Recruit CRM

recruitcrm

How to Solve the Acute Skill Shortage of Highly Skilled AI/ML Workers

Meet SwissDevJobs.ch SwissDevJobs.ch is transforming the IT job market in Switzerland by offering a platform designed specifically for software engineers and IT professionals. Our mission is to connect talented developers with exciting job opportunities across a wide range of technologies and cities in Switzerland. How SwissDevJobs Achieved product-Market Fit SwissDevJobs.ch has successfully achieved product-market fit by addressing the unique needs of software engineers. Our platform not only categorizes jobs by specific technology and location but also offers resources tailored to developers. These include salary statistics, a directory of developer-focused communities, and even an event calendar. Additionally, every job listing features salary brackets, ensuring complete transparency from day one. Milestones and Achievements Since its launch, SwissDevJobs.ch has reached several significant milestones. One of the early achievements was building a strong network of reputable Swiss companies that trust the platform to connect them with top IT talent. This has helped expand the platform’s database to hundreds of job listings across diverse technologies like Java, Python, and DevOps, making it a one-stop shop for developers looking to advance their careers. A major milestone came with the release of the “Transparent IT Job Market Report”, an in-depth analysis that offers insights into IT salaries and hiring trends across Switzerland. This report provides developers and companies with a clear understanding of the job market, helping both sides make informed decisions. It reflects SwissDevJobs.ch’s commitment to transparency and data-driven solutions. Another key achievement was the launch of our mobile app (iOS and Android), enabling users to browse job listings, check salary information, and apply for roles on the go. The app has made it easier than ever for IT professionals to stay connected with the latest opportunities, providing a seamless experience across devices. In addition to these accomplishments, we recently introduced RecruIT, a new tech recruiting insights brand. Designed for recruiters, HR professionals, and anyone involved in IT hiring, RecruIT offers valuable knowledge and tools for reaching candidates more effectively. The platform’s growth in user base has been exponential as well. SwissDevJobs.ch now serves tens of thousands of developers and IT professionals each month, making it one of Switzerland’s leading job platforms for the tech community. The addition of a robust event calendar and developer community directory has also enhanced the platform, making it a valuable resource beyond just job searches. Lessons Learned Building SwissDevJobs.ch hasn’t come without its challenges. One of the early lessons learned was the importance of maintaining a developer-first approach. By continuously gathering feedback from the tech community, the platform has evolved to meet their expectations, whether it’s through refining the user experience or adding relevant features like filtering jobs by remote options. Another key lesson was understanding the power of transparency. Developers value openness, especially when it comes to salary information, which has been part of the platform’s DNA since day one. While some companies were initially hesitant to disclose salary ranges, SwissDevJobs.ch held firm on this requirement. This approach ultimately built trust between employers and job seekers, resulting in better job matches and a smoother hiring process. Moreover, scaling the platform while maintaining a strong focus on quality has been critical. SwissDevJobs.ch has learned that providing a curated list of jobs, rather than overwhelming users with thousands of generic listings, leads to better engagement and a more satisfying user experience. Conclusion SwissDevJobs.ch has made a significant impact on the IT job market in Switzerland by focusing on transparency, developer-centric features, and continuous innovation. From its early commitment to salary transparency to launching a mobile app and insightful market reports, the platform has established itself as a go-to resource for IT professionals. As it continues to evolve, SwissDevJobs.ch remains dedicated to connecting developers with the best opportunities and setting new standards in the recruitment landscape. Meet SwissDevJobs.ch SwissDevJobs.ch is transforming the IT job market in Switzerland by offering a platform designed specifically for software engineers and IT professionals. Our mission is to connect talented developers with exciting job opportunities across a wide range of technologies and cities in Switzerland. SwissDevJobs.ch How SwissDevJobs Achieved product-Market Fit SwissDevJobs.ch has successfully achieved product-market fit by addressing the unique needs of software engineers. Our platform not only categorizes jobs by specific technology and location but also offers resources tailored to developers. These include salary statistics , a directory of developer-focused communities , and even an event calendar . Additionally, every job listing features salary brackets, ensuring complete transparency from day one. salary statistics directory of developer-focused communities event calendar Milestones and Achievements Milestones and Achievements Since its launch, SwissDevJobs.ch has reached several significant milestones. One of the early achievements was building a strong network of reputable Swiss companies that trust the platform to connect them with top IT talent. This has helped expand the platform’s database to hundreds of job listings across diverse technologies like Java, Python, and DevOps, making it a one-stop shop for developers looking to advance their careers. A major milestone came with the release of the “Transparent IT Job Market Report” , an in-depth analysis that offers insights into IT salaries and hiring trends across Switzerland. This report provides developers and companies with a clear understanding of the job market, helping both sides make informed decisions. It reflects SwissDevJobs.ch’s commitment to transparency and data-driven solutions. “ Transparent IT Job Market Report ” Transparent IT Job Market Report Another key achievement was the launch of our mobile app ( iOS and Android ), enabling users to browse job listings, check salary information, and apply for roles on the go. The app has made it easier than ever for IT professionals to stay connected with the latest opportunities, providing a seamless experience across devices. mobile app iOS Android In addition to these accomplishments, we recently introduced RecruIT , a new tech recruiting insights brand. Designed for recruiters, HR professionals, and anyone involved in IT hiring, RecruIT offers valuable knowledge and tools for reaching candidates more effectively. RecruIT RecruIT The platform’s growth in user base has been exponential as well. SwissDevJobs.ch now serves tens of thousands of developers and IT professionals each month, making it one of Switzerland’s leading job platforms for the tech community. The addition of a robust event calendar and developer community directory has also enhanced the platform, making it a valuable resource beyond just job searches. Lessons Learned Lessons Learned Building SwissDevJobs.ch hasn’t come without its challenges. One of the early lessons learned was the importance of maintaining a developer-first approach. By continuously gathering feedback from the tech community, the platform has evolved to meet their expectations, whether it’s through refining the user experience or adding relevant features like filtering jobs by remote options. Another key lesson was understanding the power of transparency. Developers value openness, especially when it comes to salary information, which has been part of the platform’s DNA since day one. While some companies were initially hesitant to disclose salary ranges, SwissDevJobs.ch held firm on this requirement. This approach ultimately built trust between employers and job seekers, resulting in better job matches and a smoother hiring process. Moreover, scaling the platform while maintaining a strong focus on quality has been critical. SwissDevJobs.ch has learned that providing a curated list of jobs, rather than overwhelming users with thousands of generic listings, leads to better engagement and a more satisfying user experience. Conclusion Conclusion SwissDevJobs.ch has made a significant impact on the IT job market in Switzerland by focusing on transparency, developer-centric features, and continuous innovation. From its early commitment to salary transparency to launching a mobile app and insightful market reports, the platform has established itself as a go-to resource for IT professionals. As it continues to evolve, SwissDevJobs.ch remains dedicated to connecting developers with the best opportunities and setting new standards in the recruitment landscape.

