A Conversation with Timid Tomm
Victimization and Parasitic Nature: The narrator feels seen as a "cursed gypsy, bruised and torn," emphasizing their vulnerability and the damage inflicted upon them. In contrast, the other person is portrayed as a "parasite sworn" who "feast[s] on
A Conversation with Timid Tomm
The Work-Tech Crossroads
What will making a living look like in 2032? That's the burning question we tackle head-on in this thought-provoking exploration of work's rapidly evolving future.
The verdict might surprise you - or confirm your deepest suspicions. Drawing on research from Oxford Economics, the World Economic Forum, and labor economists, we unpack the startling projection that AI could automate tasks equivalent to 300 million full-time jobs globally. But this isn't simply about job disappearance; it's about fundamental transformation.
We introduce you to the "friction principle" - the idea that traditional careers will still exist, but trying to perform them without AI tools will create significant disadvantages. Imagine running in sand while your competitors glide effortlessly on airport moving walkways. That's the future facing professionals who resist technological integration.
The concept of "skill inflation" emerges as particularly important - what counts as specialized expertise today becomes merely baseline knowledge tomorrow. By 2032, working effectively with AI tools won't be considered a special qualification but rather a fundamental expectation, similar to email proficiency today.
Yet not all career paths face equal disruption. We identify the most resilient roles - those demanding deep interpersonal connection, empathy, and complex problem-solving - while highlighting emerging opportunities specifically created by AI advancement. The common threads running through future-proof careers? Critical thinking, emotional intelligence, ethical judgment, creativity, and adaptability.
Want to see how this plays out in real life? We contrast two project managers in 2032 - Alex, who embraced AI tools, and Ben, who resisted change. Their diverging paths illustrate the stark choices facing today's professionals.
Ready to future-proof your career? Listen now to discover whether thriving without significant tech skills remains realistic, and how you can position yourself on the winning side of this technological revolution.
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You know, something I've been thinking about a lot, and I bet you have too, is well, what's work going to look like in, say, seven years, like 2032? Will it still be, you know, relatively easy to make a living if you haven't really jumped headfirst into learning AI and all this new tech?
Speaker 2:That's a huge question and, yeah, there's so much noise out there it's easy to feel overwhelmed.
Speaker 1:Totally so. That's what we're doing today trying to cut through that noise. Find the important bits for you.
Speaker 2:Exactly. Think of this as your shortcut. We want to give you the clearest picture possible without getting lost in like super technical jargon.
Speaker 1:Right, so let's just ground ourselves. It's 2025. Ai isn't science fiction anymore, is it?
Speaker 2:Not at all. It's here. We see it in creative fields customer service, medical diagnostics, definitely data analysis.
Speaker 1:And those generative AI tools.
Speaker 2:Yeah.
Speaker 1:Wow, writing code, making marketing stuff.
Speaker 2:Yeah.
Speaker 1:It's happening now.
Speaker 2:It really is, and the pace so fast forward. Just seven years, 2032,. The expectation is AI will be well, even more woven into everything we do Work, life, you name it.
Speaker 1:And this isn't just us guessing right, there are studies.
Speaker 2:Oh yeah, big organizations like the World Economic Forum, cognizant, oxford Economics yeah, they've all looked into this, especially generative AI. What are they saying? Well, oxford Economics, for instance. They estimated generative AI could automate tasks equivalent to get this, maybe 300 million full-time jobs globally 300 million. Wow, that's massive it gives you a sense of the scale, right. They talk about jobs changing shape, some disappearing, but also new ones popping up. It's a major shift coming fairly soon.
Speaker 1:Okay, so that really gets to the heart of it. What does easy to make a living even mean, then?
Speaker 2:Precisely. If easy means, you know, just coasting on the skills you have now without adapting, yeah, that might get tricky. You could face some real hurdles.
Speaker 1:So that's our mission today Break it down, look at the predictions, the data and figure out what you really need to know about the future job market.
Speaker 2:Okay, let's start with something interesting. A listener actually came up with this term the friction principle.
Speaker 1:The friction principle. I like it. What's the idea?
Speaker 2:Think about jobs that don't seem super tech-heavy today. Maybe a personal trainer, a local artist, your barber?
Speaker 1:Right hands-on skills.
Speaker 2:Exactly those jobs.
Speaker 1:They'll probably still exist in 2032. Okay, seems reasonable. So where's the friction?
