It was many years ago when former Canadian prime minister Pierre Elliot Trudeau spoke these prophetic words: “The many techniques of cybernetics, by transforming our control over data and information, may transform our whole society. With this knowledge we are wide awake, alert, capable of action: No longer are we blind, inert pawns of fate.”
Full of optimism, Trudeau wrote these lines years before any computer system achieved the level of sophistication required to beat a chess grandmaster (1997), a Jeopardy champion (2011) or drive a car autonomously (in the 2000s).
In this reflection, technology empowers humans to take action — a welcome contrast to the techno-dystopia common in
Today, with digital assistants in smartphones and robo-advisors, it is more common to have systems with human-like intelligence helping people to accomplish tasks or make decisions.
These systems — also known as “cognitive” — differ from typical programmable systems that most people use in their professional and daily lives (such as computers and software).
A programmable system follows a set of instructions; a cognitive system learns, infers and generates hypotheses. It can deal with uncertainty and unstructured data, and it can learn from its environment and its users.
Think about when IBM’s super computer Watson played Jeopardy: It was not looking online to find answers to questions asked in natural languages, it was generating different potential answers and then selecting the more probable ones, similar to our own thinking when we face new problems and can’t rely on simple, rule-based reasoning.
The potential for cognitive systems is endless. Many tedious tasks, complex activities and impossible decisions can be simplified with advanced computing capabilities. A computer such as Watson can help chefs to generate new recipes, based on millions of cookbooks, and help human psychophysics or researchers to develop new cancer treatments, based on thousands of research papers.
But how will these capabilities transform the workplace? Here are four directions to consider:
Because they can process large quantities of structured and unstructured data about individuals, cognitive systems can interact with users based on the mode, form and quality each employee prefers.
Think about employees’ digital footprints and data records — their online activities, system use, internal social media conversations, geolocation, transaction history, wearable data, performance data, psychometric assessments and learning history can all be assembled to provide a unique interaction between a system and human.
Artificial human resource assistants will sense a tone in an interaction, a sentiment in an email, an emotional state in an online conversation and be able to better advise employees and weather their anger or capitalize on their enthusiasm.
Talking with a machine will feel much more natural.
Scaled, elevated expertise
Nowadays, nobody can keep up with the pace of knowledge growth: 1.9 million scientific articles are published each year, according to the International Association of Scientific, Technical and Medical Publisher.
And, every year, close to 600,000 patents are filed with the United States patent office only. There are now more blogs, books, articles and newspapers accessible than ever before.
Employers are also losing expertise as older workers are starting to retire, depriving organizations of years of accumulated knowledge.
To help organizations enhance the employee expertise, cognitive computing systems can become artificial companions that quickly digest large amounts of information for human users and act as an extension of their reasoning ability.
This helps employees to acquire expertise faster. And since these systems can be taught by experts in one field (whether it’s engineering or customer service), expert knowledge is then available to a broader population.
Cognition infused in tools, products and services
With cars, medical devices, appliances and even toys enhanced through cognition, we can envision how the Internet of Things will impact the workplace. Solutions will learn and understand worker behaviour and suggest complex actions and responses that users can approve by voice or simple mobile input.
What if calendars can talk to each other and decide when people should be having a meeting (or if they need to be in that meeting at all, given the stakeholders involved)?
Or what if a digital assistant can recommend which experts might be able to help solve a problem by inferring expertise from a colleague’s activity?
By infusing the tools employees use (such as email, social, mobile and content management) with cognitive capability, employees can dedicate their mental resources (attention and effort) to activities that matter, and let the never-tired, unbiased artificial “minds” surface only relevant information.
Just like cognitive systems can recommend chef pairings of food that are both unexpected and tasty, they will be able to recommend which team members should work together for maximum impacts, based on their expertise, experience, personality, compatibility or the goal of a project.
Enhanced exploration, discovery
What everyone wants from data are insights — relationships that are true and relevant. Rather than testing it, we would rather have a smarter system guiding us in the exploration and easily showing us true patterns that matter.
Rather than using brute-force analyses (looking at all the possible correlation in a data set) or learning the complexities of statistical software, cognitive computing can simplify analytics by helping professionals to explore data visually, try different combinations and relationships, and conduct predictive analytics in a few clicks.
Exploring data or knowledge with a cognitive system becomes a conversation with the content, a natural exploration similar to a stream of consciousness. This helps organizations anticipate internal and external trends before they have an impact.
These scenarios are not science fiction — these technologies exist today at different levels of maturity and commercialization. This suggests the technological revolution has only begun to revolutionize the HR profession.
Think about the following HR activities and how the HR practitioner’s work could be amplified by cognitive systems:
A cognitive headhunter is being told to source potential candidates who would be high performers in a role.
Based on their online profile and activities, the scout can anticipate who would be a great cultural fit or who could have the right skill set, despite having the exact same experience (What if research found ex-waiters make great project managers?).
If the passive candidate accepts the scout’s invitation, she can have a cyber-interview first, and the scout can make a recommendation to the hiring manager as to whether an in-person interview is necessary.
The HR professional will offload some of the work to the cognitive system while remaining the final arbiter of the hiring decisions.
Employee engagement starts from day one (and even before) so being able to customize the onboarding experience is crucial to making a good first impression.
A cognitive “buddy” or mentor can help new employees quickly find the information, resources and expertise needed to be rapidly productive.
It can answer every question about systems, process, policies and benefits without overwhelming the employee.
HR professionals can then study the employee experience and use this knowledge to refine the behaviour of the system.
Cognitive employee engagement:
The ability to grow and develop within an organization is a powerful driver of engagement. A cognitive career advisor could guide employees in their careers.
It would be able to suggest training and activities that will benefit employees’ careers or recommend internal job openings, and suggest how to approach a difficult conversation with a manager based on his personality.
Just as employees learn about an organization when they come onboard, organizations will learn about employees.
HR professionals will lead, structure, shape and inform these processes.
Cognitive talent management. While cognitive systems will gain a deep expertise in the area of human resources, labour law or work psychology, they will also act as a decision support system and help an HR practitioner make better decisions based on the best available information: who to hire, pair, promote, separate or train.
In the end, cognitive systems will not replace humans — to the contrary, they will make people more human.
All the hard, analytical, rational processes are better left to machines that won’t suffer from biases, fatigue or envy because humans excel at empathy and their deep interpersonal needs are better satisfied by humans — therefore, these interactions will need flesh-and-bone humanoids.
They will also make us more accountable. People need to seek and take ownership of decisions, and cannot hide behind excuses. Humans need to stay in charge, to set collective goals and own them.
The execution can be left to automated processes that are monitored.
The HR function of the future, working hand in hand with artificial systems, will be wide awake, alert and capable of action.
Benoit Hardy-Vallée is the practice lead and thought leader for IBM Smarter Workforce & Social Business, developing strategies for talent management, collaboration, leadership development, performance management and employee engagement that makes use of technology, science and analytics.
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