Some large companies receive as many as 4.5 million resumes annually. Others get 10 million applications every year. Obviously, only a tiny fraction of these applicants can get hired. Finding a new job can be a job unto itself: perfecting a resume, scanning career websites, networking among friends and acquaintances. Job searches of the future need to be a completely different experience, with technology doing most of the heavy lifting. I predict a job-hunt landscape that will look very different just a few years from now.
The Job Board
About 65% of people look for new jobs within 91 days of being hired at a job which suggests matchmaking in the search for work may be less than perfect. Those imperfections can only be fixed with data—and lots of it. The sheer amount of information on job skills, salaries and user tendencies makes matching people to positions simply impossible without using AI to crunch the numbers. the Indeed.com job board generates an average of 25 terabytes of data every day.
Skills Above All
Skills testing is the centerpiece for CodeFights, a four-year-old San Francisco-based firm that offers tech workers a platform on which to practice their coding skills and to demonstrate those skills which are
scored and rated on the CodeFights platform. This system of skills-based recruiting opens doors for programmers based largely on their proven talents and offers recruiters a true picture as to what a prospective hire can actually do. There are so many data points to consider: skills, salaries, location, personality, experience, company culture, inaccuracies in resumes or job descriptions.
Job search platforms or services will ultimately become education hubs, offering skills-building services that also rate proficiency, making it easier for job-seekers to prove their quality to employers, with whom they would be matched.
A Layer of Testing
Assessing skills specific to various industries is the name of the game for Harver, a five-year-old firm based in Amsterdam. Its specialty is having job applicants go through a testing process—chosen by hiring companies—that gauges whether they are a good match for a given position. The firm has made deals with Netflix, Booking.com, OpenTable and Zappos. It’s impossible to predict whether someone would stay in the job and do it proficiently so the firm designs algorithms and testing processes with recruiting clients to predict a good match for a job.
A Deeper Knowledge Equals Efficiency
AI and machine-learning allow services like Indeed to make predictive assessments of factors such as what a salary should be. Calculations hone in on what wages would be appropriate for a particular job, in a specific location, or at a specific company. Exact job title also comes into play.
As for the future, job seekers will likely see a reduction in their research time while looking for work. As AI and machine-learning develop in the field, a service like Indeed should be able to suggest new, much more compatible opportunities based on a job seekers’ work experience, skills, salary, interests and location. A career-focused AI should also tell job seekers whether they are being paid fairly at their current job, with a high degree of accuracy, compared to others in their line of work. Consider this:
- In China, where there aren’t enough radiologists to keep up with the demand of reviewing 1.4 billion CT scans each year to look for early signs of lung cancer. Radiologists need to review hundreds of scans each day which is not only tedious, but human fatigue can lead to errors. Infervision trained and taught algorithms to augment the work of radiologists to allow them to diagnose cancer more accurately and efficiently.
- Music-generating algorithms are now inspiring new songs. Given enough input—millions of conversations, newspaper headlines and speeches—insights are gleaned that can help create a theme for lyrics. There are machines such as Watson BEAT that can come up with different musical elements to inspire composers. AI helps musicians understand what their audiences want and to help determine more accurately what songs might ultimately be hits.
- Using natural language processing, machine learning and advanced analytics, Hello Barbie listens and responds to a child. A microphone on Barbie’s necklace records what is said and transmits it to the servers at ToyTalk. There, the recording is analyzed to determine the appropriate response from 8,000 lines of dialogue. Servers transmit the correct response back to Barbie in under a second, so she can respond to the child. Answers to questions such as what their favorite food is are stored so that it can be used in conversation later.
- The AI tech revolution has hit farming as well, and John Deere is getting data-driven analytical tools and automation into the hands of farmers. They acquired Blue River Technology for its solution to use advanced machine learning algorithms to allow robots to make decisions based on visual data about whether or not a plan is a pest to treat it with a pesticide. The company already offers automated farm vehicles to plough and sow with pinpoint-accurate GPS systems and its Farmsight system is designed to help agricultural decision-making.
- UK news agency Press Association partnered with news automation specialist Urbs Media to have robots write 30,000 local news stories each month in a project called RADAR (Reporters and Data and Robots). Fed with a variety of data from government, public services and local authorities, the machine uses natural language generation technology to write local news stories. These robots are filling a gap in news coverage that wasn’t being filled by humans.
- Google is using AI and satellite data to prevent illegal fishing. On any given day, 22 million data points are created that show where ships are in the world’s waterways. Google engineers found that when they applied machine learning to the data, they could identify why a vessel was at sea. They ultimately created Global Fishing Watch that shows where fishing is happening and could then identify when fishing was happening illegally.
- Even Disney is getting even better thanks to big data. Every visitor gets their own MagicBand wristband that serves as ID, hotel room key, tickets, FastPasses and payment system. While guest enough the convenience, Disney gets a lot of data that helps them anticipate guests’ needs and deliver an amazing, personalized experience. They can resolve traffic jams, give extra services to guests who may have been inconvenienced by a closed attraction and data even allows the company to schedule staff more efficiently.
In the span of less than 20 years, job hunting will have evolved from newspaper want ads to online job boards to social sites like LinkedIn to AI powered headhunting. Experts in the recruiting field agree that AI can help streamline the connection between employer and candidate. With the vast amounts of data collected on skillsets, job titles and salaries, AI can help job boards like Indeed make accurate predictions on hiring competition and compensation. It helps cut down on the research time for job seekers and helps employers find qualified candidates faster.