The job search website CareerBuilder has rolled out a new mobile app that uses artificial intelligence and augmented reality to help job seekers apply and employers find candidates more quickly and easily, VentureBeat reported last week:
The mobile app has some attention-grabbing features. It can build your resume, apply to jobs on your behalf, and show augmented reality views of job openings at the businesses you walk by. It also helps you develop the skills needed for a better-paying job.
And for [employers], the mobile app shows the real-time supply and demand trends for talent you need. It instantly builds your job descriptions, automatically matches your job openings to candidates who are more likely to respond, and runs campaigns to engage them.
CareerBuilder’s mobile app is the latest in a series of new technological innovations search engines and job boards have unveiled in the past year to simplify and streamline the job search process and to provide prospective applicants with additional information about organizations and roles. Google’s built-in job search function was launched in the US last year and has since expanded to India, Canada, and the UK. The search giant has also developed new tools for recruiters, including an AI-powered candidate discovery feature and its Cloud Talent Solution product, which it made publicly available last month. Facebook has also added a dedicated job search functionality, which it has rolled out in 40 countries. The Japanese HR conglomerate Recruit Holdings, which owns Indeed, made a deal to acquire Glassdoor earlier this year.
According to Gartner research, the adoption of AI is poised to grow rapidly in the coming years. This and other emerging technologies like robotics are bound to fundamentally change the way we work, largely or completely automating many of today’s jobs. While this technological upheaval is generally expected to create more jobs than it destroys, the transition will be disruptive and challenging for many professionals accustomed to working in a pre-AI world. The most dire projections anticipate widespread displacement or the radical transformation of current jobs due to AI and robotics, potentially affecting tens of millions of workers in developed countries.
The effects of automation will be challenging for the clients of many HR business partners, and HRBPs will be called to provide increasing support for those impacted, such as ensuring they have access to retraining opportunities. In addition, HRBPs see themselves as part of the population affected by automation: Ten years from now, HRBPs expect nearly half of their current day-to-day responsibilities to be automated. HRBPs are optimistic, however, about the impacts that technology and automation will have on their role. Our research at Gartner finds 68 percent of HRBPs agree that automation is an opportunity to prioritize strategic responsibilities. To capitalize on this opportunity, however, HRBPs need to anticipate what work will be automated and what work will be augmented.
At a recent meeting with 70 HRBPs in New York City, we discussed predictions for the future of their role and asked them how technology has changed or will change it. Several attendees mentioned employee data collection: Previously, this was an onerous monthly or quarterly process of manually pulling together data from various sources to populate dashboards for stakeholders. Technology has made this process easier and quicker, with the use of pulse surveys and other tools. It also creates opportunities to collect data in larger quantities or more precisely, and to use it in new ways, though HR still has a lot of work to do in convincing the C-suite of the value of talent analytics.
After successfully piloting its AI-enhanced job search technology, Cloud Talent Solution, with select customers including Johnson & Johnson and CareerBuilder, Google made the product publicly available last week, VentureBeat reported:
Cloud Talent Solution, which launched as Cloud Jobs API in 2016, is a development platform for job search workloads that factors in desired commute time, mode of transit, and other preferences in matching employers with job seekers. It also powers automated job alerts and saved search alerts. According to Google, CareerBuilder, which uses Cloud Talent Solution, saw a 15 percent lift in users who view jobs sent through alerts and 41 percent increase in “expression of interest” actions from those users.
Alongside the public launch of Cloud Talent Solution, Google introduced a new feature to the toolset: profile search. It allows staffing agencies and enterprise hiring companies to, using natural phrases like “front-end engineer” or “mid-level manager,” sift quickly through databases of past candidates. Profile search is available today in private beta.
Organizations can try Cloud Talent Solution out for free (pricing kicks in at over 10,000 queries per month) directly through the Google Cloud platform, or request access through one of Google’s talent acquisition technology provider partners.
The public rollout of Cloud Talent Solution is another sign of Google’s extensive investment in AI and machine learning and the rapidly growing application of these technologies to talent acquisition and management. It is just one of several avenues through which Google is moving into the recruiting market.
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Once the industrial base of the US, the Midwest has struggled in the high-tech era to capture the talent-driven growth enjoyed by coastal cities like Boston and San Francisco, but the region’s fortunes are changing fast. In the past year or so, a burgeoning Midwestern tech scene has begun attracting more attention from venture capitalists and Silicon Valley giants, with many local startups and big-company expansions focusing on the middle-skill roles for which the tech sector’s demand is insatiable, but that are still in short supply nationwide. These “mid-tech” or “new-collar” jobs are described as a 21st century analog to the factory jobs of the past—and as such, a promising path to revival for the industrial Midwest.
High-tech industries including major international firms have been making some big bets in the region: The Indian IT services and business process outsourcing giant Infosys is planning a sprawling campus near Indianapolis, which aims to create 3,000 new jobs within five years, while the Taiwanese multinational Foxconn Technology Group made a deal with the Wisconsin state government last year to build a display panel factory there, which will see the company invest as much as $10 billion and hire as many as 13,000 people. Several midwestern cities are on the list of finalists in the competition to host Amazon’s second headquarters, though Detroit, for example, didn’t make the cut, partly due to a lack of readily available talent.
