AI Trap: The Concealed Cost of Artificial Intelligence

Published Date: 24/07/2024

Canada's reliance on artificial intelligence to boost productivity may come at a steep long-term cost, as big tech companies like Microsoft, AWS, and Google set up a dependency trap

Canada's economy is facing significant challenges, and artificial intelligence (AI) is often touted as the silver bullet to address these issues. However, the current business model of generative AI is problematic and may lead to short-term gains but long-term costs. The most common generative AI solutions, like OpenAI's ChatGPT, are presented as free or low-cost to consumers, but they are costly for the proponents, who are making significant investments to train large models and process generative AI solutions.

The 'hyperscalers' - Microsoft, AWS, and Google - own a large share of the AI processing power and are making massive investments to keep up with global demand. These investments are leaps of faith, hoping that if they build the infrastructure, companies will come. For example, Microsoft reported $14 billion in capital investments, up almost 80% year over year, in its last quarterly filing.

The hyperscalers are creating comfortability, and perhaps even dependency, with generative AI solutions. They are incentivizing adoption at scale through discounted initial pricing as well as technical and commercial support in exchange for multiyear commitments. This can lead to a situation where companies become locked into these solutions, making it difficult to switch to alternative providers.

Canada is at risk of falling into such an AI dependency trap in the name of addressing our productivity decline. Our country represents an untapped market for the hyperscalers, given our productivity woes and low AI adoption levels. The government of Canada is doing its part to accelerate adoption and contain costs by increasing the supply of AI processing power, but this may further exacerbate the issue.

Instead of relying solely on generative AI, Canadian leaders should consider a range of innovative solutions, including cloud, automation, data analytics, and process improvements that require little to no technology. Even within the AI spectrum, machine learning has the potential to substantially improve productivity at a fraction of the cost of generative AI.

In conclusion, while AI has a place in Canada, leaders should beware of the AI trap and consider the full range of options to address specific problems, alongside their cost and risk profile.

FAQS:

Q: What is the AI trap?

A: The AI trap refers to the potential long-term costs and dependencies that companies and countries may face if they rely too heavily on big tech companies' artificial intelligence solutions.

Q: What are the hyperscalers in AI?

A: The hyperscalers are big tech companies like Microsoft, AWS, and Google that own a large share of the AI processing power and are making massive investments to keep up with global demand.

Q: What is the cost of generative AI?

A: The cost of generative AI includes the investments required to train large models and process generative AI solutions, such as specialized chips, cloud servers, and secure facilities, as well as substantial energy costs.

Q: What are the risks of relying on generative AI?

A: The risks of relying on generative AI include becoming locked into these solutions, making it difficult to switch to alternative providers, and overlooking other innovative solutions that may be more effective and cost-efficient.

Q: What is the alternative to generative AI?

A: The alternative to generative AI includes other innovative solutions such as cloud, automation, data analytics, and process improvements that require little to no technology, as well as machine learning within the AI spectrum.

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