Understanding the Current Situation A lot of people are worried about ChatGPT, Bard, Llama, and all the other large language models taking their jobs. But they haven't really considered the underlying issues that have led to today's situation. I'm going to walk us through those issues and problems and use that to project what the future of the industry might look like, regardless of automation and large language models. https://youtu.be/sgTTk_1Tb5Y?embedable=true Short video: for those who are looking for the TLDR The Effects of Company Cuts and Migration to IT Last year, we saw significant cuts from large companies like Google, Amazon, and Facebook, leading to a loss of employees. The finance sector experienced hiring freezes, yet we witnessed one of the largest migrations of talent into the IT industry. On top of that, the UK IT industry has been growing 10% year on year, and the states that the world needs to reskill a billion people into IT to maintain its current pace. World Economic Forum I enjoy mentoring in tech and usually have at least 3 or 4 people I’m working with at any one time, and half of them are coming over to IT from their existing job. Re-skilling and investing their time in coding, architecture, and infrastructure automation. Questions to Consider With these changes, ask yourself: What happens when a large volume of people from different industries moves into one industry, all with the same skill set? How will the supply and demand challenges we have today project forward as the currently undersupplied area fills up with people? How are business and thought leaders responding to these changes today, and how will they respond in the future? The Misconception of Supply and the Future of Talent Most people think that the issue is a lack of talent, and while it's true that large companies struggle to find the right talent, we're not considering what happens tomorrow. The markets are already responding to minimize the impacts of the talent shortage. Automation with ChatGPT, Bard, and others will happen, but even without it, there are business mechanisms that replace multiple people with one. This contrasts starkly with the outsourcing practices of 25 years ago when one person would be replaced by 15. Market forces drive the strategies of today, which in turn impact the landscape of tomorrow. The Potential Future Model In the future, we might see a team of one or two super senior people overseeing automation and business processes, similar to how a single employee supervises several self-checkout machines at a grocery store. This model could become more prevalent in the future. But again, even if it isn’t automated this way, it would be reduced in some other way, and it would be risky to assume there will always be an abundance of, say, web developer roles. Opportunities in the Changing Landscape As things move forward, regardless of automation or business processes, they will simplify the systems in place, but things won’t just stop. We won’t pat each other on the back and say, job done. Scope and requirements never end; they just expand to cover new domains, and the challenge will be spotting what those domains might look like. For AI alone, here is a starter for 10: AI Ethics and Compliance Officer: Ensuring AI systems adhere to ethical guidelines and comply with legal regulations. AI Model Auditor: Reviewing and auditing AI models to ensure their accuracy, fairness, and reliability. AI Data Curator: Organizing, labeling, and maintaining large datasets used for training AI models. AI Trainer: Teaching AI systems to perform specific tasks, including fine-tuning and improving their understanding of human language. Human-AI Interaction Designer: Designing and optimizing interfaces between humans and AI systems to ensure seamless and efficient communication. AI Explainability Specialist: Helping users understand how AI systems make decisions and predictions by providing clear explanations and visualizations. AI Security Specialist: Protecting AI systems from malicious attacks and ensuring the privacy of user data. AI Integration Consultant: Assisting businesses in integrating AI solutions into their existing workflows and processes. AI Policy Advisor: Guiding governments and organizations in developing policies and regulations related to AI usage and implementation. AI-powered Application Developer: Building and maintaining applications that leverage AI technologies to enhance user experiences and solve complex problems. My advice is to get ahead of the curve,  look at the problems of tomorrow, and expand your mind to think outside the box in terms of what potential new areas of work could open up. If you think this is worth discussing further, let me know in the comments, and I can make a post on more speculative jobs and what they might look like.

The Future Job Market Amid Automation and Large Language Models

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