How SwissDevJobs.ch is Revolutionizing IT Recruitment in Switzerland

Table of Links Abstract and 1 Introduction 1.1 The twincode platform 1.2 Related Work 2 Research Questions 3 Variables 3.1 Independent Variables 3.2 Dependent Variables 3.3 Confounding Variables 4 Participants 5 Execution Plan and 5.1 Recruitment 5.2 Training and 5.3 Experiment Execution 5.4 Data Analysis Acknowledgments and References 5 EXECUTION PLAN We plan to perform a baseline experiment at the University of Seville in the first semester of the 2021–2022 academic course, and then, replicate the experiment at the University of California Berkeley at the beginning of the second semester. At each location, the experimental material provided to the students will be localized, i.e., in Spanish in Spain and in English at the USA, and the translation will be carefully checked by bilingual experimenters.[1] Independently of being the baseline or the replication, the execution plan of the twincode study consists of the steps described below. 5.1 Recruitment In this initial step, we plan to motivate the students to voluntarily participate in the study as an interesting experience in remote pair programming but without mentioning that the main goal is to study the effect of gender bias. We also remark that for the purpose of the study, they must remain anonymous to their partners, so they must neither mention nor ask any personal information. The interested students must register in the twincode platform providing some demographic data and accepting the participation conditions. Authors:
(1) Amador Durán, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (amador@us.es);
(2) Pablo Fernández, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (pablofm@us.es);
(3) Beatriz Bernárdez, I3US Institute, Universidad de Sevilla, Sevilla, Spain (beat@us.es);
(4) Nathaniel Weinman, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (nweinman@berkeley.edu);
(5) Aslı Akalın, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (asliakalin@berkeley.edu);
(6) Armando Fox, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (fox@berkeley.edu). This paper is available on arxiv under CC BY 4.0 DEED license. [1] At the time of writing, discussions are underway for another replication at the Northern Technical University at Ecuador. If this replication is eventually carried out, the experimental material will also be adapted to the local variant of Spanish if deemed necessary. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 1.1 The twincode platform 1.1 The twincode platform 1.2 Related Work 1.2 Related Work 2 Research Questions 2 Research Questions 3 Variables 3 Variables 3.1 Independent Variables 3.1 Independent Variables 3.2 Dependent Variables 3.2 Dependent Variables 3.3 Confounding Variables 3.3 Confounding Variables 4 Participants 4 Participants 5 Execution Plan and 5.1 Recruitment 5 Execution Plan and 5.1 Recruitment 5.2 Training and 5.3 Experiment Execution 5.2 Training and 5.3 Experiment Execution 5.4 Data Analysis 5.4 Data Analysis Acknowledgments and References Acknowledgments and References 5 EXECUTION PLAN We plan to perform a baseline experiment at the University of Seville in the first semester of the 2021–2022 academic course, and then, replicate the experiment at the University of California Berkeley at the beginning of the second semester. At each location, the experimental material provided to the students will be localized, i.e., in Spanish in Spain and in English at the USA, and the translation will be carefully checked by bilingual experimenters.[1] Independently of being the baseline or the replication, the execution plan of the twincode study consists of the steps described below. 5.1 Recruitment In this initial step, we plan to motivate the students to voluntarily participate in the study as an interesting experience in remote pair programming but without mentioning that the main goal is to study the effect of gender bias. We also remark that for the purpose of the study, they must remain anonymous to their partners, so they must neither mention nor ask any personal information. The interested students must register in the twincode platform providing some demographic data and accepting the participation conditions. Authors: (1) Amador Durán, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (amador@us.es); (2) Pablo Fernández, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (pablofm@us.es); (3) Beatriz Bernárdez, I3US Institute, Universidad de Sevilla, Sevilla, Spain (beat@us.es); (4) Nathaniel Weinman, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (nweinman@berkeley.edu); (5) Aslı Akalın, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (asliakalin@berkeley.edu); (6) Armando Fox, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (fox@berkeley.edu). Authors: Authors: (1) Amador Durán, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (amador@us.es); (2) Pablo Fernández, SCORE Lab, I3US Institute, Universidad de Sevilla, Sevilla, Spain (pablofm@us.es); (3) Beatriz Bernárdez, I3US Institute, Universidad de Sevilla, Sevilla, Spain (beat@us.es); (4) Nathaniel Weinman, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (nweinman@berkeley.edu); (5) Aslı Akalın, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (asliakalin@berkeley.edu); (6) Armando Fox, Computer Science Division, University of California, Berkeley, Berkeley, CA, USA (fox@berkeley.edu). This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv [1] At the time of writing, discussions are underway for another replication at the Northern Technical University at Ecuador. If this replication is eventually carried out, the experimental material will also be adapted to the local variant of Spanish if deemed necessary.