Speaker 2:Ah well, that's the catch Trying to run that business or do that job without using any AI tools. That's where the friction comes in. It gets harder.
Speaker 1:Harder how, like finding clients.
Speaker 2:Yeah, that's one way Someone using AI might find clients way more efficiently, target them better. Or think about scheduling, billing, communicating with clients.
Speaker 1:Stuff that takes up time.
Speaker 2:Right, and AI could automate a lot of that. Free you up, even analyze customer feedback to improve your service or generate marketing ideas.
Speaker 1:Okay, I see. So the barber still cuts hair, but the one using AI for booking reminders, maybe analyzing local trends, they have an edge.
Speaker 2:A big edge Potentially. It's like you're running in sand while they're on one of those moving walkways at the airport.
Speaker 1:Huh, okay, that's a good visual. Running in sand creates friction.
Speaker 2:Exactly Less efficient, probably less profitable, harder to compete, even if your core skill isn't directly AI related.
Speaker 1:That makes a lot of sense, and you also mentioned something called skill inflation. What's that about?
Speaker 2:Right, Skill inflation. It's this idea that what we consider a high level skill today might become well more average tomorrow, because AI can do parts of it.
Speaker 1:So technology kind of devalues certain skills over time by making them easier or automating them.
Speaker 2:In a way, yeah, or it raises the bar. What was specialized becomes baseline. Think about coding, for example. Parts of it might get automated, pushing human programmers towards more complex architectural tasks.
Speaker 1:And mid-level jobs.
Speaker 2:Those could be really squeezed, especially if they involve lots of routine stuff. The skills needed to just get by are sort of inflating.
Speaker 1:So by 2032, using AI tools effectively might not be a bonus. It might just be expected, like knowing how to use email today.
Speaker 2:That's a great analogy. Yeah, very likely. It could just become table stakes for a lot of professions.
Speaker 1:Wow, okay. So it's not just jobs disappearing, it's the value of specific skills shifting dramatically.
Speaker 2:Exactly, which leads us to the next point which parts of the job market are feeling this pressure the most right now?
Speaker 1:Yeah, where's the vulnerability if AI is getting better at routine tasks?
Speaker 2:That's precisely it. Roles with a lot of repetition, predictability those are generally seen as most susceptible.
Speaker 1:Like what specifically?
Speaker 2:Think basic data entry, straightforward customer service queries, transcription work, things where the rules are clear and the task doesn't change much. Ai is often faster, maybe more accurate and cheaper for that stuff.
Speaker 1:Makes sense. Anything rule based is kind of AI's sweet spot right now.
Speaker 2:Right, but it's not just. You know, traditionally lower skilled jobs Even feels like programming.
Speaker 1:Really Programming.
Speaker 2:Yeah, certain parts Like writing basic code snippets or finding bugs in routine code, ai tools are getting surprisingly good at that. Same for some graphic design tasks like creating standard elements or parts of financial analysis involving processing huge data sets.
Speaker 1:So even in skilled professions, the more routine parts are getting automated or AI assistedisted.
Speaker 2:Increasingly. Yes, we looked into the work of Dr Lena Park. She's an economist focused on labor trends.
Speaker 1:Okay, what's her take?
Speaker 2:She confirms we're in a really significant transition because of AI automation.
Speaker 1:And which jobs does she see as most exposed?
Speaker 2:Similar lines, rolls heavy on routine data gathering or predictable physical work, but she makes a really important distinction.
Speaker 1:Which is.
Speaker 2:It's not always about job displacement, meaning the job vanishes entirely. Often it's about job transformation. The job itself changes, sometimes quite drastically.
Speaker 1:So it evolves rather than disappears.
Speaker 2:For many roles. Yes, she argues that the human part of the job shifts. It becomes more about complex problem solving, overseeing the AI systems, managing the exceptions.
Speaker 1:And the uniquely human interaction parts.
Speaker 2:Exactly the stuff AI currently struggles with Empathy, complex negotiation, strategic thinking.
Speaker 1:That fits with the friction principle idea. Even if AI handles routine stuff, you need humans to manage it, interpret it, handle the tricky bits.
Speaker 2:Right, and Dr Park also warns, if you don't learn to work alongside AI, you might end up competing for a smaller pool of jobs that don't require it.
Speaker 1:Which could mean lower wages or less security.
Speaker 2:Potentially, yeah. Wage stagnation is a real risk if your skills aren't keeping pace with what the market demands. She also mentioned some studies projecting that maybe up to 75% of jobs could require advanced digital skills by the early 2030s 75% and advanced digital skills.
