AI will help workers to be more focused

Distraction theory: how advances in AI will help workers to be more focused

AI Business

February 17, 2020

5 Min Read

by James Bulpin, Citrix 17 February 2020

During an average day, we get distracted and forced to switch context between apps, email and messaging channels more than 400 times. This means that approximately every 40 seconds, our attention at work is being disrupted.

This constant fragmentation of our time and concentration has become the new normal, and while many workers have adapted willingly to the situation, the bigger picture is that it is eroding our ability to maintain focus on a task and be productive. Some research has gone so far as to suggest it is having a detrimental impact on our IQ and brain cells.

This ‘continuous partial attention’ (CPA), a phrase coined
by ex-Apple and Microsoft consultant Linda Stone, means the average employee is
in a constant state of alertness, unable to give complete focus to anything. This
is unsustainable and as employee experience rises to be a c-level priority,
businesses need to be seeking a solution. Increasingly it seems the answer may
lie in Artificial Intelligence (AI) and machine learning (ML). Curious to
discover more, we’re working hard to build immersive demonstrations and
scenarios, to evaluate how technology might enable workers to regain their
focus and concentration in the future.

Technology needs to be task-focused

A McKinsey
Global Institute study suggests workers spend nearly 20 per cent of their
time looking for information internally or tracking down colleagues. This is
often because various apps and systems don’t talk to each other either,
creating much unnecessary, manual work. This means that workflows are very
often driven by the needs of the application, or the constraints of the system,
rather than by what works best for the business or the employee.

Today's IT experience therefore is very application-centric, but technology arguably needs to focus more on the task or outcome that the user is trying to achieve. As AI and ML capabilities mature, micro apps and other intelligent features will become better integrated at a task-based level, enabling the worker to focus on the job in hand. These intelligent systems will be able to organize a vast array of micro-functionality in a way that gives the user exactly what they need, at the time they need it.

Creating a personalized recommendation experience

In our personal lives, we are used to recommendation systems
being used to great effect in online consumer retail and digital entertainment
services, and if we could apply those same concepts to an enterprise work
environment, it could significantly help with focus.

We recently showcased a high street bank concept to show how AI-driven task and workload management could help employees in many different types of roles and industries, who all have an ever-present set of background activities, but need to be able to put them to one side when clear focus on a foreground task is required. In the bank scenario, the branch manager was able to introduce an automated workflow, incorporating workspace intelligence and micro apps, so that when a high-value customer entered the bank, that individual could immediately be prioritized with all relevant information, forms, ID checks and financial specialists made immediately available through a single user interface, in just one click.

Creating access to several types of tools

People like to work in different ways, and the rise of
intuitive, no-code workflow and automation tools will enable business owners
and individual employees to build their own experiences that match the way they
want to work. AI technology, or virtual assistants, will learn from what users
do manually and recommend, or even automatically create, workflows, thus
removing unnecessary distractions from their day.

In the era of context-driven AI, offering a choice of tools and
APIs is important. I like to compare this to Lego, whereby and individual can
start with a pre-built model that works in the common case, but add parts,
remove parts, and change it as much as they like to adapt it to their desired
state - the bigger the range of building bricks, doors, wheels, axles and
propellers, that all fit together in a variety of ways, the more imaginative
and bespoke the final creation can be.

Creating focus

It is common for workers to confuse importance with urgency,
which can lead to overload and a lack of focus. In the bank example, providing
a response to a customer request for a sales quote may be important, but if a
high-value customer enters the branch, they immediately become the most urgent

Systems of engagement will increasingly need to perform intelligent filtering and prioritization, showing a user only what they need at the time they need it, deferring other notifications and tasks as necessary. Once we reach the point when systems can intelligently decide what, and what not, to put in front of a user, ‘continuous partial attention’ could potentially become a phenomenon of the past. With time, knowledge workers will be enabled to retrain their brain to focus for longer periods of time, on creative projects or cognitive work, without distraction. It goes without saying this will have a tremendous impact on business productivity in the future.

James Bulpin is Senior Director of Engineering at Citrix

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