AI's Impact on Jobs

Modern misogyny: AI advises women to seek lower salaries than men 👩🏾💻 “In what might be proof that AI chatbots reinforce real-world discrimination, a new study has found that large language models such as ChatGPT consistently tell women to ask for lower salaries than men. This is happening even when both women and men have identical qualifications, and the chatbots also advise male applicants to ask for significantly higher pay. For the study, co-authored by Ivan Yamshchikov, a professor of AI and robotics at the Technical University of Würzburg-Schweinfurt (THWS) in Germany, five popular LLMs, including ChatGPT, were tested. The researchers prompted each model with user profiles that differed by gender only but included similar education, experience, and job role. The models were then asked to suggest a target salary for an upcoming negotiation. For instance, ChatGPT’s o3 model suggested that a female job applicant requested a salary of $280,000. The same prompt for a male applicant resulted in a suggestion to ask for a salary of $400,000. The difference is huge: $120,000 a year. The pay gaps vary between industries and are most obvious in law and medicine, followed by business administration and engineering. Only in social sciences do the models offer similar advice for men and women. Other AI chatbots such as Claude (Anthropic), Llama (Meta), Mixtral (Mistral AI), and Qwen (Alibaba Cloud) were tested for biases. Researchers also checked other areas like career choices, goal-setting, and behavioral tips. Alas, the models still consistently offered different responses based on the user’s gender, even with identical qualifications and prompts. The study points out, AI systems are subject to the same biases as the data used to train them. Previous studies have also demonstrated that the bots reinforce systemic biases.” Read more 👉 https://lnkd.in/esnwnkGX #WomenInSTEM #GirlsInSTEM #STEMGems #GiveGirlsRoleModels

People are quickly discovering AI as a powerful way to augment and accelerate their job search efforts by overcoming the often mechanical and robotic application process. Brilliant! Good for them. Recruiting functions are being overwhelmed by applications and the threat of potential bot applicants. Predictable but legitimate and understandable challenge. To combat this trend, a growing number of companies are looking for AI to filter out candidates suspected of using AI in their applications. Wait, WHAT!?! If you’re considering this at your company, please take a strategic pause. Few things to consider. First, if someone or something is making it all the way to offer without a legitimate human interaction, you may want to scrap your entire TA approach and start over. Second, trying to detect AI specifically trained to mimic human behavior and language will leave you eliminating more qualified human candidates than it is catching AI criminals. Finally, consider why you would legitimately want to eliminate a candidate already demonstrating one of the most critical job skills for the modern age: AI problem-solving. Here is some additional food for thought. If you’re legitimately getting overwhelmed by what you believe are AI applications, it’s an indication your application process is far too robotic today, which is why it’s such an easy target. Accept that the robotic parts are what they are: a check-the-box activity. Make them quick and easy for a human and move on. After that, explore how you can augment your robotic process by using AI to assess skills versus someone’s head knowledge or ability to fill out a form. AI is making realistic job simulations scalable. Wouldn’t you rather have a better indication of the person’s ability to perform the job anyway? From there, ensure you maintain plenty of human oversight in your process. I agree AI can automate and speed things up, but in the AI age, interpersonal and human skills are what you need from humans, so make sure you have humans involved in hiring other humans for human work. The AI future has so much potential for good, but not when we use it as a quick fix to plug cracks in a broken dam. Instead, we need to see how it can reimagine solutions to the root problems. #BigIdeas2024

Came back from vacation Monday. Inbox? On fire.🔥 Buried in the chaos: a customer story that stopped me in my tracks (and made me so happy). A Customer Support leader at a fast-growing financial services company used AI to transform his team - in just a few weeks. This leader works for a financial services company that’s in high-growth mode. Great news, right? Yes! For everyone except his Customer Support team… As the business grew faster, they were bombarded with repetitive questions about simple things like loan statuses and document requirements. Reps were overwhelmed. Customers faced longer response times. The company has been a HubSpot customer for nearly 10 years. They turned to Customer Agent, HubSpot’s AI Agent, and got to work: - Connected it to their knowledge base → accurate, fast answers - Set smart handoff rules → AI handles the simple, reps handle the complex - Customized the tone → sounds like them, not a generic bot (you know the type) In a short space of time, things changed dramatically: - Customer Agent now resolves more tickets than any rep - 94.9% of customers report being happy with the experience - For the first time, the team can prioritize complex issues and provide proactive support to high-value customers It’s exciting to see leaders using Customer Agent to not just respond to more tickets, but to increase CSAT and empower their teams to drive more impact. 2025 is the year of AI transformed Customer Support. I am stunned by how quickly that transformation is playing out!