Speaker 1:That doesn't mean everyone needs to be an AI coder right?
Speaker 2:Oh, no, definitely not. For most people, it's more about being proficient with the AI tools relevant to their job understanding data, using the software effectively.
Speaker 1:Like a marketer using AI analytics or a writer using AI for brainstorming.
Speaker 2:Exactly that kind of thing. Yeah, being AI literate in your own field.
Speaker 1:Okay, that clarifies things. So, while some areas are vulnerable, there must be roles where humans still really shine, even with AI around.
Speaker 2:Absolutely. Let's shift focus there, because human ingenuity, empathy, certain skills, they're still incredibly valuable. You're placeable, even.
Speaker 1:So where do we see that resilience?
Speaker 2:Well, think about jobs demanding deep interpersonal connection, empathy, complex human interaction. Those tend to be more AI resistant.
Speaker 1:Give me some examples.
Speaker 2:Healthcare is a big one Nurses, doctors, therapists. Ai can assist sure Diagnostics, data analysis. Even robotic surgery is improving. But that human touch, the empathy, the communication.
Speaker 1:You can't automate a good bedside manner.
Speaker 2:Precisely, or educators.
Speaker 1:Yeah.
Speaker 2:Inspiring students, fostering critical thinking. Mentoring that's deeply human. Skilled trades too Electricians, plumbers, carpenters.
Speaker 1:Right Dealing with unpredictable physical environments.
Speaker 2:Exactly. Ai might help diagnose a problem, maybe, but you need skilled hands and on-the-spot problem-solving to actually fix that leaky pipe or wire that old house.
Speaker 1:Makes sense. What about creative fields? We hear a lot about AI, art and writing.
Speaker 2:Yeah, that's a fascinating area. Ai can generate impressive stuff, but true originality, deep emotional connection that often still comes from the human creator. The trend seems to be towards humans using AI as a co-pilot, a tool to enhance their creativity, not replace it entirely.
Speaker 1:So AI handles some laid work, freeing up the human for higher level ideas and emotion.
Speaker 2:Sort of yeah, yeah and finally complex strategic roles Leadership, setting a vision, motivating people, navigating tricky organizational politics. Very human skills needed there.
Speaker 1:It's about judgment nuance connection.
Speaker 2:Exactly, we actually looked at the experience of a chef, marco Torres. He runs a restaurant that really blends tradition with modern tools.
Speaker 1:Oh interesting, how does he use tech?
Speaker 2:He use apps for inventory, online reservations the standard stuff but he also uses AI tools, sometimes for like menu brainstorming, analyzing trends, suggesting pairings based on what's seasonal.
Speaker 1:But he still emphasizes the human touch.
Speaker 2:Absolutely. He says people come for the authentic experience, the connection. The tech helps him run the business better, frees him up to be more creative and connect more with customers, but it doesn't replace the core craft, the passion.
Speaker 1:That's a great example Using tech to enhance the human element, not erase it.
Speaker 2:Perfectly put, and we're also seeing totally new roles emerge because of AI. Things like AI ethics consultants, helping companies use AI responsibly, ai system trainers, literally teaching the AI models, human AI interaction designers, figuring out how humans and AI can work together smoothly.
Speaker 1:Wow, yeah, those sound like they'll be crucial.
Speaker 2:Definitely. And if you look at all these resilient jobs and these new emerging roles, there are common threads.
Speaker 1:Right. What stands out?
Speaker 2:Critical thinking, Definitely Real emotional intelligence, understanding people, ethical judgment and high level creativity, creativity and adaptability skills where humans still have a distinct edge over current AI.
Speaker 1:Okay, so let's loop back then. The big question will it be easy to make a living in 2032 without these AI and tech skills Based on all this? It sounds like probably not for most people.
Speaker 2:That seems to be the most likely conclusion. Yeah, it doesn't mean every single job requires you to be an AI guru, but trying to navigate the job market without any understanding or ability to use these tools, that's probably going to be much harder.
Speaker 1:More competition for fewer non-tech jobs, maybe hitting a ceiling sooner wage issues.
Speaker 2:All potential consequences, yes, Facing skill gaps, feeling less secure it just makes the professional journey potentially more challenging.
Speaker 1:But here's the twist right the easy path in the future might actually involve doing the hard work now, learning and adapting.