Yet “mid-tech” companies and regional outposts of tech giants are just one side of the Midwest’s high-tech renaissance. Over the weekend, VentureBeat reporter Anna Hensel took a look at the growing community of AI and machine learning startups in the heartland:
“The real benefit of artificial intelligence is the application to traditional problems and products that the world needs, and the really successful companies have that domain knowledge that they can understand how to apply this technology,” [Chris Olsen, a partner at Columbus, Ohio VC firm Drive Capital,] told VentureBeat in a phone interview. “We see more of those domain experts in these industries [with] massive chunks of GDP that exist here in the Midwest.”
LinkedIn’s latest round of updates to its job posting tool includes features designed to help smaller organizations without dedicated recruiting functions to more easily source and track qualified candidates, Monica Lewis, Head of Product at Linkedin Jobs, announced on the professional networking platform’s Talent Blog last week:
Now, when you post a job on LinkedIn, these new features will work to deliver a pool of relevant candidates who you can’t find anywhere else. … Once you’ve posted a job on LinkedIn, Recommended Matches will scour our network to find candidates who have the experience and skills you’re looking for. And, most of these candidates are exclusively on LinkedIn: 57% of our users in the US did not visit the top three job boards last month.
We put these potential candidates right in front of you, giving you access to their full profiles. In one click, you can indicate if you’re interested in a candidate and start a conversation with them about the job opportunity. Based on how you rate candidates, our algorithm learns your preferences and delivers increasingly relevant candidates.
LinkedIn, which is owned by Microsoft, has also reconfigured its matching algorithm and given organizations the ability to add their own targeting preferences, giving them more control over who sees a job post. The update also makes it easier for users to keep track of candidates they are considering or wish to contact.
The new features are deliberately designed to encourage smaller and medium-sized enterprises to use LinkedIn as a job board. ERE’s Joel Cheesman calls this “a smart move at the right time”:
In the latest release of its applicant tracking system, Google Hire, the tech giant has added three new features that use Google AI to reduce repetitive and time-consuming tasks, Senior Project Manager Berit Hoffmann wrote in a blog post announcing the update on Tuesday. From measuring user activity, Hoffmann noted, Google determined that Hire has already cut down the amount of time recruiters spend on common tasks like reviewing applications or scheduling interviews by up to 84 percent; the new features are intended to simplify the process even further. The new features include:
- Interview scheduling: When a user wants to schedule an interview with a candidate, Hire now uses AI to automatically suggest interviewers and time slots. The AI will also alert the recruiter if an interviewer cancels at the last minute and recommend a replacement. “This means hiring teams can invest time in preparing for interviews and building relationships with candidates instead of scheduling rooms and checking calendars,” Hoffmann writes.
- Résumé highlighting: To reduce the amount of time recruiters spend scanning candidates’ résumés for key terms, Hire will now automatically analyze the terms in a job description or search query and automatically highlight them on résumés. Google introduced this feature after observing that users were frequently using “Ctrl+F” to search for the right skills—an easily automated process.
- One-click candidate phone calls: The final feature is designed to make it easier for recruiters to reach out to candidates by phone with a click-to-call functionality. Users can call a candidate simply by clicking on their phone number, while the system will automatically log calls to keep track of which candidates have already been contacted by whom.
Google Hire was launched last July as part of the company’s G Suite of enterprise software offerings, but only for US businesses with under 1,000 employees: a deliberate decision to help level the playing field for small and mid-sized businesses that lack the dedicated recruiting resources and bespoke applicant tracking systems of their larger peers. In April, Google Hire expanded into the sourcing realm with a new “candidate discovery” feature that allows users to more easily keep track of past candidates who might be good fits for newly open positions, along with more advanced search capability to provide more relevant results based on what recruiters are actually looking for.
ERE’s Joel Cheesman sees these new AI enhancements as further evidence of the massive edge large tech companies like Google, Facebook, and Microsoft enjoy in the new era of online recruiting: “Deep integration into technologies that so many people already use daily, such as Gmail and Google Calendar, must drive traditional recruiting technology solutions crazy. Build all the Chrome extensions you want, but nothing’s ever going to be better than the stuff Google has baked itself.”
As machine learning algorithms are called upon to make more decisions for organizations, including talent decisions like recruiting and assessment, it’s becoming even more crucial to make sure that the performance of these algorithms is regularly monitored and reviewed just like the performance of an employee. While automation has been held up as a way to eliminate errors of human judgment from bias-prone processes like hiring, in reality, algorithms are only as good as the data from which they learn, and if that data contains biases, the algorithm will learn to emulate those biases.
The risk of algorithmic bias is a matter of pressing concern for organizations taking the leap into AI- and machine learning-enhanced HR processes. The most straightforward solution to algorithmic bias is to rigorously scrutinize the data you are feeding your algorithm and develop checks against biases that might arise based on past practices. Diversifying the teams that design and deploy these algorithms can help ensure that the organization is sensitive to the biases that might arise. As large technology companies make massive investments in these emerging technologies, they are also becoming aware of these challenges and looking for technological solutions to the problem as well. At Fast Company last week, Adele Peters took a look at Accenture’s new Fairness Tool, a program “designed to quickly identify and then help fix problems in algorithms”:
The tool uses statistical methods to identify when groups of people are treated unfairly by an algorithm–defining unfairness as predictive parity, meaning that the algorithm is equally likely to be correct or incorrect for each group. “In the past, we have found models that are highly accurate overall, but when you look at how that error breaks down over subgroups, you’ll see a huge difference between how correct the model is for, say, a white man versus a black woman,” [Rumman Chowdhury, Accenture’s global responsible AI lead,] says.