Welcome to the machine
Artificial intelligence is already changing the way we work. What does the future hold for this technology that once seemed the stuff of science fiction?
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From the pages of In Business magazine.
Just in case there’s any doubt that in 2019 machines run our lives, take a look around the office the next time the power goes out or the internet is down. You’ll find a whole lot of people wondering, “What do I do now?” Artificial intelligence, or machine learning, isn’t just the next wave of technological advancements to impact the way we work — it’s already here. While the prospect of smart machines working alongside humans may unsettle some, local experts say we’d better get used to it. AI, as part of the Digital Revolution, is going to impact all facets of business, and that’s a good thing.
“I firmly believe that over the next five to 10 years — maybe even sooner — that this technology will become engrained in our daily lives, and we will eventually reach a point where we can’t remember what it was like to live before this technology existed,” says Nick Myers, creative director for Sun Prairie-based RedFox Creative, a marketing agency that specializes in voice-first strategy and Alexa/Google Assistant skill design, development, and deployment. “Where we are currently with voice is like where we were in the mid-to-late 1990s with the internet and in the mid-to-late 2000s with mobile and smartphones. For younger generations that have never lived before these technologies existed, and even for older generations, many people wonder how they went so long without having access to what we have today.”
A 2017 post on Quora, a question-and-answer website where questions are asked, answered, edited, and organized by its community of users, asked, “What would happen if humans lost 50 percent of all the jobs in the world to robots?”
In a response, user Glenn Luk upped the stakes — “Let’s take this question to the extreme: What if humans lost 90 percent of all jobs in the world to robots, automation, and technology? We’d be where we are today.”
- One hundred years ago, the overwhelming majority of people in the world worked on farms. Thanks to the invention and widespread adoption of technology, it’s now possible for small minority of farmers (2 percent in the U.S.) to provide food for everyone.
- A little more than 100 years ago, millions of jobs were devoted to the primary mode of local transportation: the horse-drawn carriage. None of those jobs exist today.
- Seventy years ago, the railroad industry employed roughly 3 percent of the U.S. workforce. Today, the railroad industry employs just 0.1 percent of the workforce, although it moves nearly three times the amount of freight around the country.
Those are just a few examples of ways technology eliminated jobs once performed by humans, and yet humans continue to find ways to work. We might not be able to work in the modern world without those machines, but the machines also still need us.
“You will never truly remove the entire human factor from AI,” notes Coreyne Woodman-Holoubek, CHRO, co-founder of Contracted Leadership and president of Disrupt Madison and Disrupt Milwaukee, and a bit of a technology evangelist. “AI will need someone — a human — to learn from. I believe we have really only scratched the surface regarding the capacity of what our human brain can and will do.”
AI will increase our cognitive capacities, by helping us in our daily lives with tasks that take our mental energy and by automating our learning, Woodman-Holoubek continues. “Exponential technology will improve our quality of life and our brain, but we need to remain aware and not let it take us over. I don’t mean the human race, I mean us as humans. We have to consider if these technologies such as virtual reality, augmented reality, and the like that are powered by AI will mean that we could potentially lose our touch on knowledge mastery, reality, and our rationality?
“With proper regulations from independent bodies — not governments — there will always be a human watching out for other humans, at least, in our lifetime,” Woodman-Holoubek adds.
As a human resources professional for nearly 20 years, Woodman-Holoubek has an interesting perspective into the way businesses recruit, hire, train, and evaluate employees. In her opinion, the next decade could see the removal of the human element from the majority of each of those processes. Rather than being wary of that prospect, she welcomes it.
“It’s hard to imagine all the ways AI could impact HR processes in the next 10 to 20 years,” opines Woodman-Holoubek. “We do know that AI will allow for mundane, repetitive HR functions to be automated and optimized, create efficiencies in workflows, focus on the employee experience, gather data for predictive and people analytics, and allow HR professionals and workers the ability to achieve exponential growth in their learning, development, careers, and happiness within the next five to eight years. As well, AI will allow for some surprising impacts in the core HR technology architecture, in addition to making chatbots, robots, and holograms our co-workers.”
