Translator | Cui Hao
Reviewer | Sun Shujuan
Although artificial intelligence is developing rapidly, we have not Experience the full scope of artificial intelligence (AI) and its capabilities. After all, the scope of AI’s impact and development prospects still dominate research, and scientists are still keen to find new application cases from AI innovations.
So far, we have encountered the application of artificial intelligence in various situations. That’s because many of the companies we patronize have increased their use of AI technology. One example is Siri, the interactive personal assistant that enables Apple customers to get information across a variety of apps, dictate emails and perform tasks using iOS phones, smartwatches, computers and TVs.
Many brands are also leveraging chatbots to deliver impeccable customer experiences in a way that not only drives sales but also eliminates repetitive tasks, thereby increasing human employee engagement Spend.
While the application rate of artificial intelligence tools is rising, investment by its companies is also soaring. According to McKinsey’s State of Artificial Intelligence 2022 report, 52% of respondents identified 5% of their digital budgets More than % is used for artificial intelligence. In 2018, this proportion was 40%.
In terms of human resources, artificial intelligence can help companies improve employees’ satisfaction with their current roles and assist employees to complete tasks quickly, thereby saving money. Time and money are two indispensable factors. Beyond this, businesses can improve recruiting by using AI-powered software to sift through thousands of applications and narrow down a handful of experienced candidates.
However, there have also been instances where the system favored one particular group or gender over others. This is a dangerous trend that, if left unchecked, can significantly damage a company's image and negate the benefits of the technology. To help you effectively deal with bias in AI processing, this article provides some guidance.
In the past, people looked for job postings in classified ads in newspapers and responded by handwritten letters. Nowadays, anyone can obtain job information through a large number of channels on the Internet.
Recruiting is a company priority. This explains the increasing use of staffing agencies. Using artificial intelligence not only simplifies this process but also expands the possibilities for domain automation. From Tidio Focus on the impact of artificial intelligence on recruitmentSurvey found that nearly 67% of HR professionals admitted that this innovation had a positive impact on the recruitment stage.
But how does "prejudice" come unexpectedly?
In 2014, e-commerce giant Amazon chose to incorporate artificial intelligence into its recruiting system. While this was largely seen as a step in the right direction, as Amazon is a staunch advocate of automation, when something happened, the effort came to naught. The hiring system favors male candidates over female candidates.
"...Amazon's computer models were trained to vet applicants by looking at patterns in resumes submitted to the company over a 10-year period. Most people Coming from men, this reflects the male dominance of the entire tech industry."
Bias in AI can manifest itself in many ways, with certain genders, groups, religions, and other affiliations wait.
While it may not be possible to completely eliminate bias in AI models, there are some strategies that can reduce bias The probability of an event occurring.
The following are three methods that must be mastered.
While there are growing concerns that smart tools will replace human workers, we should think of this as a partnership rather than an outright of takeover. Also, the notion that AI-led tools should operate without human supervision because they demonstrate considerable efficiency needs to be revised.
Interestingly, human-machine collaboration has proven to be more valuable. "Harvard Business Review"'sA study Found that 1,075 companies across 12 industries experienced improvements in speed, cost savings and profits.
Given this fact, companies should ensure that there is a human team in place to continuously monitor the software used in recruitment. They can reduce the risk of favoritism. Additionally, employees should be drawn from a diverse talent pool so that every group is represented, thereby reducing discrimination.
If the probabilistic results of artificial intelligence algorithms are not regularly checked, it may undermine the company’s anti-bias efforts A serious blow. By organizing regular checks on algorithms, businesses can identify issues that prevent models from delivering fair results. Incomplete or inaccurate data should be corrected immediately upon discovery.
Just like a car dealership, you’ll find a variety of recruiting software options. To make the right decision, make an effort to understand how the mechanisms set up by the vendor address various biases.
You should require systems to be tested under various circumstances and observe how they perform. Bias aside, check the software's scalability, price, and cost savings. A good supplier is one that meets all or most of the criteria.
The development of artificial intelligence is a good thing for all of us. From enabling cars to steer and park themselves (with a driver actively supervising) to finding and hiring qualified candidates in less time, AI is showing advantages in recruiting. However, we should manage AI technology purposefully to avoid the mistakes associated with human effort.
Cui Hao, 51CTO community editor and senior architect, has 18 years of software development and architecture experience and 10 years of distributed architecture experience.
Original title: ##Three Best Practices for Tackling AI Bias in Recruitment , Author: Michael Akuchie
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