In 2024, artificial intelligence (AI) is no longer a figment of our imagination but a tangible reality, revolutionizing everything from daily interactions to image-creation.

But what’s the real cost of this technological paradise? Hidden beneath AI’s glossy exterior are hidden costs, including environmental impacts and economic hurdles we might not be fully prepared for.

Step into the lesser-known side of AI’s journey, where its groundbreaking achievements come with significant, often overlooked challenges. Unravel the complexities of AI’s impact on our world, exploring the delicate balance between advancing technology and preserving our ethical and environmental integrity.

AI’s Hidden Costs: Environmental Risks

The rise of AI has brought about significant technological breakthroughs, from chatbots that can engage in human-like conversations to algorithms that create lifelike images.

However, these advancements come at an environmental cost that’s often ignored: the high water use by data centers of major tech companies such as Microsoft, Google, and Meta. These centers are essential for the operation of AI, requiring massive amounts of water to cool down the servers.

In 2022, there was a notable increase in water usage by these companies, with Microsoft’s water consumption going up by 34%, Google’s by 22%, and Meta’s by 3%, all in the name of enhancing their AI technologies. This is only the beginning as AI is just starting to bloom.

Researchers at the University of California, Riverside, predict that AI will drive water use to astounding levels in just a few years. They expect it to use between 4.2 and 6.6 billion cubic meters (equal to 1.1-1.7 trillion gallons) of water every single year by 2027.

This growing need for water highlights an often unseen environmental impact of AI and brings attention to the pressing issue of global water scarcity. The tech industry’s expanding water footprint is concerning, especially considering the world’s current challenges with droughts and outdated water systems.

In response, some tech companies have started to address their impact on the environment by investing in projects aimed at restoring water, improving water management systems, and finding more water-efficient cooling methods for their AI operations.

These actions are just the first steps. As AI technology keeps advancing, it’s important for the industry to find a balance between innovation and caring for the environment. This way, AI development can push the limits of intelligence while also supporting sustainability, helping to safeguard our water resources for the future.

Economic Realities Behind AI: Is The AI Craze Sustainable?

As we explore the environmental challenges presented by AI, we encounter another equally intricate aspect: the economic implications of investing in AI. This perspective transitions our discussion from environmental to financial sustainability, highlighting the diverse hurdles encountered in AI’s advancement.

It’s simple to admire the amazing technology behind tools like OpenAI’s impressive ChatGPT or its new video-generating model Sora, but that doesn’t guarantee it will be profitable for everyone. It’s being tried out in thousands of scenarios with billions of dollars on the line, but no one can predict how it will do in any of them over time.

Some companies are already finding that the tech isn’t profitable in many use cases.

Microsoft’s initial ventures into generative AI, despite the hype, encountered financial difficulties, with some offerings falling short of goals due to the hefty costs of operating sophisticated AI models. Google has also been testing different pricing models for its AI-powered software, aiming to find a sweet spot that covers costs without deterring users.

Adobe has taken a careful approach to avoid the financial pitfalls of AI, setting usage limits and adopting a pay-as-you-go pricing strategy to manage rising expenses. These strategies underline a common problem across the tech sector: how to profit from AI while keeping it affordable and satisfying for users.

Customer responses to the changing AI scene are varied, with some unhappy about the high costs of using AI solutions. This discontent points to a critical issue at the heart of the AI boom: although AI has the potential to revolutionize various sectors, finding an economic model that works is still in progress.

The Reality of AI’s Practical Applications

Moving past the environmental and economic obstacles, we delve into the crucial aspect of AI’s real-world applications. This section uncovers the discrepancy between what AI promises and what it actually delivers, adding complexity to the idea of AI as a universal solution to contemporary issues.

Gemini, which was created to produce realistic images based on text descriptions, received significant criticism for outputting images with strange racial and gender biases, such as inaccurately depicting historically homogenous groups as racially diverse. It also refused to compare historical figures when asked which negatively impacted society the most. For example, writer Nate Silver confirmed that it refused to say whether Adolf Hitler was worse than “Elon [Musk] tweeting memes.”

 

These incidents underscore a larger problem in the tech industry: the rush to leverage AI’s potential often ignores the need for a comprehensive understanding essential for addressing its effects on society responsibly. The issues with Gemini not only show the technical and ethical hurdles in AI but also indicate a tendency to prioritize technological advancement over the actual usefulness and social obligations of these products.

As AI progresses, it is crucial for those involved in its creation and application to thoroughly evaluate its real-world applications against the possible consequences. The experiences gained from cases like Gemini highlight the importance of adopting a more cautious approach to AI development, one that equally values innovation, ethical considerations, and the importance of being both accurate and inclusive in what AI represents.

The Bottom Line

As we move closer to a future shaped by AI, it’s becoming clear that our path is filled with complex challenges that reflect the sophistication of AI itself.

The hidden costs of AI on the environment, seen in its high water use and carbon emissions, pose a serious threat to our planet’s health.

Economically, finding a balance between making AI profitable and keeping it accessible illustrates the fine line between innovation and feasibility.

Additionally, putting AI into practice brings up ethical issues, from biases in algorithms to the gap between what AI promises and what it actually achieves.

Looking ahead at the future of AI involves more than just technological progress; it requires a well-thought-out plan that combines innovation with caring for the environment and ethical integrity. Taking this comprehensive approach is essential to make sure AI’s development contributes to sustainable growth and stays in harmony with the wider values of our society.