The Microsoft and LinkedIn 2024 Work Trend Index Annual Report is out, and unsurprisingly, AI is rapidly transforming the global workforce. Based on a survey of 31,000 people across 31 countries, here are the highlights, and what it means for education. Key Highlights: - AI usage has more than doubled in the last 6 months, with 75% of global knowledge workers reporting using GenAI tools. - 79% of leaders agree their company needs to adopt AI to stay competitive, but 60% worry their organization lacks a plan and vision to implement it. - 78% of AI users are bringing their own AI tools to work (BYOAI), cutting across all generations. - Leaders say they would not hire someone without AI skills (66%) and would prefer a less experienced candidate with AI skills over a more experienced one without them (71%). - AI power users are experimenting frequently with AI, getting support and encouragement from leadership, and receiving tailored AI training. They are seeing significant benefits in productivity, creativity, and job satisfaction. What does it mean for education? - Experience with AI is becoming a key hiring criteria, in part due to research that shows that GenAI use can significantly decrease skill gaps. - 77% of leaders say early-in-career talent will be given greater responsibilities due to AI. This has major implications for how schools and universities prepare students for the job market. - Only 39% of people who use AI at work have received AI training from their company, and only 25% of companies plan to offer training on generative AI this year. This gap between need for training and availability is similarly playing out in schools and systems right now. - As AI reshapes work, the skills required for jobs are projected to change significantly. Educational institutions will need to adapt curricula to focus on the uniquely human skills that will be most valuable in an AI-enabled work world, such as creativity, critical thinking, and relationship building. The rapid rise of AI is transforming the workplace and the job market and the entire education ecosystem has an essential role to play in equipping students and workers with the AI skills and aptitudes that are and will be most in-demand. For the full report, visit: https://lnkd.in/eyfSRzNj AI for Education #aiforeducation #aieducation #durableskills #GenAI #AIliteracy

If I were applying for a job right now, here are three things I would use AI for: 1. Finding jobs. AI is great at searching through large quantities of information, and finding matches for what you're looking for. This could involve building an AI agent that searches the internet for exactly what you're looking for and delivers it to your inbox each morning. It could involve using the AI features popping up on job boards. 2. Getting feedback on your candidacy. AI is pretty good at matching up your experience with what the company is looking for. It DOES have a tendency to be overly positive/generous as it wants to keep you happy, but prompting it to be extremely discerning and hold a very high bar will usually help you get honest feedback and avoid applying for jobs that you're unlikely to be competitive for. 3. Preparing for applications and interviews. An AI assistant can be helpful in giving you feedback on a response or helping you select from your experiences so you can choose what to highlight on a resume or application question. An assistant or one of the many AI interview tools out there can generate sample questions and give you feedback on your responses so you can work out the nerves ahead of your next interview. And three ways I would NOT use AI: 1. Applying for jobs on my behalf without my engagement. I have seen far too many AI appliers submit people for roles that aren't a good match, and in doing so, you might actually ruin your chances for future jobs. If a company sees you've applied for 10 jobs ranging from coordinator to Sr. Director, they're going to assume you're spamming them and stop taking your candidacy seriously. Some companies limit you to say, 3 apps every 6 months. So you end up wasting yours on bad fit jobs and not being able to apply when the right job pops up. Additionally, some companies are now checking IP addresses of the applier against locations and looking for evidence of AI as a guard against fraudulent candidates so you run that risk as well. 2. Filling out the application for you. I would certainly use AI to help gather my thoughts. But when I apply for a job, I want to put my best foot forward and AI isn't going to do that. AI responses are all generic and tend to use the exact same formula to respond which means your response sounds like 80% of the applicant pool doing the exact same thing. That's not gonna stand out from the crowd, and it really gives low B-player energy at best. In a saturated market, every company is chasing A players. 3. Using it live in an interview. Y'all I've seen way too many people pause to type stuff into an assistant and then read off a screen. Some try to be sneaky (repeating the question as a prompt). I've even experienced the AI filters at this point. You can use notes from your prep with an AI Assistant. But trying to use it live in the interview is just hurting you. So the TL;DR: Yes use AI, but only in ways that make you better and help you shine.

Just a thought before the weekend. With the introduction of new technologies certain tasks traditionally performed by junior staff are being automated. In many cases the junior position is eliminated, and residual task is redistributed to more senior employees, actually increasing their workload. Historically, the roles of secretaries and accounting clerks exemplify this transition. With the advent of personal computers and advanced software, routine tasks like typing, scheduling, and basic correspondence management, once the domain of secretaries, have been automated. Consequently, these tasks have increasingly been incorporated into the responsibilities of professionals themselves, including managers and executives. In accounting, sophisticated software has made the data entry and basic bookkeeping roles of accounting clerks redundant. These tasks are now often handled directly by accountants and finance managers, adding to their comprehensive role. In creative and technical fields, such as graphic design and engineering, advanced tools have automated tasks that were typically handled by junior staff. Senior professionals in these areas now directly engage with tools like CAD software, reducing the need for junior drafting roles. The future, shaped by GAI, will likely see an expansion of these trends. In industries like marketing and advertising, AI’s capacity to generate basic creative content might reduce the need for certain junior roles. Instead, senior marketing professionals might oversee the refinement and strategic integration of AI-generated materials. Likewise, legal services might witness AI automating document drafting and basic research, once the remit of junior staff, shifting oversight and strategic refinement to senior lawyers. Moreover, GAI is expected to make complex business platforms more accessible to a broader range of employees. This will enable senior employees without deep technical expertise to perform tasks that were previously the preserve of specialists. Consequently, the skill requirements for senior roles may grow. The result is that many professionals and managers will be responsible for a long list of simple and quick tasks, that once took much longer to perform, and were the responsibility of more junior workers. #generativeai #ai #tasks #automation

