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.”
A recent study by the Boston Consulting Group and MassChallenge, a global network of startup accelerators, takes a close look at how startups founded by woman compare to those founded by men, both in terms of how much venture capital financing they receive and how well those investments pay off. Looking at five years of investment and revenue data from the startups MassChallenge has worked with, the study found that those founded by women consistently attracted less investment, even though they actually tend to generate more revenue:
Investments in companies founded or cofounded by women averaged $935,000, which is less than half the average $2.1 million invested in companies founded by male entrepreneurs. Despite this disparity, startups founded and cofounded by women actually performed better over time, generating 10% more in cumulative revenue over a five-year period: $730,000 compared with $662,000. In terms of how effectively companies turn a dollar of investment into a dollar of revenue, startups founded and cofounded by women are significantly better financial investments. For every dollar of funding, these startups generated 78 cents, while male-founded startups generated less than half that—just 31 cents.
The findings are statistically significant, and we ruled out factors that could have affected investment amounts, such as education levels of the entrepreneurs and the quality of their pitches. … The results, although disappointing, are not surprising. According to PitchBook Data, since the beginning of 2016, companies with women founders have received only 4.4% of venture capital (VC) deals, and those companies have garnered only about 2% of all capital invested.
This gender bias may be costly to venture capitalists as well as entrepreneurs: The study calculated that VCs could have made $85 million more over five years had they invested equally in the startups founded by women and by men.
The researchers went one step further and spoke to founders, mentors, and investors to understand the origins of the gender gap in VC funding. Consistent with various other research showing that women are more likely to be challenged, questioned, and criticized in the workplace than men, they found that women founders and their presentations receive more pushback from investors than their male peers. Men are also more likely to talk back to investors when their claims are scrutinized, and to make bold, blue-sky projections in their pitches:
In the US, one in three adults, or around 70 million people, have some form of criminal records, while 20 million Americans have been convicted of a felony. These records often serve to shut otherwise qualified candidates out of all but the least-skilled and lowest-paying jobs. Black and Latino men, who make up a disproportionate share of the prison and ex-offender population, suffer the most from this barrier to employment. The inability to get a good job leaves many former prisoners with few options for escaping a life of crime, and studies have shown that gainful employment for ex-felons is one of the most effective deterrents to recidivism, which means employers play a key role in helping reintegrate former prisoners into society.
With unemployment below 4 percent, more job openings than candidates, and many US employers struggling to find the workers they need, the stigma attached to criminal backgrounds in employment now stands to harm not only individuals and communities, but also businesses. “It is morally and economically bad for our country if we do not start removing barriers that prevent returning citizens from a shot at a better life after they have paid their debt to society,” JPMorgan Chase CEO Jamie Dimon and former secretary of education Arne Duncan write in an op-ed at the Chicago Tribune. “Business should be at the forefront of solving this challenge. Frankly, it’s in our best interest to do so.”
Dimon and Duncan point to several initiatives going on in the Chicago area and around the country to create employment opportunities for ex-convicts and people at risk of being swept up in the criminal justice system:
First, Boeing and a number of other organizations are partnering on Heartland Alliance’s READI Chicago initiative. This two-year program is trying to reduce gun violence by providing returning citizens and others susceptible to gun violence with employment, job training and support services. Programs like this can help reduce recidivism rates, decrease neighborhood crime and promote economic opportunity.
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.
Google’s 2017 diversity report, released last week, expands on the information included in previous reports to cover the retention and attrition of underrepresented talent, as well as an intersectional analysis of race and gender at Google. Overall diversity figures were little changed from last year’s report and showed limited progress since 2014, when Google first began making this data public. Men make up 69.1 percent of the tech giant’s workforce, while its racial makeup is 53.1 percent white, 36.3 percent Asian, 2.5 percent black, 3.6 percent Hispanic or Latinx, and 4.2 percent multiracial. In 2014, the Googler community was 61.3 percent white, 30 percent Asian, 1.9 percent black, 2.9 percent Hispanic/Latinx, and 3.6 percent multiracial.
