Is Artificial Intelligence Just a Fad?
Analyzing the future of artificial intelligence, from AI Spring and AI Winter to Generative AI and Machine Learning.
Photo Source: Medium
Let me set the scene: It’s the spring of 2022, and I’m sitting in my course on artificial intelligence, learning about embodied agents, acyclic graphs and supervised learning. This course is required for cognitive science majors to graduate, and while it was interesting, I didn’t really view the information as too relevant to my daily life. Little did I know that six months from then I would be witnessing the unveiling of an AI product unlike anything I had ever seen before.
In November of 2022, OpenAI took the world by storm with its release of ChatGPT, and the hype that ensued was comparable to that of Taylor Swift’s Eras Tour. According to the International Data Corporation, global spending on AI will reach $154 billion in 2023, an increase of 26.9 percent from 2022. The rapid evolution of generative AI is clearly backed by substantial funding, but does this current excitement reflect the true magnitude of generative AI’s potential, or is this just another passing fad?
One concept I distinctly remember discussing in that course was the contrast between AI Springs and AI Winters. The spring season is warm and blooming, which is exactly how the AI prospects look during an AI Spring – investment money is flowing, tech companies are making overconfident promises, and the media is perpetuating hype around a new product.
However, just as the seasons change, so do AI expectations. An AI winter is cold and bleak, with the technology falling short of the public’s inflated expectations, the money flow slowing to a trickle, and the media switching to excessive criticism of the technology’s shortcomings.
Photo Source: “The winter, the summer, and the summer dream of artificial intelligence in law,” by Enrico Francesconi
We’re currently living through an AI summer that began in the 2010s with the development of deep learning. But have we reached the point in the cycle where the technology starts to under-deliver?
McKinsey claims that generative AI might reach the median level of human performance in a multitude of domains by the end of this decade, but seeing as major companies like Microsoft and McKinsey are the ones that will prosper from the adoption of this technology, their proud statements must be taken with a grain of salt.
McKinsey’s assertion about generative AI reaching a human level of intelligence has some serious implications. The fear of AI replacing human jobs is a widespread one, as it can work tirelessly and efficiently, and doesn’t require paid time off.
Before we all freak out about losing our beloved jobs, let’s remember that this is the same AI that sometimes struggles with basic algebra. What we’re looking at is probably more of a shift in job responsibilities than an outright replacement.
While technology might be able to completely automate some physical work, it doesn’t seem to be a comprehensive solution for all knowledge-based work. Generative AI can take on a lot of grunt work, leaving human intelligence free to focus on more complex and fulfilling tasks, but that human oversight and finishing touch still seems to be essential. Of course, some industries will find more use cases than others, specifically marketing, sales, high tech and banking, due to generative AI’s proficiency in tasks like copywriting and software development.
AI is also already more integrated into our lives than we may realize, as prominent companies such as Snap Inc. and Meta have already implemented AI features on their platforms. And unlike the metaverse, which struggled to find a practical purpose, people are using generative AI platforms like ChatGPT in their daily life for tasks such as writing cover letters and summarizing documents.
Ivan Porollo, co-founder of the Cerebral Valley newsletter and AI community, boldly proclaimed to Vox, “I’m very bullish on this whole AI wave because it feels like it’s at the level of the app store being released. It just feels different. It feels like a generation of technology that’s going to affect our future for the remainder of our lives.”
Of course, every new technology comes with its pitfalls. Generative AI platforms, including Microsoft’s Bing, have garnered a lot of attention for producing inaccurate information, revealing cybersecurity vulnerabilities and inadvertently engaging in intellectual property infringement. It seems that AI is not ready to operate on its own just yet, and people and companies still need to be extra careful how they use these technologies.
So, will the consensus be that while yes, having generative AI write you a poem about spaghetti is fun, it can’t be relied on for any work with real consequences? In that case, an AI Winter is looming, since the principles of capitalism demand a return on investment that can’t be reached without real application of these technologies. On the other hand, perhaps generative AI will become so entangled with our daily activities that it becomes a fundamental part of society. An eternal AI Spring!
According to Matt Asay, a contributor at InfoWorld, a third option exists where the frenzy around generative AI subsides, but funding for machine learning continues. Generative AI is a subset of deep learning, which itself is a subset of machine learning, and while generative AI is the current face of AI as a whole, machine learning is the basis for all of these advancements. If the hype around generative AI can convince investors that machine learning is the future, then there may only be a publicly perceived AI Winter, while startups continue making progress behind the scenes.
Is history bound to repeat itself, or is this time different? We here at Don’t Count Us Out Yet can’t see the future, but we can (and will) provide you with the context needed to make your own informed predictions!
Best,
Nina for the Don’t Count Us Out Yet Team