For much of the world’s population, mobile devices serve as the primary tool for getting things done. Whether its banking, scheduling meetings, buying new clothes, or ordering pizza, the mobile smartphone, running a specifically designed application, can do it. Businesses in practically any industry simply must have a presence on mobile devices or they will suffer from a considerable competitive disadvantage.
Creating, designing, developing, and implementing apps for an increasingly mobile world is the job of the Mobile Application Developer. Like all application developers, the best candidates for such a position will have impeccable programming skills, but also something more. Mobile Application Developer recruiting also requires a search for candidates with knowledge of how mobile devices and mobile culture work. This knowledge does not always come from work experience, sometimes life experience may play a more important role.
Finding and recruiting a skillset that combines high-level programming skills with intricate and intimate knowledge of mobile devices will require a comprehensive hiring process. This Hiring Kit: Mobile Application Developer, from TechRepublic Premium, provides an adjustable framework your business, a job description, Want Advertisement, interview questions and analysis.
More companies are using AI hiring tools in the hiring process to pinpoint premium candidates. But potential biases in these technologies have raised ethical concerns.
In recent years, a growing number of organizations have utilized artificial intelligence (AI) to revolutionize their traditional workflows. These systems are implemented to enhance cost-efficiency, reduce employee burnout, and even identify premium talent. Many organizations are using AI tools to expedite the arduous hiring processes. These algorithms have been viewed as objective tools capable of eliminating human subjectivity from the employment screening process. Paradoxically, many of these models are riddled with the same inherent biases these systems are intended to remove. The idea of AI agents acting as the preliminary filter for candidates brings up a vast set of diversity and ethical concerns. That said, is it possible to leverage these systems in an equitable way to build a more inclusive workforce?
Companies turn to AI hiring tools to manage the volume of applicants and remove human bias
In the age of telecommuters and video conferences, more companies have warmed to the prospect of bringing on remote employees. Rather than limiting the talent pool to employees in a given area, qualified candidates can now readily apply from around the globe. Analyzing the sheer volume of applicants is often a daunting task for hiring managers.
With the potential to automate the screening process and eliminate human bias, these AI tools have been viewed as a win-win for efficiency and inclusivity. Needless to say, good intent does not always generate positive outcomes.
“I feel so bad for companies because the reason that they bought the tools is because they want to become more objective. It’s never because they want to do the wrong thing, but the tool itself is just not the right instrument for equity, it’s an instrument for efficiency, but it’s not an instrument for equity,” said Mutale Nkonde, CEO of AI For the People with current fellowships at Harvard and Stanford.
Recent evidence and use cases illustrate myriad ways these platforms hinder inclusivity efforts. After all, these programs are only as equitable as the data they are fed. If these algorithms are built on biased data, these systems will only perpetuate prejudice and compound a lack of diversity in-house.
“Humans are inherently biased—and machine learning capabilities can end up perpetuating that bias because that data itself might be biased, ” said Amy Hodler, director, Graph Analytics and AI Programs at Neo4j. “At the end of the day, the ML models are written by a human. AI today is effective for specific, well-defined tasks but struggles with ambiguity which can lead to subpar or even disastrous results.”
Flaws in AI optimization metrics can lead to unintended, biased outcomes
These AI systems can be trained to look for keywords associated with high performance and other metrics the algorithms connect with top talent. Algorithms can then upgrade or penalize candidates based on these criteria. Major players in the tech industry have looked to reap the benefits of AI-enhanced hiring systems.
A few years ago, Amazon assembled a team of engineers to develop models capable of pinpointing premium talent and assigning a tiered rating system for candidates. During development, the system exhibited biased preferences and was eventually discontinued.
“Their recruitment algorithm was effectively pushing out resumes that had the words girl or girls in there, or woman or women. That meant if you put on your resume that you went to a women’s college, Spelman being a Black women’s college in Atlanta, that resume wasn’t even going to get promoted for further consideration,” Nkonde said.
When calibrating a new hiring algorithm, a company may want to use its own metrics of in-house performance to identify top talent. This algorithm can be fed historical data related to its current top-performing employees as part of its talent search filtering process. However, if a company already has a history of internal hiring bias and lack of diversity, a hiring algorithm trained on this dataset will only perpetuate this lack of inclusivity.
