1. BC unveiled a new budget with higher taxes, service cuts and a spiralling deficit going to $9.6-billion. The BC government needs to find a way to do more with less. It needs to look for efficiencies.
2. The Code With Us put out a project for bids: “Improvements to Air Quality Warnings Shiny App” ( https://marketplace.digital.gov.bc.ca/opportunities/code-with-us/7f216ab7-44ed-414b-b5a9-48988ea44655 ). It’s to be coded with the programming language “R.” It’s a powerful language and used in the BC government IT projects. At $16k, this is a decent little project for some R conversant developer.

I asked myself: How much of this could be done by AI?

First, I drafted the proposal to answer the bid (link) using Claude AI. I’m not going to create a winning proposal. I can’t get this work. I don’t know R and I don’t have any projects with R experience. Nevertheless,a project like this can’t be won if one doesn’t submit a proposal.

Second, I took the project details from the Code With Us post and had Claude AI draft a project requirements document (PRD) ( link ). If the project details were accurate and descriptive, the PRD should reflect what’s involved to build this application.

Third, I built the app. I don’t know R. I have almost 45 years of coding experience, so I know how to get a grasp of a technology that I don’t understand. I know what questions to ask. I took what little I knew. I combined that with a new Github code repository ( link ). I opened up the OpenAI service, Codex and began the code generation. It took several rounds of steering the code, but in the end I had a working application written in R. I put it up in a deployment environment and tried it out. It works. It’s important to note that this works according to the plan and a plan built according to the marketplace opportunity. In a real world use, it may fall short of what’s needed. If it does come up short, the planning step can be re-evaluated and the code build can be re-run.

This isn’t the first time I’ve used Codex to build code. I have used it to quickly build WordPress plugins and apps. I have used other systems like Claude, Loveable, Bolt and Minimax, and Grok to build applications. These AI systems work great to build applications quickly. They all need good planning and oversight, but they can all turn out good code.

In a cash strapped world, we need to find ways to do things better and faster. I used artificial intelligence to write a proposal for this $16,000 project; write a plan; implement that plan; and deploy the application in something like 3 hours.

The Anatomy of a Software Project

An application development project can be described as having three components:

• Planning
• Development
• Viability

Using Artificial Intelligence (AI) to develop applications is sometimes called “Vibe coding.” Almost all of the development is left up to the AI. Taken to the extreme: the planning, development and viability can all be turned over to your favourite AI builder.

Organizations ranging from private industry through to national governments are looking at AI and wondering how it can help them. How AI can speed delivery; drop the headcount in their organization; and/or deflate the budget requirements. AI can accomplish all three.

Planning, development and the application viability could be thought of as a three legged bar stool. If not built right, that bar stool will be a disaster to use. When building a project, these three elements can compete for a finite well of time, money and attention. Short-changing one element, can force the other elements to balloon to cushion the shortfall. It’s the adage of “you can have fast, cheap or good– pick two.” The competing priorities could live in harmony. At the same time, they could be faster, cheaper and better. Pick all three?

Maybe we don’t need to build project bar stools. If we break down these parts of a project when armed with AI, project completion could look very different.

Planning

Planning doesn’t need to be a formal, drawn-out process. In the most simple terms: it’s the headline. What should the application do? What should it work with? What does it do?

Project planning captures the timeline, specifications, diagrams, and details and anything to trap the elements of the project. This planning includes the user interface (UI), the user experience (UX) and a firm picture of what work the application does.

Planning is the most important and least visible part of an application. My personal experience: if a project is exhaustively planned, it can land on a dime. All of the pieces make sense. All of the details are captured. All of the stakeholders appreciate the project.

It’s pretty clear that planning is sometimes skimped out. Many programs show up full of holes. The functionality doesn’t work. There are glaring security holes. They just don’t work.

Development

From a programmer’s perspective, the development is “the work.” We know better, but for all intents and purposes, the programming appears to be the work. Without the code, all you’d have is great planning documents. It often takes up the lion’s share of the time and budget involved. If the planning is clear and succinct, the development phase will be the majority of the project. If planning is shortcut, the development goes from a smooth ride to bumpy disaster. Questions arise. Vagaries fester. It plays out the phrase, “If you fail to plan, you plan to fail.” Inadequate planning will drag out a project. Development without a plan can be an expensive, exhausting exercise in frustration.

