Will AI put us all on the bread line?

Pessimists think AI will put all of us out of a job, but the best course is to learn how to use it as a cognitive complement to your job

Lots of people are concerned about the impact of AI on jobs. Whether they’re concerned about today’s AI, or a more speculative future artificial general intelligence, many people think that the labor market will be negatively affected by AI. My best answer at present to this question is “I don’t know.” That’s not a satisfactory answer, but it’s an honest one. The optimal solution seems to be: learn how to work with today’s AI technology and pay attention to development in the field.

Unemployed workers wait on the bread line, as an AI oversees them. Image created with DallE-3. I suspect that our future is less dystopian than this.

If you rely on stability and stasis as a kind of security blanket for your career, you’re going to be in for a rough time when it comes to the intersection of AI and jobs. The more you pay attention to developments in AI technology, and the more you use these new technologies, the better the feel you will have for how AI is affecting your job, and how it will affect your job in the coming years.

The way I think about this is that AI will improve over time. Think of AI as evolving its capabilities over the course of a decade or so, and you can start to develop a framework for how it might affect the job market. Let’s break this down¹:

1. Basic Automation (Next 1-2 Years): This stage involves AI systems handling repetitive, rule-based tasks. Jobs with a high degree of routine, such as data entry or basic customer service queries, are most affected. The immediate implication is a reduction in demand for low-skilled labor in these areas.

2. Machine Learning and Intermediate AI (2-5 Years): At this stage, AI systems begin to learn from data, making more complex decisions. Jobs that involve pattern recognition, basic analytical tasks, and more sophisticated customer interactions are impacted. Roles like junior analysts, basic financial advisors, and lower-level managerial positions will see a shift, with an increased emphasis on human-AI collaboration.

3. Advanced AI and Automation (5-10 Years): This phase sees AI handling complex decision-malking, including predictive analytics and strategic planning. Even creative fields like content cretion, design, and strategy could be augmented significantly. High-skill roles, previously considered immune to automation, such as senior analysts, strategists, and creative professionals, will experience a transformation in job content, with AI taking on more significant portions of the workload.

Some Sector-Specific Speculation

Manufacturing and Logistics

• Near Term: Enhanced automation in manufacturing lines and warehousing, reducing demand for manual labor.

• Long Term: Advanced robotics and AI systems managing entire production processes, leading to a shift towards maintenance, oversight, and programming roles.

Finance and Banking

• Near Term: AI-driven analytics and customer service bots will reduce the need for entry-level finance roles and basic customer service.

• Long Term: Sophisticated AI could undertake complex financial modeling, risk assessment, and decision-making processes, requiring a workforce adept in AI collaboration and oversight.

Healthcare

• Near Term: AI in diagnostic assistance and patient management, reducing administrative burdens.

• Long Term: Advanced AI potentially revolutionizing treatment plans, personalized medicine, and surgical procedures, demanding a high level of tech integration in healthcare professions.

Creative Industries

• Near Term: AI-assisted design and content creation tools augmenting human creativity.

• Long Term: AI potentially originating novel creative works, though human creativity and emotional intelligence remain irreplaceable.

How the workforce will change

• Reskilling and Upskilling: There is a critical need to reskill workers displaced by AI and to upskill current employees to work alongside AI.

• New Roles Emergence: As AI takes over certain tasks, new roles that focus on AI management, ethics, and integration will emerge.

• Soft Skills Emphasis: Skills like critical thinking, creativity, and emotional intelligence will become increasingly valuable.

Recommendations for Companies

1. Invest in Employee Training: Proactively develop training programs to manage the transition, focusing on skills that AI cannot replicate.

2. Embrace Human-AI Collaboration: Develop strategies that leverage the strengths of both AI and human workers.

3. Innovate in AI Ethics and Management: As AI becomes more prevalent, roles centered around AI ethics, governance, and management will become crucial.

4. Anticipate Regulatory Changes: Stay abreast of and influence regulatory developments related to AI and employment.

5. Foster a Culture of Adaptability: Cultivate a corproate culture that values continuous learning and adpatability to change.

Other thoughts.

The Financial Times recently published a short article about the impact of AI on white collar jobs. One of its graphs is especially instructive:

Screenshot taken from this article.

Alternatively, the article also notes that generative AI (such as ChatGPT) seems to level the playing field for high-skill white-collar jobs:

The article provides some more detail about these findings:

There was one catch: on a more nuanced task, which involved analyzing quantitative evidence only after a careful reading of qualitative materials, AI-assisted consultants fared worse: GPT missed the subtleties. But two groups of participants bucket that trend. The first—termed “cyborgs” by the authors—intertwined with the AI, constantly molding, checking, and refining its responses, while the second—the “centaurs”—divided labor, handing off more AI-suited subtasks while focusing on their own areas of expertise.

Taken together, the studies tell us three things: First, regulation will be key. Online freelancing is about unregulated a labor market as you will find. Without protections, even knowledge workers are in trouble.

Second, the more multi-faceted the role, the less risk of complete automation. The gig-worker model of performing one task for multiple clients—copywriting or logo design, for example—is especially exposed.

And third, getting the most out of these tools, while avoiding their pitfalls, requires treating them as an extension of ourselves, checking their ouputs as we would our own. They are not separate, infallible assistants to whom we can defer or hand over responsibility.

And that, I think is the key. Your best chance at success given rapidly improving AIs, is to learn how to integrate them into your workflows. It is best to think of AI as a kind of cognitive complement to the work you do. Rather than fear the rise of AI, and assert that it will eliminate your job, it is likely better to learn how to use AI, to become comfortable both with its unpredictability and its improving capabilities. When AI is used as a partner, human workers will benefit.

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1. The timing provided here is a bunch of wild estimates. It may be very inaccurate. Buyer beware, etc.