Shaping the AI Economy: A Holistic Approach Beyond Zero-Sum Thinking
There is much commentary that AI is likely to enable fewer people to generate a given amount of economic output and therefore large numbers of people are going to be redundant, leading to a bifurcated, deeply unequal world, where a few do exceptionally well whilst the rest see their skills commoditised and downgraded in value.
Is this right?
I think not, because it overlooks the inherently dynamic nature of economies, particularly in response to transformative technologies. It harks back to the late 19th century lump of labor fallacy which considered there only to be a finite amount of work within an economy that can be distributed to create more or fewer jobs. That proved wrong then, and I hope and suspect it will prove wrong in the future.
How does the dynamic nature of economies play out?
In six ways:
Productivity Gains and Income Redistribution:
Increased Corporate Profits: AI-driven productivity improvements can lead to increased profits for businesses. Ideally, a portion of these profits can be redistributed to workers in the form of higher wages or reinvested into the business to stimulate further growth.
Consumer Spending: Higher incomes for workers can lead to increased consumer spending, which in turn stimulates demand across various sectors of the economy, creating a multiplier effect.
2. Cost Reduction and Price Elasticity:
Lower Production Costs: AI can significantly reduce production costs, leading to lower prices for goods and services.
Increased Demand: Lower prices often lead to increased demand (price elasticity). This increased demand can stimulate the need for more diverse services and products, leading to new job opportunities.
3. Investment in Innovation and R&D:
Reinvestment of Profits: The savings and profits garnered from AI integration can be reinvested into research and development, sparking innovation and the development of new products and industries.
Job Creation in New Sectors: This innovation can lead to the creation of entirely new sectors, which require human capital, thus generating new job opportunities.
4. Shift Toward High-Value Jobs:
Upgrading Skill Sets: As AI takes over routine tasks, there is a shift in the job market towards more complex and high-value tasks that require human input, such as strategic planning, creative problem-solving, and emotional intelligence.
Higher Value-Add per Employee: This shift can increase the value added per employee, leading to overall economic growth.
5. Global Economic Integration:
Opening New Markets: AI can break down barriers to entering global markets, allowing businesses to expand their reach and tap into new customer bases.
Global Supply Chains and Trade: Enhanced global integration can lead to more efficient supply chains and increased trade, boosting global economic activity.
6. Secondary Markets and Induced Industries:
Support and Maintenance of AI Systems: The growth in AI technology creates secondary markets, including the need for maintenance, updates, and support for these systems.
Training and Education: As AI evolves, so does the need for ongoing training and education, which itself becomes a significant sector.
So the causation of higher productivity due to AI leading inexorably to fewer jobs is not real. That does not mean it is not possible. The above IS very likely to occur but it does need to do so alongside a wide range of education and regulatory measures.
For example education systems must foster lifelong learning, teaching not just technical skills but also how to adapt, learn, and grow continuously. Adaptability is the key to thriving in an AI-driven economy, so we need to emphasise soft skills, such as critical thinking, creativity, and emotional intelligence, which become as crucial as imparting technical know-how.
As AI transforms industries, the need for re-skilling and up-skilling becomes paramount. We’ll need tailored educational programs that can help workers transition from declining sectors to emerging fields. And partnerships between educational institutions, governments, and businesses to identify skill gaps and develop targeted training programs.
And in terms of regulatory measures we’ll need comprehensive policies to support workers displaced by AI. These must include not just unemployment benefits but also access to retraining programs and job placement services. And these measures have to be proactive, anticipating changes in the labor market rather than reacting to them.
Proactive fiscal and regulatory policies can help in redistributing the gains from AI, ensuring that the benefits are widely shared across the economy. Government investment in public goods, infrastructure, and education can further stimulate economic growth.
Fostering innovation and sector development can be catalysed by governments that play a proactive role in nurturing new technology sectors through incentives, research funding, and infrastructure support. The approach has to encourage economic diversification, without which creating new job opportunities and industries will be difficult.
Entrepreneurship and Small Business Support is an imperative. We have to encourage entrepreneurship, especially in AI-enabled sectors that can drive job creation. Support can come in the form of tax incentives, grants, and access to resources. Small businesses are often more agile than larger ones and more likely to be incubators for innovative uses of AI.
Globally we need to work hard at generating collaboration and setting universal standards. AI’s impact transcends borders so international collaboration on standards, ethical guidelines, and best practices are required to create a more cohesive and responsible global approach to AI integration.
And finally regarding the role of governments we need to vastly increase public awareness and involvement in reshaping economies. Educating the public about AI’s potential and challenges is vital to ensure (hopefully) a well-informed citizenry. Public involvement in discussions around AI ‘should’ help in democratising its development and application.
And then of course we also need to think about the actions and behaviour of company management. The labour economist David Autor has written that "AI Could Help Rebuild Middle-Class Jobs” but “the key question to ask is for whom is AI a substitute and for whom is it a complement” and “We Have a Real Design Choice About How We Deploy AI”.
How companies behave, and how we as societies let them behave, is a critical factor in determining all of our futures.
All of them above has to be taken seriously. Our future is not pre-wired. We do have a lot of agency, and how AI integrates or dominates our lives is still largely up to us.
All of which is very tricky for the real estate industry. Just how many jobs are there going to be, what will people be doing, and where and what real estate are they going to need? Every answer depends on how much of the above occurs. And how.
If you see our futures determined by an AI mediated world that will inevitably lead to a society where, to quote Thucydides ‘The strong do what they can and the weak suffer what they must.’ then the amount of change will be immense, and any project you start today will very much have to pander to the ‘Strong’. The ‘weak’ will have to take what they are given.
Which feels very dystopian to me, even as I am aware many people, especially the more libertarian Silicon Valley types, see this absolutely as where we are going.
I see two other options. First, we do follow the guidance above and build a much bigger pie, with a piece for everyone. Or we either don’t try this, or it turns out that AI is going to take most of the pie regardless of its size, in which case we need to be thinking of a much more distributive, egalitarian, society where the few do not get to keep their massive gains, but they are spread far and wide.
Either way, the only guarantee is that big things are afoot, the next decade is going to be transformational, and that we really must hope for large doses of wise leadership across the globe.
And that last sentence worries the hell out of me!