Twincode Execution Plan and Recruitment

The software-as-a-service (SaaS) industry is always evolving, so it only makes sense that your recruitment efforts evolve alongside the dynamic landscape. With an artificial intelligence boom gaining momentum, finding those all-important right hires has never been easier. The global SaaS market is expected to reach a value of $829.34 billion by 2031, representing a CAGR of 13.7%. In an industry that’s set for exponential growth, finding and onboarding the right hires is of the utmost importance. Discovering and hiring the right talent for your SaaS business can be filled with inefficiencies, and this is where AI enters the fray. According to ArtSmart data, 88% of companies now incorporate AI into their hiring and HR processes. Additionally, 78.3% claimed that AI improved the quality of hires. But how is the AI boom driving innovation in SaaS recruitment? Let’s explore how technology is causing a fundamental shift in how the best hires are identified and onboarded: Generative Listings While HR or in-house recruiters would have to craft job descriptions, manually post listings, and analyze CVs themselves, generative AI has paved the way for large-language models (LLMs) to pick up the slack and offer more effective summaries and recommendations. Generative AI brings many perks to the recruitment process. In terms of text extraction, summary, and recommendations, GenAI can analyze and extract key information from CVs to build straightforward summaries for ease of reference and even generate intelligent recommendations. Generative AI can also help to automatically write job descriptions and post listings in seconds while ensuring accuracy and a high level of detail. For larger SaaS companies that have hundreds of employees, generative AI can be a real time-saving force. Machine Learning Insights While generative AI can automate the job listing process, artificial intelligence can also combine with machine learning to uncover powerful data-driven insights that can aid the recruitment process. With the ability of machine learning to analyze the competencies, experience, and skills of thousands of CVs and cover letters in a matter of minutes, HR professionals can be provided with a focused shortlist of applicants who match the requirements without losing hours scanning irrelevant applications. Additionally, the functionality of LLMs in analyzing natural language more effectively can help avoid scenarios where strong applicants are missed by the AI through oversights. These insights can be utilized alongside external candidate assessment tools at an international level that focus on extracting and appropriating soft skills, cultural alignment, and technical competencies for a more holistic view of the talent pool at your disposal. With many businesses tasked with looking to the international talent pool for key SaaS roles, these integrations can be a major time-saving measure. Elimination of Bias Sadly, unconscious bias is difficult to manage in the recruitment process. However, AI tools can help prevent SaaS firms from losing out on key talent because of bias by screening candidates without the need for human intervention. Using AI to overcome unconscious bias helps SaaS firms boost their diversity and inclusivity while offering every candidate a fair screening experience. With AI naturally adding objectivity to the selection process, businesses can use a greater pool of talent without any applicants being unfairly overlooked. Artificial intelligence also semi-automates candidate screening by removing personal details, profile pictures, and other identifiers for applicants, leaving recruiters to assess CVs or recommendations based on skills, experience, and business culture fit alone. Challenges Remain While there are plenty of benefits for applicants, the use of automation tools can cause candidates to feel more disconnected from the process and struggle to showcase their skills effectively as a result. Company culture fits can also be more challenging for artificial intelligence to interpret, and an autonomous or semi-autonomous screening process could lead to applicants with exceptional intangible qualities failing to make it to the shortlist despite being a suitable fit. This calls for a measured approach to the implementation of AI and generative AI solutions when recruiting for SaaS roles. \One possible solution could be to host more informal interviews either in-person or remotely earlier in the recruitment process to ensure that the AI hasn’t unfairly marked a candidate lower despite strong suitability because of difficulties in judging intangible qualities like motivation, adaptability, and communication skills. The Path to Fair Recruitment Data-rich industries like recruitment will benefit heavily from the rise of AI and generative AI in the future. As algorithms become more intelligent and the industry continues to grow, SaaS firms can excel in discovering and onboarding the best talent from a larger pool of candidates without the dangers of unconscious bias and high time consumption seeping into the process. By building a fair recruitment environment, businesses will benefit from a more accurate and effective hiring process, helping to drive better operational performance and long-term growth along the way. The software-as-a-service (SaaS) industry is always evolving, so it only makes sense that your recruitment efforts evolve alongside the dynamic landscape. With an artificial intelligence boom gaining momentum, finding those all-important right hires has never been easier. software-as-a-service (SaaS) industry The global SaaS market is expected to reach a value of $829.34 billion by 2031, representing a CAGR of 13.7%. In an industry that’s set for exponential growth, finding and onboarding the right hires is of the utmost importance. value of $829.34 billion value of $829.34 billion Discovering and hiring the right talent for your SaaS business can be filled with inefficiencies, and this is where AI enters the fray. According to ArtSmart data, 88% of companies now incorporate AI into their hiring and HR processes. Additionally, 78.3% claimed that AI improved the quality of hires. 88% of companies 88% of companies But how is the AI boom driving innovation in SaaS recruitment? Let’s explore how technology is causing a fundamental shift in how the best hires are identified and onboarded: Generative Listings While HR or in-house recruiters would have to craft job descriptions, manually post listings, and analyze CVs themselves, generative AI has paved the way for large-language models (LLMs) to pick up the slack and offer more effective summaries and recommendations . effective summaries and recommendations effective summaries and recommendations Generative AI brings many perks to the recruitment process. In terms of text extraction, summary, and recommendations, GenAI can analyze and extract key information from CVs to build straightforward summaries for ease of reference and even generate intelligent recommendations. Generative AI Generative AI can also help to automatically write job descriptions and post listings in seconds while ensuring accuracy and a high level of detail. For larger SaaS companies that have hundreds of employees, generative AI can be a real time-saving force. Machine Learning Insights While generative AI can automate the job listing process, artificial intelligence can also combine with machine learning to uncover powerful data-driven insights that can aid the recruitment process. With the ability of machine learning to analyze the competencies , experience, and skills of thousands of CVs and cover letters in a matter of minutes, HR professionals can be provided with a focused shortlist of applicants who match the requirements without losing hours scanning irrelevant applications. analyze the competencies analyze the competencies Additionally, the functionality of LLMs in analyzing natural language more effectively can help avoid scenarios where strong applicants are missed by the AI through oversights. These insights can be utilized alongside external candidate assessment tools at an international level that focus on extracting and appropriating soft skills, cultural alignment, and technical competencies for a more holistic view of the talent pool at your disposal. With many businesses tasked with looking to the international talent pool for key SaaS roles, these integrations can be a major time-saving measure. international talent pool international talent pool Elimination of Bias Sadly, unconscious bias is difficult to manage in the recruitment process. However, AI tools can help prevent SaaS firms from losing out on key talent because of bias by screening candidates without the need for human intervention. unconscious bias Using AI to overcome unconscious bias helps SaaS firms boost their diversity and inclusivity while offering every candidate a fair screening experience. With AI naturally adding objectivity to the selection process, businesses can use a greater pool of talent without any applicants being unfairly overlooked. Artificial intelligence also semi-automates candidate screening by removing personal details , profile pictures, and other identifiers for applicants, leaving recruiters to assess CVs or recommendations based on skills, experience, and business culture fit alone. removing personal details removing personal details Challenges Remain While there are plenty of benefits for applicants, the use of automation tools can cause candidates to feel more disconnected from the process and struggle to showcase their skills effectively as a result. more disconnected more disconnected Company culture fits can also be more challenging for artificial intelligence to interpret, and an autonomous or semi-autonomous screening process could lead to applicants with exceptional intangible qualities failing to make it to the shortlist despite being a suitable fit. This calls for a measured approach to the implementation of AI and generative AI solutions when recruiting for SaaS roles. \One possible solution could be to host more informal interviews either in-person or remotely earlier in the recruitment process to ensure that the AI hasn’t unfairly marked a candidate lower despite strong suitability because of difficulties in judging intangible qualities like motivation, adaptability, and communication skills. The Path to Fair Recruitment Data-rich industries like recruitment will benefit heavily from the rise of AI and generative AI in the future . As algorithms become more intelligent and the industry continues to grow, SaaS firms can excel in discovering and onboarding the best talent from a larger pool of candidates without the dangers of unconscious bias and high time consumption seeping into the process. generative AI in the future By building a fair recruitment environment, businesses will benefit from a more accurate and effective hiring process, helping to drive better operational performance and long-term growth along the way.

