


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%.
Dramatic improvements
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.
Artificial Intelligence in Recruitment: What You Need to Know
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.
Why does this happen? A report from Reuters shows
"...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.
Three Best Practices for Mitigating AI Bias in Recruiting
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.
1. Always Keep Humans Informed
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.
2. Conduct regular audits of artificial intelligence models
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.
3. Patronize an AI recruiting software provider and hate bias
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.
Views on the future of artificial intelligence
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.
Translator Introduction
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
The above is the detailed content of Artificial Intelligence in Recruitment? There will be bias! Three excellent practices help you get it done easily!. For more information, please follow other related articles on the PHP Chinese website!

机器学习是一个不断发展的学科,一直在创造新的想法和技术。本文罗列了2023年机器学习的十大概念和技术。 本文罗列了2023年机器学习的十大概念和技术。2023年机器学习的十大概念和技术是一个教计算机从数据中学习的过程,无需明确的编程。机器学习是一个不断发展的学科,一直在创造新的想法和技术。为了保持领先,数据科学家应该关注其中一些网站,以跟上最新的发展。这将有助于了解机器学习中的技术如何在实践中使用,并为自己的业务或工作领域中的可能应用提供想法。2023年机器学习的十大概念和技术:1. 深度神经网

本文将详细介绍用来提高机器学习效果的最常见的超参数优化方法。 译者 | 朱先忠审校 | 孙淑娟简介通常,在尝试改进机器学习模型时,人们首先想到的解决方案是添加更多的训练数据。额外的数据通常是有帮助(在某些情况下除外)的,但生成高质量的数据可能非常昂贵。通过使用现有数据获得最佳模型性能,超参数优化可以节省我们的时间和资源。顾名思义,超参数优化是为机器学习模型确定最佳超参数组合以满足优化函数(即,给定研究中的数据集,最大化模型的性能)的过程。换句话说,每个模型都会提供多个有关选项的调整“按钮

实现自我完善的过程是“机器学习”。机器学习是人工智能核心,是使计算机具有智能的根本途径;它使计算机能模拟人的学习行为,自动地通过学习来获取知识和技能,不断改善性能,实现自我完善。机器学习主要研究三方面问题:1、学习机理,人类获取知识、技能和抽象概念的天赋能力;2、学习方法,对生物学习机理进行简化的基础上,用计算的方法进行再现;3、学习系统,能够在一定程度上实现机器学习的系统。

截至3月20日的数据显示,自微软2月7日推出其人工智能版本以来,必应搜索引擎的页面访问量增加了15.8%,而Alphabet旗下的谷歌搜索引擎则下降了近1%。 3月23日消息,外媒报道称,分析公司Similarweb的数据显示,在整合了OpenAI的技术后,微软旗下的必应在页面访问量方面实现了更多的增长。截至3月20日的数据显示,自微软2月7日推出其人工智能版本以来,必应搜索引擎的页面访问量增加了15.8%,而Alphabet旗下的谷歌搜索引擎则下降了近1%。这些数据是微软在与谷歌争夺生

荣耀的人工智能助手叫“YOYO”,也即悠悠;YOYO除了能够实现语音操控等基本功能之外,还拥有智慧视觉、智慧识屏、情景智能、智慧搜索等功能,可以在系统设置页面中的智慧助手里进行相关的设置。

人工智能在教育领域的应用主要有个性化学习、虚拟导师、教育机器人和场景式教育。人工智能在教育领域的应用目前还处于早期探索阶段,但是潜力却是巨大的。

阅读论文可以说是我们的日常工作之一,论文的数量太多,我们如何快速阅读归纳呢?自从ChatGPT出现以后,有很多阅读论文的服务可以使用。其实使用ChatGPT API非常简单,我们只用30行python代码就可以在本地搭建一个自己的应用。 阅读论文可以说是我们的日常工作之一,论文的数量太多,我们如何快速阅读归纳呢?自从ChatGPT出现以后,有很多阅读论文的服务可以使用。其实使用ChatGPT API非常简单,我们只用30行python代码就可以在本地搭建一个自己的应用。使用 Python 和 C

人工智能在生活中的应用有:1、虚拟个人助理,使用者可通过声控、文字输入的方式,来完成一些日常生活的小事;2、语音评测,利用云计算技术,将自动口语评测服务放在云端,并开放API接口供客户远程使用;3、无人汽车,主要依靠车内的以计算机系统为主的智能驾驶仪来实现无人驾驶的目标;4、天气预测,通过手机GPRS系统,定位到用户所处的位置,在利用算法,对覆盖全国的雷达图进行数据分析并预测。


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

DVWA
Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

WebStorm Mac version
Useful JavaScript development tools

SublimeText3 Linux new version
SublimeText3 Linux latest version