Sound like science fiction? It’s already happening.
“Our economy will be vastly improved by incorporating AI and removing some of the human factor.” — Coreyne Woodman-Holoubek
According to Woodman-Holoubek, AI can comb through large sets of data on job boards, in databases and social media profiles, and keys to access digital identities on the blockchain. With this capability, it will allow us to have “almost perfect” job and project-matching with efficiency and massive cost savings. “Platforms like Indeed, LinkedIn, and Glassdoor are currently optimizing this, as well as sourcing tools from companies such as Entelo, TalentBin, Gloat, Orderboard, and Hiretual, which are helping companies find hard-to-locate candidates,” she explains. “This includes locating internal candidates, as well, which are now one of the biggest sources for new jobs created by automation and robotics.”
During the interview process, she adds that we can expect AI facial recognition to allow interviews to be more authentic and transparent. AI that currently is being developed can read facial expressions that may not necessarily be in line with the answers candidates provide, potentially avoiding “bad hires.” Chatbots can also answer general queries and teach us what to look for in good hires, as well as what to look for in good questions.
According to Woodman-Holoubek, the independent categories of search, matching, candidate relationship management, and recruiter analytics are likely to merge into one over the next five years. PhenomPeople, a platform combining all these categories, is currently working on this technology.
“AI will also allow individuals and organizations to customize training, learning, and employee evaluation programs,” Woodman-Holoubek notes. “IBM is trying to build out its own family of talent applications, including IBM Watson tools for assessment, career planning, job coaching, salary planning, and interfacing with its human capital management platform. IBM’s CHRO says that the company’s internal use of AI has had a dramatic improvement in employee career management and salary administration. The system now recommends career moves and salary changes based on patterns of success within IBM, demand in the outside market, and demand for skills inside IBM.”
On top of that, Woodman-Holoubek expects AI desk assistants or “co-workers” to be able to conduct filtered chats to improve learning outcomes based on content and learner preference. This in turn would help continuous virtual learning systems in the organization guide the learners, organization, or trainer to revamp learning models and AI dimensions, and then the AI learning could update the models in real time. These processes could also tell the organizational system if a skill gap or job void exists, triggering the AI system to find a job or skill match to recruit.
“I’m in favor of automating the recruiting and hiring process for better job matching, for elevated candidate communications, and for cost and time-saving on both the part of the organization and the candidate,” says Woodman-Holoubek. “Our economy will be vastly improved by incorporating AI and removing some of the human factor. Forty-five million people in the U.S. change jobs each year, and that figure jumps to 180 to 225 million people worldwide. Every time someone changes jobs there is a candidate search, a set of interviews, assessments, job testing, background checks, and an enormous amount of effort and time for face-to-face meetings that eventually yield an offer or two or three depending on the candidate pool, and then onboarding, which if done properly takes six months to a year. All of these steps can be automated with AI.”
Although AI has vast potential to remove implicit and explicit bias from the hiring and evaluation process, it’s still only as good as the people programming it. “In the HR tech world, we have a saying regarding the algorithms and learning of the AI — junk in is junk out,” says Woodman-Holoubek. “If we are expecting unbiased hiring from AI right now, we have to closely look at our organizations. We are nowhere near ridding our organizations of bias enough that a machine could learn to be unbiased from us. As well, how do we know that the coder or coders who built the underlying code does not have biases?”
How and where we use, treat, and protect the data that employees give us is of utmost importance and must be considered with every technology decision, she adds. If we expect employees and workers to give us their data sets around their skills, talents, and learning, then we must know that they expect we will give them something of value in exchange. If expectations are not met on the employer end, there can be huge societal consequences. Will we erode the trust in our economic system of employer and employee — the employment contract? Will data breaches be catastrophic?
“Organizations may want to establish ethics-related positions or review boards as a part of their AI efforts to guide businesses on such issues as algorithmic bias and the impact on consumers of AI applications,” she states.