The company has made some progress in improving the gender balance of its leadership over the past four years, with its the percentage of women in leadership globally rising from 20.8 to 25.5 percent. Google’s US leadership is 66.9 percent white, 26.3 percent Asian, 2 percent black, 1.8 percent Latinx, 0.4 percent Native American, and 2.7 percent of more than one race. Black and Latinx representation in leadership have improved slightly since 2014, while the report highlights that 5.4 percent of new leadership hires in 2017 were black.
The attrition data included in this report touches on an issue that tech companies struggling with diversity and inclusion have discovered to be of critical importance: not just recruiting diverse candidates but also retaining those employees for the long term. Based on an index of US attrition, Google’s report shows that attrition rates are highest among black and Latinx employees, at 127 and 115 compared to an overall index of 100. “Black Googler attrition rates, while improving in recent years, have offset some of our hiring gains,” Google acknowledges, “which has led to smaller increases in representation than we would have seen otherwise.” On a global index, attrition was slightly higher for men than for women, however, at 103 compared to 94.
Effective onboarding often makes the difference between a successful hire and an early quit. To better understand the causes of attrition among recently hired employees, Microsoft created a survey that was given to new employees after their first week and again after 90 days to find out about their experiences and first impressions of the company. The tech giant’s workplace analytics team also compared anonymous calendar and email metadata with engagement survey data from around 3,000 new hires.
At the Harvard Business Review last week, Dawn Klinghoffer, Candice Young, and Xue Liu revealed what this investigation uncovered and how it shaped Microsoft’s decisions about how to improve new hires’ experience. One thing the survey revealed was that having a working computer and access to the building, email, and intranet on day one was important for new hires to be productive and engaged from the very beginning, making an important first impression that colored their overall experience. Their more complex analysis produced another insight: New employees who had a one-on-one meeting with their manager in week one were more successful than those who didn’t:
First, they tended to have a 12% larger internal network and double network centrality (the influence that people in an employee’s network have) within 90 days. This is important because employees who grow their internal network feel that they belong and may stay at the company longer. For example, employees who engage internally intend to stay at a rate that’s 8% higher on our intent-to-stay measure. They also report a stronger sense of belonging on their team while maintaining their authentic self.
Over the past week, the US Equal Employment Opportunity Commission has sent a series of signals to US employers that it is focusing its energies on rooting out sexual and other forms of harassment in the American workplace. On Thursday, the agency announced that it had filed seven separate lawsuits against employers throughout the country over allegations of sexual harassment and misconduct, as well as racial harassment and other forms of abuse.
“As the nation has seen over the past nine months, harassment at work can affect individuals for years in their careers and livelihoods,” EEOC Acting Chair Victoria A. Lipnic said in a press release announcing the lawsuits. “There are many consequences that flow from harassment not being addressed in our nation’s workplaces. These suits filed by the EEOC around the country are a reminder that a federal enforcement action by the EEOC is potentially one of those consequences.” About a quarter of the lawsuits filed by the EEOC in recent years has involved an allegation of harassment, Lipnic added, as do one third of the 80,000 to 90,000 discrimination charges the EEOC receives each year.
The EEOC also recognizes that most instances of harassment never come to its attention. Studies show that more than 80 percent of harassment victims never file a formal complaint, the agency noted in its statement, while nearly three quarters never even raise the issue internally within their organizations. To that end, and in light of the heightened public consciousness of sexual harassment brought about by the #MeToo movement, the agency is also looking to promote changes in American workplace culture to make harassment less common and more likely to be addressed when it does occur.
On June 11, the EEOC reconvened its Select Task Force on the Study of Harassment in the Workplace, a panel of experts including academic scholars, legal practitioners, and representatives of advocacy groups and organized labor, which was established in 2015 to study the problem of harassment (including, but not limited to, sexual harassment) and what employers and the agency itself could do to prevent and respond to it. In her opening remarks at last Monday’s meeting, Lipnic, who co-chairs the task force along with Commissioner Chai R. Feldblum, stressed that harassment had been on the EEOC’s radar for some time, but that the government could not solve the problem alone: