Naveed Iftikhar’s Post

Using AI in the hiring process is huge! Lately, I have been thinking and reading articles a lot about how organizations are using AI in the hiring process. There are pros and cons, and I noticed a recurring concern. While AI has the power to streamline recruiting and uncover talent, it can also unintentionally replicate or amplify existing biases in ways that disadvantage underrepresented groups. What are your thoughts? Potential Biases of AI in the Hiring Process 1. Bias in Training Data 📚 • Description: AI might perpetuate systemic biases by relying too heavily on past trends rather than assessing current qualifications. • Example: Women historically underrepresented in tech may result in fewer female candidates being shortlisted for tech roles. 2. Algorithmic Bias 🤖 • Description: Biases can arise from the design of the algorithms, especially if certain variables correlate with protected attributes (e.g., race or gender). • Example: Using ZIP codes as a feature might inadvertently favor or disadvantage specific racial or socioeconomic groups. 3. Feature Selection Bias 🔍 • Description: AI may prioritize certain features that are indirectly biased. • Example: Preferring candidates from “top schools” could disadvantage underrepresented groups who have historically had less access to these institutions. 4. Lack of Contextual Understanding ⚙️ • Description: AI lacks nuanced judgment and might unfairly screen out candidates based on rigid criteria. • Example: Automatically rejecting candidates with non-traditional career paths or gaps in employment. 5. Bias in Natural Language Processing (NLP) 💬 • Description: Language models may reflect biases present in their training data. • Example: AI might score resumes differently based on gendered language or cultural differences in expression. 6. Homogenization of Workforce 🧑🤝🧑 • Description: AI might favor candidates similar to those already hired, leading to less diversity. • Ex: Recommending candidates who resemble the current employee base in terms of background, education, or skills. 7. Opaque Decision-Making 🕵️♀️ • Description: AI decisions are often difficult to interpret or audit, making it challenging to identify and rectify biases. • Ex: Candidates may not know why they were rejected, and companies may not understand the bias in their models. 8. Bias in Candidate Assessments 🎥 • Description: AI-driven assessments like video interviews may analyze facial expressions, speech, or other non-verbal cues that could be culturally biased. • Ex: Misinterpreting body language or speech patterns from different cultures as less “competent.” 9. Bias in Job Descriptions 📝 • Description: AI-generated job descriptions may include biased language that discourages certain groups from applying. • Ex: Using gendered or exclusionary language that deters diverse applicants. By understanding and addressing these biases, organizations can create fairer and more inclusive hiring processes.

Artificial Intelligence, Recent Graduates & Selling Windows I had planned an entirely different topic to share today. 🤖 Then I saw Lili Foggle's post about an April survey of hiring managers and their perspectives on hiring recent grads and AI. I felt it was too important not to share today. 🎓 The results of this survey are eye-opening. For example, 69% believe that AI can do the work of a recent college grad. ✍🏼 If your education and experience include AI, it's crucial to showcase this on your LinkedIn profile and customize your resume accordingly. Make sure to mention it in your cover letter as well. During interviews, be prepared to highlight what you've learned and how you've applied it. 📈 For those without AI experience, read Lili’s note and links in the comments, which provide valuable suggestions on how to boost your AI knowledge. 📚 AI is here and is changing the landscape of almost every industry. I would suggest that all of us, not just new grads, read up, train up, and join communities in our fields to build up AI knowledge and experience to understand its limitations and potential. 🪟 A friend of mine has been selling and installing windows for years, and he just signed up for a 6-week AI class! How is AI being used in your industry? What have you done to boost your AI knowledge? #artificialintelligence #futureofwork #resumeconnections

𝐀𝐈 𝐯𝐬. 𝐀𝐓𝐒 𝐢𝐧 𝐇𝐢𝐫𝐢𝐧𝐠: 𝐀𝐫𝐞 𝐘𝐨𝐮 𝐑𝐞𝐚𝐝𝐲 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐒𝐡𝐢𝐟𝐭❓ 🚨 𝐍𝐞𝐰 𝐀𝐥𝐞𝐫𝐭 𝐟𝐨𝐫 𝐉𝐨𝐛 𝐒𝐞𝐞𝐤𝐞𝐫𝐬: You may now see options asking if you consent to AI screening during your job applications. It's something that's starting to come up more and more in my conversations with job seekers. I recently took an AI in HR course, and there will be significant changes in the hiring and recruitment process in the near future. 𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭 𝐲𝐨𝐮 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐤𝐧𝐨𝐰❗ ✍️ Traditional ATS: ■ Uses keyword matching to filter resumes ■ Sorts candidates based on pre-set criteria ■ Organizes applicant data for easy access 🤖 Advanced AI Screening: ■ Understands context with Natural Language Processing (NLP) ■ Uses Machine Learning for deeper analysis and insights ■ Automates skills tests and video interview assessments ■ Designed to reduce bias by focusing on objective factors 𝐊𝐞𝐲 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞𝐬 𝐭𝐨 𝐊𝐧𝐨𝐰: 🔍 Depth of Analysis: AI evaluates context, not just keywords 📊 Predictive Insights: AI predicts candidate success using data patterns 🚀 Continuous Learning: AI improves over time by learning from past hiring outcomes 📝 Personalization: Tailors feedback and recommendations for both candidates and recruiters 𝐖𝐡𝐚𝐭 𝐈𝐭 𝐌𝐞𝐚𝐧𝐬 𝐟𝐨𝐫 𝐘𝐨𝐮: 🕵️♂️ Expect more comprehensive assessments, beyond just keywords 🏃♀️ Faster responses thanks to AI-driven processes 🤔 Be mindful of opting in or out of AI screening—know the pros and cons 🔑 Optimize your resume for both ATS and AI screening: use relevant keywords but also highlight your unique skills and experiences ❗ Be aware that while AI aims to reduce bias, algorithmic bias can still occur 𝐃𝐢𝐝 𝐘𝐨𝐮 𝐊𝐧𝐨𝐰? 67% of hiring managers believe AI will reshape the recruiting process 𝐅𝐢𝐧𝐚𝐥 𝐓𝐢𝐩𝐬: 𝐒𝐭𝐚𝐲 𝐈𝐧𝐟𝐨𝐫𝐦𝐞𝐝 𝐚𝐧𝐝 𝐀𝐝𝐚𝐩𝐭: This is an evolving space, so it's key to stay up-to-date on changes in how companies screen applications. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭 𝐔𝐧𝐢𝐪𝐮𝐞 𝐒𝐤𝐢𝐥𝐥𝐬: AI systems are becoming better at recognizing non-traditional qualifications, so don't hesitate to showcase your unique experiences. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐔𝐩 𝐀𝐟𝐭𝐞𝐫 𝐀𝐩𝐩𝐥𝐲𝐢𝐧𝐠: After submitting your application, wait about one week before following up. A polite email or call expressing your continued interest can keep you on the radar of hiring managers and demonstrate your enthusiasm for the role. Please share this post with your network or anyone you think might benefit from this information! 𝐇𝐚𝐯𝐞 𝐲𝐨𝐮 𝐞𝐧𝐜𝐨𝐮𝐧𝐭𝐞𝐫𝐞𝐝 𝐀𝐈 𝐬𝐜𝐫𝐞𝐞𝐧𝐢𝐧𝐠 𝐲𝐞𝐭? Share your experience below. How do you feel about AI's growing role in recruitment? #CareerCoach #JobSearch #ResumeTips #Success #CareerChange

Why #GenAI is a bubble? You might have heard that there is an extremely high investment of about a trillion dollar on GenAI, but service companies only grabbed single digital billion dollar deals for AI! which is too lo So AI will create jobs or take jobs? Lose Job scenario - Goldman Sachs predicts that 300 million jobs will be lost or degraded due to AI https://lnkd.in/g3Eafe8c Public Policy Research says alone in US - AI take away 8 million jobs (https://lnkd.in/gBsQvafy) IMF predict 40% job impact in early 2024 due to AI (https://lnkd.in/gQa2Tpf4) Or AI will create job World Economic forum says AI will create 97 million jobs , 12 million by 2025 (https://lnkd.in/gyMxJKZE) I started working on Natural Language Processing (part of GenAI) in 2008, I have seen such claims from the first chatbots, the very intelligent IBM Watson. I am part of transformation journey from ontology databases to LLMs. From statistical NLP to Artificial Neural Network. There is no straigthforward answer. GenAI definitely increase productivity of any development by whopping 50%. It is the most interesting usecase with good ROI, it can be a good consultant, it can provide solution and also suggest better way to do everything. It can generate images, blogs, summaries and language translations. It can understand what customer wants and raise queries, it can create data insight dashboards. But that's it. Advance genAI like #ChatGPT - is equivalent to knowledge of 1000 developers. But still one thing missing is intelligent - the part becoming intelligent is understanding query and retrieving specific result in different format. Job creation in tech depends on business outcome. If you see in real world - you pay only for two applications of AI - Alexa and ADAS. Yes, there are many usecases of Artificial Intelligent but not of Generative AI. Whatever can be implemented, mostly already out in the market. Like automation testing, AI will improve productivity of developers by 50% currently it is just 20-30% (https://lnkd.in/gw9svtut). It will reduce need of junior developers (0-5 years) that's why company stopped hiring freshers. There will be some impact to senior developers, architects and consultant but it will be adjusted by growth.

➡ The Expanding Universe of AI Careers New AI careers are emerging, transforming traditional employment and creating opportunities in unexpected ways. AI is not just reshaping how we approach tasks; it’s spawning a new generation of job roles, particularly in sectors that have traditionally relied heavily on human intervention. ➡ New AI Careers The term “AI competency leader” has recently popped up in job ads. It shows jobs requiring teamwork across different groups to use AI in many areas. This shows a shift from the conventional job roles we’ve been accustomed to. Now, it’s not just about having development or data science skills. Integrating AI into business strategies requires new responsibilities, from training algorithms to managing ethical concerns. There are two levels of AI-related positions that are emerging. The first involves AI specialists with broad training in machine learning, neural networks, and more. The second, more intriguing category is “AI plus something”. For example, “AI in law”, “AI in medicine”, or “AI in hiring”. These positions are more abundant and demand a combination of core expertise and AI implementation skills. ➡ The Rise of Prompt Engineering Prompt engineering is among the new positions making headlines. It’s now a hot job. However, its longevity as a career path remains uncertain. While it’s currently in demand, its future depends on how AI interfaces evolve. Other prospective roles include AI trainers, auditors, and ethicists, focusing on ensuring the ethical use of AI and maintaining data integrity. The transformation doesn’t stop there. According to experts, AI is taking over many lower-level tasks in IT development and management, a trend that should be welcomed. These include coding, updating legacy code, and implementing SDKs. These were previously considered tedious and time-consuming tasks. ➡ Disappearing Jobs - Keep reading: https://lnkd.in/gYvf_7XE ⭐ Pre-order my book now & Supercharge your career with AI: https://lnkd.in/eYSTy53t #AI #chatgptprompts #chatgpt #artificialgeneralintelligence #aiatwork #resumewriting #cvwriting #jobhunting #layoffs #jobsearch #jobsearchstrategies #kindlebooks #kindlebook #indieauthor #chatgptprompt #aicommunity #indieauthor #indieauthor #indiepublishing #jobsearchtips #redundancies #redundancy #aiinhr #aiadvancements #newcareer #newcareeropportunities

➡ The Expanding Universe of AI Careers New AI careers are emerging, transforming traditional employment and creating opportunities in unexpected ways. AI is not just reshaping how we approach tasks; it’s spawning a new generation of job roles, particularly in sectors that have traditionally relied heavily on human intervention. ➡ New AI Careers The term “AI competency leader” has recently popped up in job ads. It shows jobs requiring teamwork across different groups to use AI in many areas. This shows a shift from the conventional job roles we’ve been accustomed to. Now, it’s not just about having development or data science skills. Integrating AI into business strategies requires new responsibilities, from training algorithms to managing ethical concerns. There are two levels of AI-related positions that are emerging. The first involves AI specialists with broad training in machine learning, neural networks, and more. The second, more intriguing category is “AI plus something”. For example, “AI in law”, “AI in medicine”, or “AI in hiring”. These positions are more abundant and demand a combination of core expertise and AI implementation skills. ➡ The Rise of Prompt Engineering Prompt engineering is among the new positions making headlines. It’s now a hot job. However, its longevity as a career path remains uncertain. While it’s currently in demand, its future depends on how AI interfaces evolve. Other prospective roles include AI trainers, auditors, and ethicists, focusing on ensuring the ethical use of AI and maintaining data integrity. The transformation doesn’t stop there. According to experts, AI is taking over many lower-level tasks in IT development and management, a trend that should be welcomed. These include coding, updating legacy code, and implementing SDKs. These were previously considered tedious and time-consuming tasks. ➡ Disappearing Jobs - Keep reading: https://lnkd.in/gasihAUz ⭐ Pre-order my book now & Supercharge your career with AI: https://lnkd.in/eyhAJYjZ #AI #chatgptprompts #chatgpt #artificialgeneralintelligence #aiatwork #resumewriting #cvwriting #jobhunting #layoffs #jobsearch #jobsearchstrategies #kindlebooks #kindlebook #indieauthor #chatgptprompt #aicommunity #indieauthor #indieauthor #indiepublishing #jobsearchtips #redundancies #redundancy #aiinhr #aiadvancements #newcareer #newcareeropportunities