Viability

A plan is a good idea. Development is the realization of that plan. Viability: it’s how the project goes out into the world. UI and UX from the planning phases hits the screen. Does it work? Do the users make sense of it? If people dislike the interface, they won’t use it.

Beyond the look and feel, the really big consideration: security. As code does more things– more connectivity, more utility and more performance– there are more opportunities for problems that arise from security holes. Can the logins be faked? Can the data be scooped? Can financial and personal data be siphoned out of the application? An attractive app with big security holes is radioactive.

Assume the application is pretty and all of its security is locked down. Will it work long term? There is a concept called “technical debt.” Technical debt are the awkward parts of launching a program. Can the program be added easily by the user? Is its data portable when needed (migrating to a new device; or restoring a backup)? Can the program be upgraded as needed? Will the code work with newer operating systems? There are thousands of fantastic programs, plugins and tools that worked on old computers, but die on anything from the 2000s. When an application works but hides fussy elements– that application isn’t going to flourish.

After the coding is all done, the other front of viability: adoption. Marketing, documentation, support and marketplace fit are all challenges to the longevity of an application. If a great product is also an unknown product, it’s eventually doomed through a lack of adoption.

Good planning, smart development and lots of testing will expose issues. Viability comes down to the survivability of the application when it goes out into that big cruel world.

How AI Changes The Game

People are still confused about how artificial intelligence works. While touted as intelligence, what it really does well is a colossal exercise in auto complete. Give a chatbot a prompt and it runs with it to satisfy the prompt. Chatbots have indexed massive amounts of programming code from other available projects. They can use that code as an example of how to build new code.

AI works very fast. In the last year, AI gained the capacity to work long. It can take on increasingly larger projects, spending the time to code elaborate solutions. The OpenAI service, Codex, is capable of developing very large and elaborate applications. It can store its code in a code repository– a storage tool to track changes and manage the sharing of the code between developers.

At its core, AI is a computer system: it needs explicit direction to do anything. AI is fantastic at filling in the blanks but those blanks are where variability can creep in. The solution is to be exhaustive on the details. AI can take in a very large set of instructions to work from.

Our workflow: we write a detailed product requirements document (PRD). It outlines what the project needs to succeed. We build that with Claude, iterating the project plan until it’s detailed enough for a developer to work with. If it’s good enough for a developer, it’s good enough for an AI. We hand that PRD to Codex and ask it to develop the application drawing from the PRD details. After the work is detailed, we do a combination of manual and AI driven code reviews. We draft security documents to cover testing and find issues that could threaten the success of the application and the security of its data.

Before the chatbot era, development step took the lion’s share task of a project. A deep planning exercise was always good, but it could be abbreviated by personalities and budget pressures. No one wants to short change the security and viability aspects, but those aspects get squeezed just to get a product out the door. What resulted were applications that did the work, thin on planning and band-aided security.

AI flips the script. The biggest component– the development– can be handed over to Codex and similar tools to build the code. That bulk can be externalized. The work happens much faster. It can happen better. It can be coded at an expert level. The found time and found budget can go into planning to get a clear target. The breathing room can go into the viability topics to ensure it’s safe, it’s appreciated and its utility has some longevity.

How Is This Relevant to 2026 British Columbia?

The BC government’s Digital Marketplace posted a $16,000 opportunity. Depending on billable rates, $16k ranges from 320 hrs. of development at $50/hr.; all the way to 80 hrs. of development at $200/hr.. That 80 – 320 hours of development time should cover planning, development and security / viability. It will likely be a 25%-60%-15% split of where the hours go. Arguably, the majority of any budget goes to the development phase. What happens to project labour breakdowns if the majority of the work can get replaced with AI?

Imagine if the project splits were to radically change:

• 40% of the budget into planning and prep;
• 20% of the budget goes to the development;
• 40% of the budget goes to security and the longevity of the application.

Beyond re-cutting the resource pie, shrink the pie. Look at the $16k project above. If they forecast that 60% of the project or $9600 went to development, but that could be done with a few hours of vibe coding and a strong requirements document– then a project needs less time to deliver. Replace that $9600 bulge with 12 hours of development; precede it with 24 hours of planning; and follow it with 24 hours of viability work. Use AI to get more out of the planning work; and then get more out of the viability steps at the end of the project. Maybe a $16k project could become a $10k project delivered faster and better thanks to AI. That’s a savings. Wherever there is knowledge work (coding, number crunching, etc.), AI can play a role in delivering that work better, faster and for less money. The delivery comes down to skill.

Organizations look at AI with technological superstition. They think it will simultaneously take all the jobs and do the work poorly. Some organizations have laid off people or stalled hiring because they’re replacing people with AI systems. Those organizations have seen minimal wins. They’re missing the role of AI.

AI in the workplace is not about replacing people. It’s about enhancing them. Think of a good suite of AI tools and techniques as an Iron Man suit, not a robot worker. Your people could do more, do it better and do it faster. That found time can be sunk into making solutions that are more ruggedized and well tested.

Organizations looking to deliver more for less need to look at what artificial intelligence can do to help. Imagine if the BC government could deliver its IT projects for less money? That’s not going to knock down the tremendous BC government deficit, but every little bit helps.

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Our economy and society are working in well-known models. With some minor updates, this is how things will continue to roll until the impacts of artificial intelligence are inescapable. The inescapable moment will come with the general distribution of AGI. We’re in the pregame of that change. Every piece of technology is getting the AI treatment. Government workers are seeing their workflows getting mimicked by AI to process easy tasks in moments and process them automatically. Businesses used to be in dire need of their graphic designers for their branding, advertising and marketing. Many of these tasks are now handled by AI image generators. AI is cranking out AI images, short videos, janky marketing copy. The turnaround time for graphic design and marketing assets used to take days. Apps return those assets in minutes.

All of the simple stuff is going to AI. Intellectual workers who used to appreciate the mix of difficult and easy tasks now have only the hard stuff left on their plates. For junior talent, the change is more profound. Where once they were given all of the easy work, now they’re not being given any work. Entry level jobs are drying up.

Parents will know this dynamic better than others. When a baby is born, there’s little danger of the kid getting into something they shouldn’t. As they grow, the water level of jeopardy rises. Cover the plugs in the wall boards. Put the sharp stuff up high. It’s a slow motion flood of danger. That’s happening with intellectual labour. If AI is the toddler, it’s at the electrical outlet: it has its paws all over the entry level jobs. Eventually, AI will be able to grab mid-level jobs. Before we know it, it’s going to be reaching high for the elite level tasks that usually require senior experts. We’re not there yet. But keep in mind that OpenAI rolled out ChatGPT less than three years ago.

In less than three years, AI has chewed through entry level graphic design, CGI and programming work. It’s overhauling the workflow of large organizations. It took decades of work in the study of protein folding and did all the homework in weeks. It’s true that the level of skills in practice by an expert are exponentially greater than their junior counterparts. But technology grows exponentially.

AI Doesn’t Need A Bathroom Break

For workers, this is a dire time. The bottom rungs of the career ladder have been chopped out. With each passing month, more rungs are going to be chopped out. If someone hasn’t entered into their career already, I don’t know if they could. I follow Indeed’s job feeds. The entry level jobs are gone. At the same time, the elder statesmen in the workplace are peacing out. Many of them retired during COVID. Some of them are ready to do so now. Employers are getting worried: the experts are retiring. The mid-level people are going to be drafted up to the majors before they’re ready. If those mid-career people don’t skill up fast, they’re going to get caught in the rising tide of AI. At the same time, businesses are looking at what AI can do. Some of them are adjusting their product offerings to lean on AI.

For the general public, this is a mixed bag. They get very informed results at lightning speed from AI. In the cases of image generation and marketing copy, that’s sometimes awesome; that’s sometimes slop. There’s good and bad, but the short assessment is that AI is good.

Do Entrepreneurs Like AI?

For entrepreneurs, this is a golden age.

In the 1990s, I was approached by people who basically said, “if you build this app, I’ll split it with you 50-50.” 50-50, huh? So: I make it real and sink in my time and in your largess, you’ll give me half. I rarely accepted those deals.

By the 2000s, the tune changed up. Entrepreneurs had managed some growth and prominence. They promised programmers and designers glory. They suggested that people could work for “exposure.” Exposure doesn’t pay the rent. Lots of influencers could peddle their notoriety for free labour until the talent realized how poor the pay-off was.

The 2010s: the VC game. Venture Capitalists have been around forever. They have had a good run, making the Internet an intrinsic part of our lives. So many startups did a speed run of getting ready for acquisition. That came with the big payday and their cash out, leaving entrepreneurs seeking encores.

Now, it’s 2025. AI powered apps are getting adoption at a lightning pace– almost too fast for VCs to hop on board. As a for-instance, search Youtube for “$10k / month AI App” – there’s an explosion of small scale developers ramping up to health incomes in very little time. They’re finding all of the nooks and crannies where AI could play a role to make people’s lives better, faster and more efficient.

While AI entrepreneurs are making bank, what about those poor entry level white collar workers? With how things are going now, they’re doomed. They’ll never get the first job. They’ll never skill up to be mid-skilled staff. Less likely still, they’re not going to get to those exalted expert positions. We all thought automation was going to take the factory jobs and put robots in McDonalds. Instead: AI has gotten all of the creatives and the paper pushers– the stuff that it easy to feed into a computer.

Where does that leave us? On the current course, this leads to economic disaster. When AGI becomes a part of our day-to-day life, this trend will accelerate. More people will lose their jobs to automation. Corporations will become profitable to a point. Corporations need consumers and out of work consumers are not good consumers. Once we send the workers home, there’s going to be a profound down shift in the fortunes of industry.

Universal Basic Income (UBI) is often touted as the solution to the jobless future. I love the idea, but I can’t make it work. Use Canada as an example: 30,000,000 people. The simple UBI payroll would be $1000/mo – or $30-billion per month paid out to people with heartbeats. I know: pay children? First off: children need food and housing. Second: our social and economic changes have really put a crimp on the urge to start families. There will always be children, and they’ll always need lunch. So, how would Canada pay out a $30-billion/month payroll? Some existing thoughts for how to fund it:

• Increase the GST. Make it 20%. The affluent would pay a lot more for their goodies. The poor would also pay, but having less money means they’d pay fewer GST dollars.
• Charge a robot tax. That’s a fast track to squelching progress. Those who don’t innovate, dodge the tax. Those who sneak in innovation, dodge the tax. Those who don’t want to pay the robot tax can just go offshore and run their robots there.

If I Ran The World (well, Canada)

If I ran Canada, I would look at the landscape of the problem. I would tackle our challenges and opportunities with new policies from government to usher in the world we’re heading towards.

As AGI rolls out, we’re going to eventually lose many of the jobs. It is true that AI will create new jobs and new opportunities. As long as we need experts, their value will increase. At some point, their comparative value and the comparative economy of turning to automation will cross and the experts will be sent home. Their robot replacements will do the work faster, cheaper, without ego and without bathroom breaks. They will break down and for some time, robot repairmen will be the new superstars… until a robot replaces them.

Our demographic is aging: the median age is climbing. This will continue to shrink the number of children and grow the number of seniors in all of the developed countries. Eventually the biggest cohort (Boomers) and their children (Gen X) will be retired and/or in elder care. Even as Canada games out raising the retirement age, it’s eventually going to hit the biological limits of forcing 75 year olds onto the bus every morning to oversee a diminishing workforce of mid-level people who fear losing their jobs.

Automation is going to decimate retail and those retail clerk jobs. It’s going to take the fast food workers out of the back of house and front of house. Kiosks will be sending orders to burger machines that run 24×7 and never pick their noses. The burger flippers are doomed. All it’s going to take is someone rolling out a “Robo-Burger” franchise into the marketplace for every other fast food joint to transform. Automated services are creeping into our lives. At some point, they will be a fixture of business.

Our youth are aimless. Unemployment in the under 30 group is huge. Every generation gets to the age where they look at 25-year olds and say, “when are going to do anything with your life?” In this era, it’s even more profound. Fewer of them are moving out, getting jobs or starting families of their own. They’re jammed into being teenagers for a decade or more.

In China, this situation is a 5-alarm fire. The One-Child policy and the disproportionate number of boys to girls had led to a dilemma. The boys are now men who can’t find partners. They have aging parents with no siblings available to share the load. Good jobs are not as plentiful as they’d wish. The men make a career out of elder care, locked in a cycle of late teenagehood lasting deep into their 60s and 70s. When their parents die, those boys are going to inherit what their parents left to them before following them to the grave in a couple decades.

The sliders of profitability and affordability are going on a roller coaster. That’s going to see a lot of people gouged. It’s going to see disruptive players eat the lunch of unprepared profiteers.

If our economy and society get broken, we’re heading for trouble. When you see protests and civil unrest, what you’re really seeing is people who didn’t need to show up at work that day. Either their job is already gone; or they didn’t care if they lost the job. Civil unrest happens when people have the time to be unruly and when they have nothing to lose. If left as-is, jobs will be in short supply. Incomes and the standard of living will be poor. There will be a lot to grieve and the time to protest or just lash out.

How do we make this all work?

Models of what works often exist in our past. LIkewise, models of what fails will stick out in our history like sore thumbs. The driver of the evolutions needs to come from three places. The government needs to set legislation and establish norms. Workers need to expect more from employers. People need to re-evaluate their role in society and where they find contentment.

My models of what works come from some simple places: COVID, Victoria BC and telecommunications.

COVID

The house arrest vibe of COVID wasn’t fun. What I did like: working from home. More so, after working from home off-and-on for over 40 years, it was nice to see a defacto workplace to match my own. Working from home takes the commute out of the affordability math. It gives workers back 1 to 3 hours per day of unpaid labour that went into commuting. It let them raid their kitchen for affordable, healthy food instead of fast food and salty diner fare. That kitchen raid: it’s cheaper than a restaurant. The found money from no commute and no dining out: that’s money in workers’ pockets. Staying at home is a cold and flu circuit breaker: less illness means less misery and fewer sick days. Also: fewer trips to the pharmacy for $20 cough syrup.  Employers win too: they can shrink their office sizes. They can save on office furniture, phones and all of the trappings of a bulky workplace. As AGI takes jobs, businesses can see their bottom line thicken without seeing the desks empty out.

Working from home. Small offices. Reliance on AI labour. These moves make life more affordable for workers. They also make profitability more likely for businesses.

COVID also showed us that what was once impossible flipped overnight. The “we’ll never do that” evaporated under necessity. Governments also were able to quickly open their wallets to cover the crisis with cash. We can move fast. Industry can move fast. Even governments can move fast when their political lives depend on it.

Victoria BC

Victoria BC: one of the least affordable places in Canada. It also only has 46% employment. Yes: 54% of the residents live in the least affordable city and they do so without a job. If more than half of the people can make a go of it without UBI, having a job isn’t the lynchpin that we maybe thought it was.

Most of the idle folk break into these subsets:

• Children. They don’t work, but they could clean up their rooms a little, you know.
• Retired folk. There are a lot of retired people living here and living off of a pension.
• The disabled. There is a big cohort of people who use a disability pension to survive.
• People living off of annuities. Some people have a nest egg to fund them for the rest of their lives. However they came by it, they are not a small population in Victoria.
• The destitute. Some people live off of nothing. They couch surf. They sleep rough. They rely on the kindness of strangers. They subsist off of aid agencies. When people speak of UBI and the jobless future, this is the cohort that sets fear in our hearts. We don’t want to become poor, homeless, at risk, and in trouble. If the robots take our jobs and we have nowhere to turn, this is our fate.

Of the 400,000 people in Victoria; and the 216,000 who don’t have jobs; 1,800 are destitute / homeless; and 56,000 live below the poverty line– some of whom are actually the working poor. The remaining 160,000 get by without a job. So: you don’t need a job to survive– even in one of the least affordable cities in Canada. If 54% of the community don’t need to work, how many people really need to work?

In Victoria, despite the high share of non-employed people, there is a labour shortage. It has led to many businesses shortening their operating hours. The affordability crisis keeps people from working in low paying jobs. What if low paying retail and service jobs were replaced with automation? Automation could turn some businesses into 24×7 businesses. If the drive-thru order is taken by AI, then the food is prepped by robots, why not keep it open 24×7. Door Dash and Uber Eats are already delivering goods beyond food. If they could pick up supplies from grocery stores and pharmacies run through automation, they could prep the orders for delivery at any hour. Imagine the impact on day-to-day traffic flows if the grocery runs happened by robo-delivery at 8PM instead of after work in-person. Serving those needs could provide new opportunities. Grocery stores that serve only automated deliveries could be set-up in locations with poor curb appeal, but excellent property prices. The rise of Door Dash has brought about “ghost kitchens”– restaurants that only consist of a kitchen and place to pickup orders. Moving operations to more affordable venues could make those ventures more profitable. It may even allow them to offer lower prices… or prices that don’t spike as readily as we’ve seen in the last few years.

What about the low paid service workers ejected by automation? They could skip from entry-level up to management. Consumer needs will persist, so the markets and opportunities will persist, too. Employee-owned businesses could make the same income but distribute the profits to all of the staff. People can invest in businesses that go heavy on automation and live off of the dividends and profits. Government could set up policies and incentives to encourage low income people to participate in the investment of automation businesses then live off of those proceeds.