How the AI Boom is Delivering Unprecedented Innovation in SaaS Recruitment

কিভাবে AI বুম SaaS নিয়োগে অভূতপূর্ব উদ্ভাবন প্রদান করছে

Wie der KI-Boom beispiellose Innovationen bei der SaaS-Rekrutierung hervorbringt

Cómo el auge de la IA está generando una innovación sin precedentes en la contratación de SaaS

Comment le boom de l'IA génère une innovation sans précédent dans le recrutement SaaS

कैसे AI बूम SaaS भर्ती में अभूतपूर्व नवाचार प्रदान कर रहा है

AIブームがSaaS採用に前例のないイノベーションをもたらす方法

AI 붐이 SaaS 채용에 전례 없는 혁신을 제공하는 방법

Como o boom da IA está proporcionando inovação sem precedentes no recrutamento de SaaS

Как бум искусственного интеллекта обеспечивает беспрецедентные инновации в сфере SaaS-рекрутинга

AI Boom, SaaS İşe Alımlarında Nasıl Eşsiz Yenilik Sağlıyor?

Sự bùng nổ AI đang mang lại sự đổi mới chưa từng có trong tuyển dụng SaaS như thế nào

人工智能热潮如何为 SaaS 招聘带来前所未有的创新

From placing attention-grabbing job ads to screening thousands of potential candidates for various positions, web3 recruitment agencies significantly contribute to the growth of the web3 job market. , the founder of Owen Healy Blockchain Talent and a leading pioneer in blockchain recruitment, recently sat down with Olayimika Oyebanji for a discussion about web3 recruitment and its challenges. Owen Healy Owen, what were you doing before you ventured into Web 3? Before working in blockchain recruitment, I worked in HR for several years.  Through that, I gained a lot of experience building teams ‘in-house’ e.g. getting budgets approved, scanning resumes, conducting interviews, reference checking etc. It was one aspect of HR that I really enjoyed, but I never once thought of becoming an agency recruiter. To be honest, at the time, I found agency recruiters repulsive. I avoided them as much as possible, both as a candidate and hiring manager.  However, during the pandemic, I found myself unemployed with few options at my disposal and that was what kickstarted my career in blockchain recruitment. I was fascinated by the underlying tech and how Bitcoin could radically improve the lives of billions across the globe. I remember stumbling across Bitcoin when randomly googling ‘internet money’ and within minutes, I was hooked. Ever since, I’ve always had a ‘fix the money, fix the world’ mindset. The problem was that I did not really know how I could join the industry full-time. Similarly, as I was not a developer or a marketer; I didn’t really know how I could make an impact. Then, during the pandemic when I had more time on my hands,  I started to connect with people on LinkedIn who I believed could help me. Things sort of took off from there. I joined the space at the beginning of 2021 just as the VC money started flowing into the space. One of the toughest challenges for people making a career transition is getting started. What would you say to anyone looking to join the space? Yes, I understand. It can be daunting at first. I was in the same situation a few years ago. The market is slowly picking up, but on the whole, the past year has been grim for web3 jobseekers. There are fewer roles and it’s very much an employer-driven market. A lot of people with exceptional ‘web3’ experience are unemployed through no fault of their own, struggling to find a new opportunity. Trust me,  if you are in a ‘web2’ role that you enjoy and are getting well paid, there are a lot of ‘web3 rockstars’ envious of your position. Therefore, to those looking to commit full-time to web3, I would say explore it first,educate yourself, join a DAO, network with people in the industry, help bootstrapped entrepreneurs pro-bono etc. Most importantly, dip your toe in the water and decide whether or not this space is for you. For anyone exploring the space with a view to working in it full-time,  I would say find an ecosystem that particularly interests you, network with people deeply involved in that ecosystem and showcase your talent by assisting one or two early-stage projects within that ecosystem pro-bono. It may only be for an hour or two each week. In doing so, you will quickly build credibility within that ecosystem and from there opportunities will arise. Most roles in the space are filled via word of mouth so the saying ‘your network is your net worth’ couldn’t be more valid. From an educational perspective, I would advise anyone that is crypto-curious to complete the University of Nicosia’s Digital Currency course. It's a free 12-week program perfect for newbies.  By completing that, you’re highlighting a genuine proof of interest to prospective employers.  I understand the next intake is sometime next month,what I would recommend people do is embrace the power of LinkedIn. It is a wonderful networking and personal branding tool. If you use it correctly, you will find that it will open a lot of doors for you. Another recommendation I would share is to attend any web3 meet-ups or hackathons in your area. You can’t beat meeting people IRL especially if you’re a so-called ‘hidden gem’. Is it more difficult to get a job in Web 3 than in Web 2? That's true to an extent. What we refer to as ‘web3’ is just getting started. In fact, there are more developers working at some corporations than there are monthly active web3 developers. In the grand scheme of things, the blockchain scene is still relatively small. If you are a cryptographer or rust developer you will have no problem switching from web2 to web3, but for most professionals, it’s significantly more difficult. There is a learning curve too. Whether you are an experienced web2 marketer or developer, the playbook in web3 is often completely different. That said,  I do feel that some web3 projects can be very narrow-minded when hiring. Some fail to appreciate how skills gained in web2 can be applied in web3. Of course, the bear market is not helping things either. The past 8-9 months have been brutal. There have been numerous high-profile layoffs. Competition for jobs is fierce, especially across non-technical disciplines and salaries in areas such as marketing and design have taken a significant hit. What is different about hiring in web3? I would say that roles are generally filled quicker. Additionally,  most teams operate on a fully remote basis so employers generally don’t mind where one is located so long as there is no significant disparity in timezone. I guess, from a personal perspective, I would say that having a good grasp of the underlying technology is imperative. Developers, in particular, seem to appreciate you the more if you are able to ask decent follow-up questions. Moreover, a lot of these senior blockchain developers are already ETH rich so many of them are not in a rush. In order to arouse their interest, you really need to know a lot about your client’s product offering and roadmap when speaking to them. What is the biggest challenge in web3 hiring? Where do I start?! All in all, you need to have a good BS detector. You meet a lot of spoofers. For example, I recently spoke to someone looking for a DeFi Engineer. There was no website so when I asked for details about the project, they weren’t prepared to share any information about what they were building nor were they willing to comment on who was funding them so I politely said ‘I can’t help you’. Similarly, you also need to know how professional your client is about hiring. You don't want to be working with a project that sends dozens of candidates through 7/8  rounds of interviews. It leaves a bad taste in the mouth of candidates and naturally, they will be reluctant to work with you on other roles. As I said, your network is your net worth and you can’t jeopardize the trust of that network. Web3 is a tight-knit industry and I have found that integrity goes a long way. I guess from a recruitment perspective, I stopped using Telegram and Discord some time ago. Both platforms are littered with Lazarus Group developers. And lastly, you need to be extremely passionate about what you do. I’m loving it so far and have been lucky enough to hire 77 people from 31 different countries, but it’s not been easy. I’m constantly working and I’m realistic enough to appreciate that it's not sustainable long-term. I plan on bulking up my team over the coming months so hopefully, once they are settled in I’ll be able to find some more ‘me time’. How is blockchain going to transform the world? How long do you have?! Let’s just say, we’re in for an interesting couple of years.