As Nkonde pointed out, if a company has never hired a Howard University alumni, and the algorithm has been optimized on traditional metrics and patterns associated with in-house talent, the Howard graduate’s resume will be filtered from the candidate pool and never make it to the next round.
Flawed emotion recognition technology may thwart inclusivity efforts
These sophisticated tools are used for far more than sifting through resumes to screen candidates. A number of organizations are utilizing emotion recognition during the interview process to analyze candidates.
“They’ll look at your facial expressions and then try and infer through facial expressions whether you were telling the truth, whether you were comfortable, whether you were interested, whether you were engaged and then that will have some type of score that relates to your employability,” Nkonde said.
From crafting financial briefings to identifying potential new uses for existing pharmaceutical medications, AI systems have been leveraged for a host of applications across industries. While these models are quite impressive at consuming massive catalogs of datasets and pinpointing patterns, these systems are woefully inadequate at human reasoning and discerning context. These latest findings reiterate the need for human oversight within the hiring and recruiting process.
“At its best, what these algorithms [are going to] do is return a very, very particular type of person, who has the same exact qualities of whoever’s considered a model of success. The reason that that’s actually even worse than human decision making is that in human decision making there’s always the option that we will think outside of the box, there’s always the option that we will take a chance. There’s always the option that we will do things differently and that’s really the story of human progress from the beginning,” Nkonde said.
While these advanced tools can certainly expedite the hiring and recruiting process, there are long-term consequences for organizations to consider. In recent weeks, organizations have taken a closer look at standard operating procedures and with diversity and inclusivity in mind. At times, this might require organizations to scrutinize more than their basic hiring practices.
“Improving the rigor in the talent process is the first step in improving diversity and inclusion. Technology cannot solve a broken culture or a broken process. Leaders and HR professionals need to make a commitment to a fair talent lifecycle, understand the value that brings and continuously monitor for improvement opportunities,” said Dr. Joel Philo, principal behavioral scientist at Infor.
With diversity and equity at the forefront of public debate, some organizations are taking a closer look at the impact of their technological choices and standard procedures. Whether AI hiring tools can be implemented in a fair and equitable way remains largely up for debate.
“Should we use these implements when hiring people, or should we think about new ways of screening nontraditional applicants and bringing them in? Because unless we can employ some aspirational and revolutionary and equity-based thinking, we’re going to fall back on these magic machines that are here to solve our problems, when the real problem isn’t who should I hire? The real problem in my view is how do I create a labor force that gives all people opportunity?” Nkonde said.
In a competitive business universe, the more successful companies innovate, iterate, evolve, and improve their product and services. For many industries, this drive to innovate not only applies to the finished product, but also to the processes required to create the finished product. A stagnation of ideas could cost a company market share and perhaps much more.
Industries that depend on information technology and related fields of research, often call upon the Computer Research Scientist for innovative ideas. Generally tasked with creating and improving computer software and hardware, the Computer Research Scientist works to turn abstract algorithms into practical improvements in efficiency and productivity. Computer Research Scientists often play integral roles in artificial intelligence, machine learning, autonomous vehicles, and robotics.
Finding and recruiting a skillset that combines high-level abstract thinking with the practical understanding of business requirements will likely require a comprehensive hiring process. This Hiring Kit: Computer Research Scientist, from TechRepublic Premium, provides an adjustable framework your business can use to find, recruit, and ultimately hire the right person for the job. Also included in this Hiring Kit are sample interview questions with notes, a sample Want Advertisement, and job descriptions.
Big brands from a wide swath of industries are looking to fill long-term posts, according to Flexjobs.com.
Unemployment remains high as Americans emerge from the pandemic-driven lockdown, but 18 well-known companies that made the switch to telecommuting are currently hiring for long-term remote work, according to Flexjobs.com.
This is welcome news: Working remotely is not only safer from COVID-19, it’s very popular, especially among those who had the opportunity to work from home (WFH), after fears of the spread of COVID-19 shifted the way many Americans work.