Telecommunications

Telecommunications and media used to be MUCH more expensive. Up until the 2000s, people with long distance connections used to go broke because of their phone bill. The proliferation of cellphones quickly led to national calling plans; then unlimited minutes; then unlimited national calls – poof. Your $300 phone bill got replaced with a $60 cellphone bill– a phone you can use while at the beach, not tethered to that phone table in the front hallway. It became a massive improvement at the same time, the service (long distance) basically de-commodified. At the same time, Skype then Google Meet and Zoom made even the cellphone bill optional.

Netflix and Amazon Prime have replaced movie rentals taking Blockbuster and all of its competitors off of the playing field. There’s more to this topic as all of the streaming services are now making the replacement option more balkanized and expensive, but the overall service delivery is much less expensive.

The creation of media: that’s an entirely revolutionized situation. When I was a kid, I got a tape recorder– I could make media and I was so grateful. I did get an 8mm film camera but the cost of film developing wasn’t going to work for my 10-year-old wallet. I spent my teens and twenties coveting the video cameras of others. In the 2000s people could get digital cameras for a high cost with lousy resolution. Moore’s Law quickly improved audio and video capabilities. Nowadays many of us have 4K video cameras in their pockets. With the advent of text-to-AI video, there may be another implosion of costs with a beach scene and a space battle costs the same pennies to create.

Moore’s Law on cellphones has created a different problem: profit contraction. Your $100 cellphone from 2000 did so little, and your current $1500 phone does so much. By Moore’s Law, that phone should be $10 now. Why did it go the other way? Profit. The slicked back sales reps at cellphone stores need a commission to make their job worthwhile. The commission on a $10 phone would be pointless. An artificially expensive phone would be seen as gouging. To keep the price points high, the features have to continue to skyrocket: more memory, high resolution, better apps.

As technology improves cost and quality continue to improve geometrically. It’s the best example of “decommodification.”

Decommodification

We’re all well aware of how supply chain disruptions made commodity prices jump. Inflation is about the deterioration of buying power. Economists cheer when it’s low and we all suffer when inflation is high. Deflation is often considered worse. I am not an economist, so I stand on my small sandy hill and say: Deflation is good. We need it. We need affordability more than we need the benefits of long game compounding investment interest.

Deflation and decommodification will drive affordability. As people need less money, it changes the math. Where before maybe a household need $150k to keep the lights on, maybe automation can deliver a plunge in prices to give people a decent life with much less money.

Housing

House prices are the best example of an economy off course. The houses have not gotten better. The ground has not gotten more verdant or picturesque. The population pressure have made them more sought after. The malpractice of government has made housing a lot more expensive for new builds. It means that existing home supply is a bargain– a bargain that can remain a comparative bargain event if the price points rise closer to the new housing supply. Our demand is constant (1 person needs 1 home); the supply has fallen behind demand. Housing prices should have increased, but not to the extent we’re seeing.

Housing needs a soft landing to flatten inflation. Government policies can make this happen.

My first suggestion: change tax laws to let all mortgage holders write off the interest they pay. In the early years of a mortgage, most of the payments go to interest. As they continue, they start to bite into the principal of the loan. If the mortgage holders can get a tax credit for that interest, it would benefit them. People who paid cash for their homes: they wouldn’t get a tax credit. As people progress through their mortgage and the interest share diminishes, the tax credit diminishes. Those tax credits can be paid by also changing the tax structure to extract more money from the big banks. Yep: that will kill the best friends of politicians (ie. the banks), but making banks into a source of revenue for the general public is long overdue.

Second suggestion: make the CRA the lender of last resort. Banks are profiting off of mortgages. They’re making billions of dollars. Why shouldn’t the government do that instead? Reap those profits and use them in lieu of taxes to pay for things we all need in the world of AGI.

Financing and affordability are more important than simple housing supply. Developers have been allowed to slow walk housing supply to keep healthy profits rolling in. There needs to be policy shifts to change the housing situation. When housing becomes less expensive, it increases the likelihood of access to home ownership; and it takes the pressure off ot people’s budgets.