Popular Web3 Recruiter Owen Healy Shares His Insights Into The Blockchain Job Market

Gen Z is transforming the modern workplace.  Compared to other generations, Gen Z is joining the workforce earlier, and will .  Additionally, job transitions for Gen Z are up 80% year over year, revealing the ways in which the generation is exploring early careers.  What does this mean for hiring professionals and the future of the workplace? make up 30% of the workforce by 2030 Currently, hiring professionals are struggling to , with one in two hiring managers having trouble connecting with early-career employees.  This lack of connection leaks into the overall employee base; organizations struggle to integrate Gen Z into established office communities. recruit and retain Gen Z The hiring gap that faces is due to several reasons. Gen Z For starters, COVID-19 pushed young workers aside; Gen Z workers suffered a 79% increase in layoffs and a 73% increase in furloughs compared to other generations.  Additionally, excessive conflict exists within the workplace, usually resulting from negative headlines that target generational differences.  This causes tension between various groups within a workplace and pushes many Gen Z’ers to renege on current job offers.  Finally, the expectations that Gen Z’ers bring to work often do not align with their employers, resulting in confusion, dissatisfaction, and high turnover rates. These early-career turnover rates do not just impact the individual in question; they also affect the company, impacting time expenditures, monetary costs, and future prospects.  For example, it takes an average of 42 days to complete the recruitment process, which means positions are often unstaffed for over a month during the job search.  High turnover rates lead to more stretches of unstaffed positions, which can harm companies. Early-career turnovers are common, but often preventable. Hiring managers can implement several goals to reduce turnover rates.  The first step is to establish clear expectations with new employees.  This is arguably the most important thing hiring managers can do; 98% of Gen Z employees agree that clear expectations are important in the workplace.  This can lead to higher levels of mental and emotional stability in the office. The second step is to create genuine transparency.  This includes clear responsibilities and goals, as well as significant one on one check-ins with supervisors.  Salary transparency is especially key; in fact, it has the number one influence on job decisions, and 52% of Gen Z’ers wouldn’t accept a job without salary transparency. Hiring managers should also offer workplace respect.  This promotes positive mental health and encourages Gen Z to stay with a company long-term.  Respect entails a healthy work-life balance and demonstrations that employers value their employees’ work. Another solution is to develop strong connections.  45% of Gen Z’ers want to know their coworkers outside of work.  This can lead to stronger professional growth and connection.  Connections should grow between team members, supervisors, and other new hires. Finally, intentional communication can go a long way.  51% of Gen Z’ers want clear and concise information when learning about a job.  Gen Z also wants timely communication after interviews.  Ensuring communication during the hiring process can demonstrate a company’s commitment to communication day-in and day-out. While there are several obstacles to Gen Z entering the workforce, there are also many ways that hiring managers can adapt.  The workforce is changing, requiring new perspectives, values, and connections.