Some companies that have made the complete shift to remote work are hiring now, and it means a job with a recognizable company name. And there’s a wide swath of industries, too, including big tech, credit card or affiliated companies, real estate, social media, sales, higher education, research and advisory, social and viewing management, software, family history research, and an online retailer, Flexjobs.com said.
Find open WFH technology positions at the following companies:
Flexjobs.com reports that “many companies are now figuring out that working remotely is the future of work, pandemic or not.” Companies in which some staff already WFH, (if not full-time, then a hybrid of WFH and in-office) made an easier transition than those whose employees worked only or primarily in the office.
Once the WFH system was in place, companies discovered that remote work facilitates increased productivity, a better work-life balance and collaboration among colleagues.
The cost of working from home
Even though it might cost about an additional $108 monthly, 35% of Americans working from home prefer not to return to the office yet, according to a CreditCards.com survey. Sheltering-at-home has changed many lifestyles, as people spent $182 more on groceries, $121 more on utilities, but they’re saving on child care, gas and public transportation, restaurants and takeouts, and clothes and dry cleaning, the survey found.
More than three-quarters of those polled (2,768 adults who have, or are currently, WFH) by CreditCards.com want to continue to WFH for “at least two days per week,” and that includes the 35% who want to telecommute full-time.
Meanwhile, 21% said they wanted to WFH “most of the time, and 26% said they would “some of the time.” Other poll numbers were considerably lower: 7% wanted to WFH once-a-week, 6% said less than once weekly, and only 4% said they never wanted to work from home again.
A Global Workplace Analytics survey of 3,000 employees found that 72% of telecommuters say they have the resources to be successful and home, and that they’re most successful, when armed with tools, skills, resources and a nice place to work at home.
To gain competitive advantage, modern business has turned to technologies like cloud computing and big data, but the benefits derived from those high-level concepts can only be reaped when there are applications built to exploit them. The application engineer creates, designs and tests computer software programs designed to meet pre-determined specifications and goals.
Application engineers work in the trenches of software development and are often required to first assess what a client, both internally and externally, needs, wants, and should want from a prospective or existing application. Only then does an application engineer have the framework necessary to begin the actual coding of a piece of software.
Application engineers need to have technical expertise in programming, design, business, and the software and hardware required to run the application. A skillset that not everyone possesses. This Hiring Kit: Application Engineer, from TechRepublic Premium, provides an adjustable framework your business can use to find, recruit, and ultimately hire the right person for the job.
Quality Assurance Engineers apply their technical expertise and skills to oversee the entire software development lifecycle and to verify the quality of the product and the overall user experience against a checklist specified by the client. Finding and hiring individuals with the right technical expertise, system experience, and ability to apply that expertise to software development and testing will require thorough recruiting and candidate vetting.
This Hiring Kit: Quality Assurance Engineer, from TechRepublic Premium, provides an adjustable framework your business can use to find, recruit, and ultimately hire the right person for the job.
Finding the right person to fill the role of robotics engineer can be tricky because of the combination of skills required. This kit includes a detailed job description, sample interview questions, and basic want ad to simplify the task.
From the job description:
For many industries and enterprises, manufacturing of any kind is dependent on robotics in some capacity. Automation and the efficiency it brings to the manufacturing process is the technology that can ultimately make or break an enterprise.
Qualified engineers are required to develop, test, and maintain these robotic machines. Finding the right engineer, with the right experience and qualifications, takes effort, determination, and a detailed description of the job at hand. This sample job description for a robotics engineer will help you form a foundation for your enterprise’s next candidate search.
A robotics engineer designs the plans needed to build robots, codes the processes necessary for the robot to run correctly, and develops the procedures the robot will execute once it is built. Sometimes the robotics engineer will also be tasked with designing and building the machines that actually assemble the robots. Only after the design phase has been completed does the engineer move toward assembling the unit. This means a robotics engineer must be a creative designer, a programmer, and a precise engineer—a rare combination of talents.
The company is seeking a self-motivated individual with creative skills in design as well as impeccable skills in precision engineering and programming. The successful candidate will exhibit passion and enthusiasm about engineering, robotics, programming, and the creative process. Candidates will have qualifications, certifications, and experience commensurate with the open position.