Speaker 2:That's the paradox, isn't it? Proactive effort now could lead to a smoother ride later.
Speaker 1:So what does that proactive effort look like? What should people be doing?
Speaker 2:Well, first, basic digital literacy is just the foundation. Everyone needs that. Then cultivate AI awareness. Understand what it can do, especially in your field, find relevant tools and learn to use them.
Speaker 1:And focus on the human skills.
Speaker 2:Absolutely. Double down on critical thinking, communication, creativity, emotional intelligence those become even more valuable and finally, embrace lifelong learning. This isn't a one-time upgrade. It's a continuous process.
Speaker 1:So it's about future-proofing yourself through adaptability.
Speaker 2:Exactly, and you know, this isn't just about individual careers.
Speaker 1:It raises bigger questions for society too, for sure, like should everyone have to become some kind of tech expert, or do you need to make sure non-tech jobs are still valued, still provide dignity and a decent living?
Speaker 2:Huge questions. We looked at insights from Dr Ethan Cole, a philosopher who studies tech ethics.
Speaker 1:What was his perspective?
Speaker 2:He really stressed that a healthy economy, a good society, needs to value a whole range of contributions. Dignity and work shouldn't just be tied to how tech savvy you are or how easily an algorithm can measure your output.
Speaker 1:That's a powerful point. Work is about more than just productivity numbers.
Speaker 2:Right and Dr Cole suggested that, as automation advances, we need serious conversations about policies like, well, universal basic income, maybe massive investment in retraining and maybe rethinking what we even consider valuable work. We need an inclusive future.
Speaker 1:These are massive societal discussions and the impact won't be the same everywhere. Right Global differences.
Speaker 2:Definitely Right. You might see slower AI adoption in some sectors and developing nations, for instance, but globalization can also speed things up unexpectedly, so adaptation and policy talks are crucial everywhere.
Speaker 1:Okay, to make this really concrete, let's imagine two people in 2032. Two different paths.
Speaker 2:Good idea. Let's picture Alex. Alex works in project management Back around now, 2025,. Alex saw AI coming and maybe felt a bit worried, but decided to learn.
Speaker 1:So Alex learned AI tools for project planning, risk assessment, team collaboration.
Speaker 2:Yeah, leaned into it Now in 2032, alex is way more effective. Ai handles a lot of the routine tracking, data analysis, reporting. It frees Alex up for the strategic stuff managing complex stakeholder relationships, creative problem solving. So Alex feels Challenged, valued, secure, comfortably using AI as a partner.
Speaker 1:Okay now let's picture Ben also a project manager. But Ben was skeptical, stuck to the old ways, didn't really engage with the new AI tools.
Speaker 2:What's Ben's 2032 look like.
Speaker 1:Well, Ben's finding a lot of the tasks he used to do are automated now, or colleagues using AI do them much faster. The purely traditional PM roles are scarcer, maybe offer less growth.
Speaker 2:So Ben feels.
Speaker 1:Probably uncertain, struggling to compete, maybe feeling a bit left behind, less secure about the future.
Speaker 2:Now, obviously these are simplified sketches.
Speaker 1:Right, just illustrations.
Speaker 2:But they show how choices made now about learning and adapting could lead to very different outcomes down the road. The future isn't set in stone.
Speaker 1:Our actions shape it Exactly. So, wrapping this all up, the answer to that first question will it be easy to make a living in 2032 without deep AI tech skills? For most people, the answer leans towards no. It'll likely be significantly harder.
Speaker 2:That seems the clearest takeaway. The 2032 work world looks like one where tech, especially AI, is deeply embedded almost everywhere. Hopefully, ai is deeply embedded almost everywhere.
Speaker 1:And the people best positioned will be those who adapt, who keep learning, who build both digital skills and those irreplaceable human skills.
Speaker 2:Right, it's not about fearing AI. It's about understanding it, partnering with it, shifting your own focus from routine tasks to judgment, creativity, connection, often using AI to help with that.
Speaker 1:So the most viable path seems clear Engage with the changes, be curious, learn, explore. Engage with the changes, be curious, learn.
Speaker 2:Explore. That's the proactive stance. The future of work is changing, no doubt about it. Your ability to change with it really dictates how easy or hard navigating your career will be.
Speaker 1:Which leaves us with a final thought for you, the listener, thinking about your own situation, your field. How realistic does thriving without significant tech skills seem in the long run? Is learning to work with AI feeling inevitable for you, something to chew on after our deep dive today?