The Inside Scoop on Gen Z Recruitment and Retention

La primicia interna sobre el reclutamiento y la retención de Gen Z

Le scoop sur le recrutement et la rétention de la génération Z

जनरल जेड भर्ती और प्रतिधारण पर इनसाइड स्कूप

Z世代の採用と定着に関する内部スクープ

Informações privilegiadas sobre recrutamento e retenção da Geração Z

Thông tin nội bộ về tuyển dụng và giữ chân Gen Z

Z 世代招聘和保留的内幕消息

In my years of experience, I’ve seen firsthand how the rise of has transformed the way the recruitment industry operates. It has now become possible to collect public web data from online sources (thanks, Internet) and these sources provide invaluable information about candidates. big data However, that’s not all. You can also get incredible amounts of data and ingest it into your platform, creating data-driven products with huge potential, only limited by your creativity. In this article, I will deep-dive into the benefits and importance of using public web data for recruitment platforms. After reading this article, you will know the main steps involved in building or substantially improving a recruitment platform. Navigating your data needs First things first, let’s talk about identifying your data needs. Public web data is great, but it branches out to so many different options that it’s easy to get lost. For recruitment platforms specifically, I’d recommend looking into the following. Firmographic data Firmographics will provide you with the main characteristics of companies, such as industry, size, location, revenue, and more. This type of data is beneficial if you want to tailor your recruitment platform to specific industries or company types. Example A recruitment platform that specializes in the technology industry can use firmographics to create tailored company profiles and job recommendations for software developers. For instance, it can filter out job postings from established tech companies like , Amazon, and and present these jobs to job seekers with relevant skills and experience. Google Microsoft Employee data Employee data will provide you with information about professionals, such as experience, skills, location, education, job title, and more. This data will help you create and fine-tune your pool of candidates. It will ensure that the candidates you provide are truly the best-fit talent for the employers. Let’s say your client has an employee that is so extraordinary that the management can’t wait to find another one just like them. You can build a unique candidate model that consists of the skills, experience, education, and other qualities that the employee has. Then, using employee data, you can compare that model to the millions of profiles to see what pops out. And if you manage to provide your client with extraordinary talent, what better way is there to retain clients? Example A recruitment platform can analyze thousands of resumes of marketing professionals and gather insights into the most common skills, experiences, and tenure of these employees. This data, in turn, helps the platform tailor the candidate profiles that would be the best match for your client. It can anticipate future hiring needs and help you propose a long-term hiring strategy. Also, a platform fueled with millions of employee records can help you enable the automation of candidate screening. Job posting data Job posting data will provide you with information about job openings, job descriptions, requirements, technological capacities, and overall job market trends. This data will help you improve job matching and provide insights into market dynamics. Example A recruitment platform can analyze job postings to identify the most popular job titles, skills, and requirements in the data science field. This data can help provide personalized job recommendations to data scientists at companies that require expertise in machine learning, data visualization, big data processing, or more. Combining several data categories You don’t have to use the data categories individually. You absolutely can combine them and make your recruitment platform even better and more sophisticated. By doing so, you can benefit from all the features of these separate datasets and build a product that’s hard to beat. For example, there are recruitment platforms that can help customers source talent, evaluate it, automate some processes, and even help with onboarding. That’s a relatively long journey and if your product can help with a big part of it, you’re on the right track. All in all, there are more types of data that would further benefit your recruitment platforms, such as user behavior data, feedback data, and more. However, I recommend these 3 as the cornerstones of your data-driven product. How to get the data? Now you know the data that you need for your recruitment platform. But where do you get it? Well, there are 2 main ways you can go about it: scrape it yourself or buy from a data provider. You might be wondering which one is better, and that’s a fair question. It all depends on your goals. If you need a small amount of data that you won’t need to refresh, then it may be cheaper for you to scrape it. However, if you need data that is always fresh and ready to use, then it’s a lot more cost-effective to get the data from a data provider. No matter the scale. “It's safe to say that most companies that work with web data create the most value in the data analysis stage. Therefore, you may be better off concentrating on working with the data, rather than working on getting it.” - Laurynas Gruzinskas, Coresignal’s Head of Product Data from providers is relatively expensive, yes, but once you find a trustworthy provider, you can always know that the data you use is fresh, accurate, and useful. And it will allow your business to generate more value than it costs. Now that all the formalities are out of the way and you know the data that you need and where to get it, let’s see how you can put it to use. What should you keep in mind when developing your recruitment platform? In this section, I will provide you with several advices while building (or improving) a recruitment platform. However, I haven’t built any recruitment platforms myself, so this is only a rudimentary logic around building the platform. It’s more about the things you need to keep in mind and tips that would help make your recruitment platform better. H ere are 10 things you should focus on: Identify the industries, job titles, and company types that your recruitment platform will deliver talent to. It will help you focus on the right data and tailor talent solutions to your target audience. Define your target audience. Use scrapers or data providers to get the data that you need. Collect the data. If you scraped it yourself, you will definitely need to spend some time on this step. If you relied on a data provider, you might be able to skip it, depending on the data you got. However, you still need to dig deeper into the underlying logic of data cleaning procedures, check what portion of the data has been cleaned and how much cleaning you still have to do yourself. Also, in terms of data structure, you need to figure out how it connects with your existing data, how it can be mapped, and other aspects that are relevant to you. Clean and structure the data (if needed). Identify trends, patterns, and insights that can help you improve the platform. You can analyze job postings, for example, to determine the most popular skills in your target industry or the most in-demand job roles. Analyze the data. Next, you need to develop matching algorithms that connect jobs with candidates. Consider data points like skills, experience, location, education, and other relevant factors. Develop matching algorithms. Your product is only as good as it is easy to use. Work on simplifying complex interfaces so users find it intuitive and easy to understand. Design a user-friendly interface. Feedback allows you to improve your platform based on direct comments from your users. You can also implement feedback mechanisms on companies as well so you can later filter out the best companies based on people’s choices. Integrate feedback mechanisms. If you’re getting the data from a provider, it’s highly likely that they will take care of legal matters. If not, then you must adhere to GDPR and CCPA regulations to avoid trouble. Ensure data privacy compliance. Launch a beta version first for the early users. Test, test, and test to improve your platform and rid it of any annoying bugs. Test and iterate. Track KPIs such as time-to-fill, quality of hire, cost-per-hire, and more to assess the success of your recruitment platform. These indicators will also serve as good marketing material. Measure success and adapt. I hope you can put all this advice to good use and get your recruitment platform to a whole other level. To sum up Public web data is a powerful tool that can transform your recruitment platform and bring it to new heights. High-quality matching will bring better talent to the employers while saving expenses at the same time. Especially when nowadays the . cost of a bad hire can go up to $240,000 By leveraging public web data, you can help employers cut these costs and minimize the chances of bad hires in general. And that’s one of the ways to build long-lasting relationships with your clients. Also published here.

How to Build or Transform Recruitment Platforms Using Web Data?