AI is a double-edged sword for IT careers—will it replace jobs or aid workers in being more productive and efficient? The jury is still out, but it does seem to be impacting entry-level workers as generative AI tools increasingly take on organization’s entry-level responsibilities. This trend in which entry-level and early-career roles are being reduced, leaving less-seasoned candidates struggling to find work and gain more experience. AI is a top focus for organizations, and tech talent with AI skills is much more in demand than those without AI-related skills. As we look to the future—skills that relate directly to AI, such as NLP [natural language processing], working and training LLMs [large language models], as well as skills related to AI such as cloud architecture and engineering, data science, and management skills—these are continuing to see demand, at the expense of other IT skills. And for organizations that plan to lay off workers to hire AI, the question remains whether there’s enough skilled talent available to hire with AI skills. The demand for AI skills is only increasing, along with cloud and data skills, but we may be heading towards a skills mismatch in the marketplace—where certain skills remain hard to find and organizations struggle to have enough of them, and yet there are talented, experienced tech workers who cannot find work. The best thing organizations can do to prepare for the unknown landscape of AI is to invest in their workforce through upskilling and skills development programs. The best way to beat the skills gap is to identify what skills your organization is going to need in the near future and then train and upskill talented workers to meet those skills needs. Organizations should be taking a more strategic approach to their talent and demand pipelines in order to put in place the skills development programs now so that they can take advantage of internal talent and mobility, retaining valuable organizational knowledge and expertise, while building the skillsets required for the future.

The job market for AI specialists is growing rapidly, driven by advancements in technology and increasing demand across various industries. Key trends include: High Demand for AI Skills: The demand for AI and machine learning specialists is projected to increase significantly, with roles such as AI engineers, data scientists, and natural language processing (NLP) specialists becoming more prevalent. These positions are essential in developing AI systems and applications that drive business innovation. Industry Adoption: AI professionals are being sought after in numerous sectors beyond traditional tech companies. Industries like finance, healthcare, automotive, and retail are heavily investing in AI to improve operations, customer experiences, and overall efficiency. This widespread adoption opens up diverse opportunities for AI specialists. New Job Roles: As AI technology evolves, new roles are emerging. For example, positions like AI product managers, data ethicists, and AI prompt engineers are becoming more common. These roles focus on integrating AI into business strategies, ensuring ethical AI development, and fine-tuning AI models for specific applications. Skills and Training: To capitalise on these opportunities, professionals should focus on acquiring relevant skills such as proficiency in AI frameworks, programming languages, and understanding of data analytics and machine learning techniques. Continuous learning and upskilling are crucial to staying competitive in this rapidly changing field. Overall, the AI job market is expanding, and specialists with the right skills and expertise are in high demand across multiple industries. #happyhiring #exceptionaltalent #rentarecruiter #makingplacements #talentteam #talentfinder #futureofrecruiting #recruiter #recruiters #rentarecruiter #talentsubscriptions #candidatejourneyb #candidateexperience

🔥 Hiring update 🔥 overview of my current AI related positions 🤖 ☎ DM with your CV including AI achievements/skills for more details please ⤵ #Hiring #AI #ArtificialIntelligence #MachineLearning #DigitalStrategy #DigitalTransformation #salesjobs #AIApplications #berlintechjobs #JobOpening

“In the rapidly evolving field of AI, staying ahead means mastering a diverse set of skills. This article highlights the top 15 skills employers are seeking in AI professionals. From deep learning and natural language processing to problem-solving and teamwork, these skills are crucial for anyone looking to excel in AI roles. #AI #MachineLearning #CareerGrowth #TechSkills”