Look at what happens when there is a big housing announcement, and the government pledges something like $100 million to a program. In today’s markets, that’s equal to 400 apartments or maybe 200 homes– that’s not a government program. That’s a lottery. A lottery that millions of people lose out on. We lack affordable housing more than we lack housing. If the CRA were a lender, it could couple its access to money with the government’s ability to set policy and legislation. It could limit what properties are eligible. It could set rules that sellers may have to adhere to. Best of all: a $100-million program gives 400 people apartments. $100-million in mortgages gives those same people housing and it eventually pays back along with a bonus $100-million the government can use to fund more mortgages and/or pay for government programs. Governments can also pledge long mortgages, giving people some predictability to their futures. This pressure valve in the mortgage market will force banks to up their game.

Electricity

As we decarbonize, we’ll rely more on the electrical grid. Eventually, we’ll be all the way swapped over to electric heat, electric cars, and the need to power our compute. Relying on one source is a tremendous risk. Some time ago, the price of solar dropped to the point where it’s the cheapest source of energy. Eventually, fusion power will come about– maybe in 20 years? 😉 Thorium fission will come into play to power remote locations and industries that may need much more than what the power grid could easily handle. Best of all, they’re small and relatively safe. As they become common, their price could drop. As a base load power source, they could back stop the intermittency of solar, wind and wave power.

This expansion of electricity into our lives could lead to the costs per kilowatt dropping. Homeowners who deploy solar panels can often be completely power independent inside of a decade. It effectively freezes the cost of their electricity. As some power companies have fallen into the hands of profiteers, sidestepping them entirely is the best defense.

If electricity is cheap, and electricity powers physical and cognitive work, then it can be more efficient than we were currently seeing. People who generate their own power would have effectively decommodified their heating, recreation and transportation costs.

Medical Costs

Healthcare in Canada is going to Hell. As soon as the Boomers bulged into the years where they needed lots of care, the system really started to rattle. Already, affluent people can use medical tourism to jump the queue on elective procedures. There have been calls to privatize healthcare but this will lead to haves and have-nots. Eventually, taxpayers who are underwriting poorer people will call for further cuts for the sake of their own bottom line. We don’t want that. What we do want is affordable healthcare.

Medical interventions can prove really expensive. They’re also a choke point. They won’t double up in operating rooms or otherwise scale to meet demand. The more they’re relied on, the worse the system will work. Operations are scary: every technique to avoid them is a win. Governments are doing lots to try to get people to age healthy: exercise, dietary choices, and the like are in place to head off health crises as long as possible.

Likewise, medical appointments can add up. It takes too long for patients to see a doctor. That exacerbates some health conditions needlessly and simply put: why do we need to suffer?

Policies need to change. There has been a shift to allow pharmacists to do more in the doctor’s stead. That trend should continue and more people in the healthcare field should get the work that overloads doctors to free them up to see patients.

There needs to be technical improvements in the healthcare system. Too often do doctors claim they can’t get access to test results or the files held by other health practitioners. Wherever a digital system can replace a personal interaction, it should get automated. At the same time, make prodigious logging and reporting available for quality control. When it comes to medical billing, the entire regime needs simplification. Doctors are not accountants and it’s poor use of our tax dollars to make them that.

We need Chat GPT… to a point. Over recent years I have turned to 811. In BC, it’s a healthcare line where people can post questions to a registered nurse or similar healthcare expert. They answered a question fairly quickly; and I didn’t need to go into the emergency ward or book a doctor’s appointment. Keep drawing through this trend line. It simultaneously feels like the best idea and the worst idea to turn to AI with healthcare questions. There has to be a middle ground: an AI that can field questions; it can deliver home based solutions; and it can get their patient to escalate to a professional. If an AI could take the place of some of 811, that would make the system less expensive, maybe less crowded.

We need to put AI into senior care. Visit a nursing home and you’ll see first hand the mismatch of patient needs compared to the labour available. At the same time, private elder care can be eye-wateringly expensive with some places costing $10k – 20k per month per patient.

Use AI pattern recognition to monitor residents to detect those in distress. Similar to police bodycams, patientcams could monitor seniors and routinely delete old footage to keep alive some balance between privacy and accountability. I have a camera perched in my garage. It cost $30. It alerts me if there is motion. It differentiates between the types of motion. Imagine if that basic hardware and connectivity were ramped up with AI image detection– a system to see if someone had fallen and couldn’t get up. It could be anticipatory– detecting when someone is in imminent trouble. Many injuries compound during the wait time to rescue. The Golden Hour rule in first aid is all about getting someone into treatment inside of the hour following the injury. Some injuries are much more complicated to treat if there is a long delay before treatment. Imagine the cost savings of sometimes stopping accidents before they happen, or at least getting an aide worker to them in seconds.