AI has made a significant impact on numerous industries, revolutionizing the way businesses operate, innovate, and solve problems. One such area experiencing a significant transformation is HR and with it, of course, recruitment. In today's competitive business landscape, are crucial for organizations to stay ahead of the curve. efficient and effective HR and recruitment practices The AI-driven recruitment revolution is changing the game by leveraging the power of machine learning and natural language processing to streamline the hiring process and improve the candidate experience. Ultimately, organizations that employ these strategies will be able to while increasing new employee success rates. reduce hiring expenses Let’s explore the evolution of AI in recruitment, the key technologies driving these changes, and the benefits of AI-driven recruitment. I’ll also touch on the challenges and ethical considerations that come with it. As AI continues to evolve and become more sophisticated, it is essential for C-level executives to understand and embrace the potential of AI when hiring. AI & HR: Humble Beginnings The journey of AI in recruitment began with the development of applicant tracking systems (ATS). These early AI tools automated the process of collecting and organizing candidate information, simplifying resume management, and tracking the progress of applicants through the hiring pipeline. While the initial versions of ATS offered limited AI functionality, they laid the groundwork for more advanced AI applications in recruitment. Advancements in Natural Language Processing and Machine Learning Over time, the advancements in natural language processing (NLP) and machine learning (ML) have paved the way for more sophisticated AI applications in recruitment. NLP enables AI systems to understand and analyze human language, helping them process resumes and job descriptions more effectively. Meanwhile, ML allows AI tools to learn from large datasets and improve their performance over time, making them more accurate and efficient in identifying the right candidates for a job opening. How Basic Tools Became Sophisticated Ai-Driven Recruitment Platforms As AI technology evolved, so did the tools used in recruitment. Today, various advanced AI applications are at everyone’s fingertips. While it’s completely okay to have fun convos with GPT4 and share them on your socials, some have already started leveraging these tools to create completely automated hiring platforms accessible to everyone. Multiple aspects of the process are being handled at once. From sourcing candidates to conducting preliminary interviews (which are then forwarded to a human), and even predicting how likely a candidate is to succeed in a particular role. This particular combination of advanced NLP and ML technologies has slowly started to reshape the entire hiring process. Key AI-Driven Recruitment Technologies AI-powered resume screening tools utilize natural language processing and machine learning algorithms to and identify top talent based on specific criteria set by the hiring team. analyze candidates' resumes This enables recruiters to quickly shortlist the most suitable candidates for further evaluation, resulting in a more efficient hiring process. Reducing Time Spent on Manual Resume Review If you ever worked as part of a hiring team, you know how daunting this can be. Sit at your desk, sift through a stack of papers or pdfs, and read the phrases “growth-driven” and “team player” time and time again. Word to the wise: if you’re looking for a job - please don’t use the ones I mentioned above and similar ones. Be genuine. Back to AI-driven resume analysis. Automating resume reviews can significantly reduce the time spent here and present you with the best candidates for the role in a matter of seconds. This not only increases efficiency but also frees up HR professionals to focus on other . strategic aspects of recruitment However, be wary of your AI setup so you don’t overlook some great candidates by mistake. AI Recruitment Chatbots AI recruitment chatbots are transforming the way candidates and employers interact during the hiring process. These chatbots can automate repetitive tasks such as scheduling interviews, answering frequently asked questions, and providing updates on the application status. This streamlines communication, improves efficiency, and ensures that candidates are well-informed throughout the hiring process. By providing instant, personalized responses to candidates' inquiries, AI recruitment chatbots help create a positive candidate experience. They can also guide job seekers through the application process and offer real-time support, ensuring that candidates feel valued and engaged. Benefits of AI-Driven Recruitment AI-driven recruitment technologies streamline various aspects of the hiring process, from sourcing and screening candidates to scheduling interviews and providing feedback. This increased efficiency allows HR professionals to focus on more strategic tasks and shortens the overall time-to-hire, giving organizations a competitive edge in the race for top talent. Improved Candidate Quality and Fit By automating resume screening and utilizing intelligent job matching algorithms, AI-driven recruitment tools can identify candidates with the right skills, experience, and cultural fit for a given role. This ensures that the candidates presented to the hiring team are of high quality and have a within the organization. greater likelihood of success Reduced Hiring Bias and Promotion of Diversity AI-driven recruitment technologies can help in the hiring process by focusing on objective factors such as skills and experience rather than subjective elements like appearance or perceived "culture fit." reduce unconscious biases This promotes diversity within the workplace by ensuring that candidates are evaluated based on merit rather than factors unrelated to job performance. Increased Cost Savings for Companies By streamlining the recruitment process and reducing time-to-hire, AI-driven recruitment tools can generate significant cost savings for organizations. The reduced need for manual intervention, improved candidate quality, and decreased employee turnover all contribute to a more efficient and cost-effective recruitment process. Challenges and Ethical Considerations Despite the potential to reduce hiring bias, AI-driven recruitment technologies can also inadvertently perpetuate existing biases if not properly designed and monitored. It is crucial for organizations to continually evaluate the performance of AI algorithms to ensure that they are not reinforcing harmful stereotypes or introducing new biases into the hiring process. Ensuring the Privacy and Security of Candidate Data The use of AI-driven recruitment tools necessitates the collection and processing of large amounts of candidate data. Organizations must take appropriate measures to , complying with relevant data protection regulations and safeguarding against potential data breaches. ensure the privacy and security of this data Balancing AI-driven Recruitment With the Human Touch While AI-driven recruitment technologies can significantly improve the hiring process's efficiency, it is essential not to overlook the importance of human intuition and interpersonal skills. HR professionals must strike the right balance between leveraging AI tools and maintaining personal connections with candidates, ensuring that the recruitment process remains human-centric and that AI technologies complement rather than replace the human touch. The Future of AI in Recruitment AI popularity seems unlikely to go down any time soon, so we can expect more and more advanced automated hiring solutions to dominate the HR space. While these changes are likely to save a lot of money and time for both employers and job candidates, I strongly believe there are many potential pitfalls on our way to a robot-recruiter utopia.

The AI-Driven Recruitment Revolution

Unlock the power of AI to transform recruitment from a cost center to a strategic driver of business success. Recruitment has always been a crucial aspect of business operations, and companies have been employing various methods to find and hire the right talent for centuries. From placing ads in newspapers to working with recruiting agencies, they have tried everything to attract the best possible candidates. However, with rapid advancements in technology, the recruitment industry has also undergone a massive change. In recent years, the rise of artificial intelligence (AI) in particular is notable, as it has come a long way since its inception. In fact, the global market for AI is expected to reach an impressive market growth rate of . $521.3 billion by 2028 Recruitment is just one of the industries that AI has successfully revolutionized. According to a report by Facts & Factors, the global AI recruitment market size is projected to increase to . $890.51 million by 2028 The increase is mainly due to companies adopting AI recruiting tools in their hiring processes. Today, AI-based recruitment has enabled companies to automate many tedious and time-consuming tasks associated with the hiring process. This automation is rapidly becoming a game-changer in the industry. So, let’s delve into why and how AI is driving this automation and revolutionizing the recruitment industry as a whole. Time Is Money - The Cost of Elongated Hiring Processes Every company focuses on hiring the best workforce to scale and expand its services. But building a team takes a toll on the company’s finances. The human resources department of any organization is in a constant struggle every day to find the best candidates. From spending hours on end sorting through resumes, scheduling interviews, and conducting background checks, the time to screen employees can sometimes take forever. According to LinkedIn, the average length of a hiring process is . 36 days Moreover, the costs associated with finding the right candidates are enough to leave a dent in the company’s revenue targets. A reveals that the average cost of hiring an employee can be as high as $4,000. Glassdoor study Hiring a new employee can be a time-consuming and expensive process, but AI-based automation in recruitment is successfully helping companies combat these problems. Not only does AI-based recruitment automation help companies reduce costs, but it also reduces the time taken to successfully screen and hire candidates. With the help of AI, many of the processes involved in recruitment can be easily automated, allowing recruiters to focus on more strategic tasks. AI-powered automated application tracking tools and resume scoring and ranking can make life easier for recruiters. The technology can also significantly reduce a recruiter's time spent reviewing nontechnical aspects of candidates, such as communication skills, through the use of virtual reality-based dialogue systems or virtual recruiters. Unconscious Bias - Improving the Quality of Hires Unconscious bias is a prominent problem in the recruitment industry, and it can have a significant impact on the hiring process. According to , “79% of HR professionals agree that unconscious bias exists in both recruitment and succession planning decisions." BrightTalk When we talk about unconscious bias, we’re referring to particular attitudes and stereotypes that people hold about certain groups of people, often without realizing it themselves. In recruitment, this bias can lead to hiring decisions that are influenced by external factors like age, gender, race, and education level, rather than job-related criteria. At the workplace, it can “ ” stymie diversity, recruiting, promotion, and retention efforts. AI-based recruitment tools can offer a potential solution to this problem, as they are designed to minimize bias and promote fair and objective hiring practices. They can also be used to improve the quality of hires. AI systems also do a much better job of tracking candidates, unlike traditional manual processes. This is because AI systems can be trained with large datasets to understand ideal candidate traits and can quickly identify the right candidates from a myriad of platforms like GitHub or Quora. Training and Development - Curating New Recruitment Strategies The recruitment industry faces several limitations when it comes to training and development. According to a , 80% of organizations have expressed that they are having difficulty filling openings due to an ongoing shortage of skills. Monster survey This is why companies must prioritize investing in employee development and adapt to the evolving industry landscape to stay competitive and attract top talent. AI-based recruitment can assist them with this by helping curate new recruitment strategies and improve existing ones. Once the talent needs have been identified, AI can help source potential candidates through AI-generated custom advertisements that target the right candidate pools from across the web. Not only that, but AI can also help companies upskill their current workforce. AI-powered learning management systems can analyze employee performance data and create customized training plans to help employees improve their skills and knowledge. AI can help recruiters and companies make important decisions like choosing between which will provide additional support and expertise in areas where there may be a skills gap. getting consulting services or augmenting the existing workforce AI Is Transforming Recruitment Into a Strategic Driver of Business Success By leveraging AI, companies can gain a competitive advantage in the industry by attracting top talent and building a more diverse and inclusive workforce. According to Forbes, at least are invested in recruitment automation as it will enhance efficiency and drive data-driven hiring processes. 55% of companies However, it is crucial to ensure that AI algorithms are trained on diverse data sets and viewed as a tool to support recruiters rather than replace them. As the recruitment industry continues to evolve, AI-based automation is set to play an increasingly important role in streamlining the hiring process, reducing costs, and improving the overall quality of hires. Hence, it is crucial for companies to stay up-to-date with the latest trends and technologies and embrace the power of AI to drive growth and success. Ultimately, AI offers a unique opportunity to transform recruitment from a cost center to a strategic driver of business success.