CEOs are looking around their businesses and realizing they have a lot of people that they don’t need anymore, and they need a whole lot of capabilities they don’t have. That’s driving this weird layoff cycle. AI is disrupting the white collar hiring paradigm of the last 40 years. Skills that used to be high-value have seen demand collapse. Capabilities that used to be nice to have are suddenly in high demand. Doing background research on prospects used to make you a superior salesperson. AI has taken over that work. Technical salespeople who can work with AI tools to close more deals are in high demand. Grinding out thousands of lines of code quickly used to make you a superior software engineer. AI can do that. Engineers who can architect and design products that help the business monetize technology are in high demand. Answering hundreds of emails, calls, and messages a day is no longer an in-demand skill. Parsing and maintaining dozens of spreadsheets and creating reports aren’t either. Managing tasks, resource coordination, and tracking project deliverables are fading into background automation. What Bill McDermott calls “soul-crushing work” is actually how millions of people make a good living today. Those jobs are gone, and they’re not coming back. As harsh as McDermott’s words are, we need to hear them. The collapse of legacy roles is happening slowly enough that there’s time to reskill. Take the opportunity. Evaluate what parts of your job can be managed by AI and learn to do those more efficiently using AI tools. Find new ways to use the time that frees up. Roles are consolidating, so think about what parts of upstream and downstream processes you can take on. Upskill to manage larger workflows and deliver more of the business outcome yourself.

GenAI isn’t just challenging the ideas but also organizational structure/frameworks. The meticulously designed structures within companies, characterized by defined roles, responsibilities, competencies, culture, and a shared vision, are being challenged. One element of this structure is the management layers that typically come with deep context about the business. GenAI has created a divide in excitement levels across the organization. Senior leaders are engrossed in strategizing for GenAI's integration, fascinated by its potential. The ground team and engineers are eager to learn more about this technology and run experiments to evaluate it. However, this enthusiasm presents a conundrum for the middle and mid-senior management tiers, particularly for those in people management roles. It's crucial for them to not only grasp the technical nuances of GenAI but also to understand its broader business implications. This mid-management layer is where strategy meets execution. Any misses here will either create a situation of over-promises and then push the ground teams to achieve the impossible or miss the execution by not understanding the potential of this technology. Both of which could prompt precarious business decisions. In this transformative period, promoting a supportive culture is essential. Success hinges on how well an organization can equip its current managers with new skills while judiciously integrating external leaders (as new hires) to bolster the transition. If not handled properly, there's a risk of territorial behavior that might push real problem-solving out of the window. #ExperienceFromTheField #WrittenByHuman

AI was supposed to make us 24% faster. It made top developers 19% slower. That’s not a typo. That’s from a real world study. So what actually slows people down? 1. Tool overload. Developers had to manage too many AI outputs. AI tools struggled with code context. Humans still fixed minor issues AI couldn’t catch. 2. Mismatched expectations. Developers expected 24% speed-up. Reported feeling faster even when slower. Believed AI helped after the fact. There’s a 43% gap between perception and reality. 3. Unrealistic testing environments. Real work is messy, full of edge cases. AI still struggles with multi-step real-world issues. This study used live coding tests on real open source codebases. 4. Short-term adoption, long-term learning curve. Developers only used AI tools for a few dozen hours. Most weren’t optimized power users. Higher returns may come after 100+ hours. Speed-up might emerge with sustained usage and better prompting. This doesn’t mean AI is useless. But it proves that evaluating AI’s real impact needs more than benchmark bragging rights. Want to know what makes AI truly work inside a team? What do you think drives real AI productivity gains?

Last week, I had a conversation with a Managing Director of a US bank. I wanted to understand what they’re doing, and plan to do, with respect to careers in the evolving AI era. He explained the emerging role of AI and how AI will influence and impact careers of the future. Good People, over time, on most white-collar jobs, our supervisors will be AI. For example, a bank can set up a system where AI will handle customer support for customers who are investing $100 in a fund while humans will be required to call and speak with clients putting in $1m. But those calls could be monitored by AI so that immediately you drop the call, AI will analyze the call, examine context, etc on how effective you were on that call. At the end of the week, AI will summarize what you have done on those calls and send them to a senior manager. Feedback? AI can also provide you after every call! (Some US banks are just beginning to track calls made by their sales teams, not just for compliance purposes, but also to track how efficient they are on those calls. He does posit that AI is already listening to some of those calls). Good People, rethink your role at work because intelligent machines are at the doors.