AI and the advances in robotics could help with senior care. The costs of robots are falling. At the same time, their capacity is improving. We may soon see a situation where a $20,000 robot shadows a senior to help them get up, carry their groceries, or catch them before they fall. A 24×7 care worker for a fraction of the cost of the current flesh-and-blood versions. Yes: this does accelerate our race to joblessness by sending care workers home, but it has to happen. Seniors need round-the-clock potential care. They need aid without attitude or sick days. Seniors need a continuity of care that is humanly impossible. After the $20k spend and the maintenance cost of a robot, this could greatly reduce the per-patient costs as we get to an era where senior care is going to explode. If robots shadowing seniors seems like sci-fi, think about how fast we all adopted cellphones– and a cellphone has never helped anyone carry a bag of groceries. Anyone who has a senior friend or relative in extended care knows that these places come up short. There’s too much demand. There’s too much jeopardy. The wage:workload ratio is lousy, leaving disaffected workers caring for infirm people. Technology can play a role with monitoring, the early detection of issues, and the labour needed to manage the residents.

Getting In On The AI Economy

All of the entrepreneurs are trying to turn their side hustle into money to free them from the 9-to-5. Businesses looking to adopt automation need to find a path to automation. They could just bankroll new devices, but more likely than not, they need to finance or defer the costs. It’s not uncommon for businesses to lease their equipment. What if there were automations and AI solutions that could be leased? That would create on-going income for the company that supplies the solution. People could invest in these integrators and collect the dividends.

Making The Jump

How does all this add up? What’s the big plan?

The realities:

• Change is coming. AGI could be in a year, a decade or maybe two. When it comes, it will disrupt our workplaces, our economy and our society.
• We can change fast. COVID showed us we could shift in weeks. If someone tells you otherwise, they’re lying.
• We can’t afford inflation.

Technology can make electricity less expensive and make our lives more affordable. As automation replaces workers, the costs of service and manufacturing will drop; businesses will be more profitable; and hopefully both things will happen. That could make more billionaires, but it could also lead to less expensive products and services. If those billionaires get too greedy, disruptive players could deliver the same services at a deep discount and take their market share.

Policies can be used to make healthcare and housing less expensive. They are our biggest concerns in day-to-day life. Will we be healthy? Will we be able to afford our home? If people are jobless, they won’t have employment income. Tackling affordability will be paramount.

People already tap into non-employment income to live decent lives. A post-jobs future will change things like pensions, but it won’t eradicate that some people already don’t work for a living. The people displaced by automation could live a decent life if we got some of our expensive line items down. They could live off of AI dividends; or profit sharing in employee owned businesses. For the few who don’t have access to a job, a hustle, a dividend or a pension, there would need to be money to provide them a basic income and those dollars need to go further. Technology has already done a lot to skyrocket literacy; improve incomes worldwide; and connect us for good or ill. It can permeate further into our lives to shoulder all manner of labour while we reap the rewards.

I’m not suggesting UBI. For a reason I cannot fathom, universal basic income has a stink on it. When the Swiss voted to adopt UBI, it handily lost. The spectre of UBI is often held up as an example of the threat of woke socialists. Despite the merits of UBI, it may never come about. I argue that we do better than living off of government handouts. Our current world is too expensive and we keep getting less for more. Technology can turn the tide on that trend. We can find new venues to invest in. We can turn to new technology that will accomplish big tasks economically. Those economic wins can make our day-to-day life more affordable.

We can live well, if government changes policies and makes new legislation to usher in a wonderful albeit messy world of artificial intelligence.

Linked Sources & Further Reading

• WEF – Jobs most at risk from AI: https://www.weforum.org/agenda/2023/05/jobs-most-at-risk-from-ai/
• McKinsey – Generative AI and the future of work: https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america
• World Bank – Universal Basic Income debate: https://blogs.worldbank.org/developmenttalk/universal-basic-income-panacea-or-pipe-dream
  
• IMF – Solar now cheapest energy: https://www.imf.org/en/Blogs/Articles/2020/10/13/solar-power-now-cheapest-energy-in-history
  
• OECD – COVID accelerated remote work: https://www.oecd.org/coronavirus/policy-responses/covid-19-and-remote-working-the-new-normal-3b0d2f78/

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