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If you haven’t already received an earful about ChatGPT, LLMs, and how generative AI is going to make you obsolete, then count yourself lucky.

But don’t be too complacent – the impact on the future of work may be more subtle than the wholesale destruction of jobs as currently envisaged, but it will nonetheless be sweeping. A bit like a slow-motion, trans-generational shift and replacement of familiar roles and jobs across all value chains.

We’ve been using generative AI for close to a year now, and while it is far more capable than we initially wanted to believe, it is not a magic bullet that will solve all our problems. We do however believe that they will become general-purpose technologies.

In their 2005 book, Economic Transformations: General Purpose Technologies and Long-Term Economic Growth, Richard Lipsey, Kenneth Carlaw and Clifford Bekar, give us some criteria with which to evaluate this possibility.

The criteria can be considered as three simple questions: Does the technology improve over time? Is the technology pervasive throughout the economy? Can the technology spawn complementary innovations? The very first link in this article will take you to a paper that answers these questions in detail.

You can also skip to the bottom of this article for a link to a short video worth watching.

ChatGPT and other generative AI tools have the potential to create a new ‘level playing ground’ that could see some jobs engineered out of formal, dedicated existence because they will be absorbed into the realm of ‘basic skill’.

At the same time, these tools can also increase efficiency and productivity and create new job opportunities. We must consider both sides of the coin.

For example, in Nigeria and across Africa, generative AI tools can be used to support service delivery and good governance. AI tools can help governments engage with the public quickly, relatively accurately, and at scale, making them more responsive.

In the legal industry, these tools can assist lawyers in conducting legal research and drafting legal documents, freeing up their time for more high-level work such as advising clients.

In the healthcare industry, generative AI can be used to analyze medical data and assist with the diagnosis and treatment of patients. In these cases, generative AI is not replacing jobs but rather enhancing them.

However, we must also be aware of the potential downsides of relying too heavily on generative AI. The risk of bias is a major concern, and ongoing human oversight and input is necessary. We must also consider the potential ethical implications of using generative AI and the need for responsible AI practices and policies.

The impact of generative AI on the future of work is not limited to specific industries or job roles. It will be felt across all sectors and professions. As skills move through society, some roles will become obsolete, while others will be transformed.

Typists are a good example of a role that has been absorbed into the realm of basic skills. As we move forward, other roles will follow suit.

We must be mindful of the potential nuances and complexities of the topic and avoid making sweeping generalizations about the future of work. The impact of generative AI on the future of work is not predetermined, and it is up to us to shape it in a way that benefits everyone.

This requires a collaborative effort between industry, government, and society. So, while the human element is still essential, we must also harness the power of generative AI. The future of work is in our hands, and it is up to us to make it a bright, inclusive and safe one.

If you would like to watch a video about all the AI announcements we can expect to hear over the next six months watch this video featuring Nvidia’s CEO, Jensen Huang, who goes all in, calling for the establishment of a TSCM for AI.


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