How Artificial Intelligence Drives Automation & Reduce Costs in Recruitment Industry 

It's not wrong to infer that we're yet to experience the full range of artificial intelligence (AI) and its capabilities. After all, its impact, fears, and prospects still dominate research endeavors; as scientists are keen on finding new use cases for this innovation. We're likely to have encountered the application of AI in various situations. This is because many companies whom we patronize have increased their adoption of the technology. Consider the interactive personal assistant Siri which enables customers to access relevant information from various apps, dictate emails, and perform many other tasks from their iOS-enabled phones, smartwatches, computers, and televisions. Apple Brands are also leveraging chatbots to deliver impeccable customer experience in a manner that not only boosts sales but eliminates the need for repetitive tasks, thereby increasing human employees’ engagement. Just as the adoption of AI-led tools rose, so did investments in the enterprise soar. According to McKinsey’s “ ” report, 52% of respondents confirmed that over 5% of their digital budget was channeled to AI. In 2018, the percentage stood at 40. The State of AI in 2022 This is a striking improvement. In human resources, AI plays a critical role in helping corporations enhance employees’ satisfaction with their current roles and rapidly complete tasks, thus saving the indispensable duo of time and money. Aside from this, companies can refine recruitment by using AI-powered software to sift through thousands of applications and shortlist a handful of experienced candidates. However, there have been situations when the system favors a specific group or gender over others. This is a risky trend that, if unchecked, could greatly tarnish a firm’s image and negate the good this technology symbolizes. To help you effectively handle AI-sponsored prejudice, this article provides some pointers. AI in Recruitment: What You Need To Know Previously, individuals found job postings in the classifieds portion of newspapers and responded via handwritten letters. Nowadays, anyone can access job postings on the internet across a plethora of channels. Recruitment is a delicate task that companies prioritize. It explains the growing use of talent acquisition agencies. Using AI not only simplifies the process but broadens the possibilities of automation in other areas. From into the impact of AI on HR, it's discovered that nearly 67% of HR professionals admit that the innovation has positively impacted the recruitment phase. Tidio's inquisition But then, how does bias enter the scene? In 2014, e-commerce giant opted to integrate AI into its hiring system. And while this was largely celebrated as a step in the right direction since Amazon is a staunch automation advocate, the effort was discontinued following an awful discovery. The system preferred male candidates to their female counterparts. Amazon Why did this happen? A report revealed that... Reuters “...Amazon’s computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10-year period. Most came from men, a reflection of male dominance across the tech industry.” AI bias can manifest in several ways, with certain genders, groups, religions, and other affiliations always being the victim. — which spewed many hateful messages before earning a Twitter account suspension — is another instance of how anomalies in the machine-learning process can yield great consequences. Microsoft’s Tay Three Best Practices for Mitigating AI Bias in Recruitment Although it may not be possible to completely eradicate bias in AI models, there are strategies capable of reducing the odds of a future incident. Below are three must-have methods. 1. Always Keep Humans in the Know While there's a growing fear that smart tools will replace human workers, we should see this as more of a partnership and less of a dystopian takeover. And also, the notion that AI-led tools should function without human supervision because they exhibit considerably more efficiency needs to be modified. Interestingly, human-machine collaborations have been proven to be more rewarding. A discovered that 1,075 companies across 12 industries recorded increased speed, cost savings, and profit. Harvard Business Review study Given this undeniable fact, firms should ensure that a human team consistently oversees the software used in recruitment. Together, they can reduce the risk of favoritism. Also, the employees should be drawn from a diverse pool so that every group is represented in the responsibility of reducing discrimination. 2. Conduct Regular Audits on the AI Models When AI algorithms aren't frequently checked for the probability of delivering partial outcomes, this could deal a company’s anti-bias effort a serious blow. By organizing periodic checks on the algorithms, corporations can find problems that may hinder the model from conveying fair results. Incomplete or inaccurate data should be rectified immediately upon discovery to protect ethics. 3. Patronize AI Recruitment Software Vendors with an Aversion to Bias Just like a car dealership, you will find various recruitment software options. To make the right decision, endeavor to learn more about how the mechanisms set by vendors to tackle the various kinds of bias. You should request to see the system get tested in various situations and see how it performs. Aside from bias, check the software for scalability, pricing, and cost savings.  The one that ticks all or most of the boxes is the winner. A Candid Take on AI’s Future The advancement of AI and its subsets is a good thing for all of us. From enabling cars to steer and park themselves (with active driver supervision) to sourcing and hiring qualified candidates in lesser time, AI offers several benefits that transcend recruitment. But then, we should purposefully manage this technology to avert the blunders associated with manual effort. Dr. Lisa Palmer shares in a thoughtful that the American state of Oklahoma should throw its weight behind the enactment of Perhaps, we can learn from that and as she recommends to navigate this technological revolution toward the good side. article “legislative and regulatory action that both support innovation and ensure that this critical technology serves humanity well.” “do more"

Stories, News & Mentions about RECRUITCRM

Recruitcrm’s Stories on HackerNoon