Shahid Hanif is the Chief Technology Officer and cofounder of ShuftiPro, a biometric identity verification (IDV) solution.
Every recent major technological advancement—from analytical computers to the internet—has caused competition among inventors. The key to winning has been gathering enough resources for timely execution before competitors.
The global AI race is no exception. Tech companies are in an investment frenzy, competing to create the most potent augmented intelligence and autonomous systems. Artificial general intelligence (AGI) has yet to be developed, but AI neural networks and reasoning systems are advancing rapidly. Decision support and automation systems are now integrated with general software solutions, changing how we solve digital problems.
But AI has proved so exciting that many people have turned a blind eye to its unchecked growth.
This is concerning. For one thing, the excitement may lead to a bubble, as I spell out below. Handling AI correctly will also be crucial for managing privacy and ethical concerns. Tech leaders and governments should ensure that sound policies are created and that AI technologies are deployed with measures to regulate this technology properly.
A Brief History Of Recent Bubbles
The growth of AI has been significant over the past few years. The global AI market size is nearly $100 billion in 2023 and is expected to reach almost $2 trillion by 2030. However, the bandwagon effect has likely influenced AI growth as investors and companies have invested unprecedented amounts in the sector. To understand this, let’s consider a few similar recent bubbles.
• The 2000s United States Housing Bubble: As more and more people purchased real estate, the prices of houses increased rapidly in the middle of the 2000s. The bubble eventually burst in 2008, kickstarting a global recession.
• The Dot-Com Bubble: Between 1995 and 2000, internet-related companies saw an investment surge. This is an example of an asset bubble, which is similar to the bandwagon effect. When the masses began investing in internet-related startups, these companies eventually ran out of venture capital and did not prove as profitable as expected. A few companies, like Google and Microsoft, thrived after this crash, but many did not survive.
• The NFT Bubble: The NFT market did well during the pandemic, leading to a bandwagon effect where huge brands invested in the sector and NFTs sold for millions of dollars. But, as the hype died down in 2022, the market fell 95% by July 2023 from its peak of $17 billion in January 2022.
Will AI Face A Downturn?
AI may be experiencing a similar phenomenon, with enormous investments from organizations large and small.
In 2018, MIT announced a budget of $1 billion for an AI and computing research college. According to CNN, a French startup, Mistral AI, didn’t have a working product when it raised $118 million in one of Europe’s largest-ever seed rounds. Tech giants such as Microsoft, Amazon, Meta and Nvidia have all jumped into the AI race and are making large investments in creating powerful AI tools.
This may turn out to be an excellent thing for the world, but it has to be noted that investment surges are often unstable. It is also risky to focus too many resources on a single sector, as this can create an asset bubble. A race to make the most powerful AI tool may also result in an influx of half-baked AI tools in the market.
Many now believe that if you have AI related to your company, it will drive the stock prices up. The trajectory of the AI industry is uncertain, but it is necessary to approach it with realistic expectations.
Preserving AI: A Paradigm Shift
We need clarity over AI’s purpose and function to prevent it from appearing on the list of failed tech breakthroughs. For now, we need to get over the notion that AI is a self-sufficient system that will take control of all our affairs. The expectation that we can rely completely on this technology is putting users, investors and AI itself at risk.
As AI continues to evolve, companies investing in AI should, therefore, consider a few factors.
1. Business Models: Businesses need a comprehensive business model for how AI will complement their existing workflows and help improve their processes instead of blindly investing in it. Businesses need to narrow their needs and goals while choosing an AI solution. Moreover, factors like scalability, cost-effectiveness and ethical considerations should also be considered when investing in an AI solution.
2. Patience: Despite its growth, AI is still a young technology, and it will take a lot of time to achieve its full potential. Above all, AI is a technology that needs space to develop so that it can provide us with our desired outcomes.
3. General Awareness: The masses have a considerable awareness gap about AI. Businesses and tech firms in different parts of the world must cooperate to create awareness about AI in their regions. Tech firms’ employees should be educated on AI and how to use it properly. Public seminars and campaigns must also be considered so the public can fully understand the AI revolution.
AI is a global endeavor and needs the cooperation of all countries. Unless governments and federations recognize the AI surge and introduce policies to keep AI’s growth in check, it will likely continue to sprawl.
In short, to ensure that AI is not—and does not become—a bubble, the tech industry should develop empathy for all the involved shareholders and entities to create an ideal AI ecosystem. While healthy competition can lead to great things, those involved in creating AI must ensure they develop it with the public’s and investors’ interests in mind.
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