Biz vs AGI: Can greed align with progress?

Welcome to the year 2034, where flying cars are still a pipe dream, and AGI remains the elusive unicorn of the tech world. Despite the relentless hype and the endless promises that "next year" will be the year of AGI, we're still stuck with glorified chatbots and predictive algorithms. Why? Because the very business models that promised to drive innovation are also what stifles it. So, in more than 10 years of waiting, has structured human greed turned the dream of AGI into a never-ending chase for shadows?

AGI was supposed to be the game-changer, the technology that would revolutionize industries, solve global challenges, and maybe even make your morning coffee. Unlike narrow AI, which excels at specific tasks, AGI was envisioned to understand, learn, and apply knowledge across a wide range of domains, much like a human being. The potential benefits were touted as immense: advancements in healthcare, education, environmental sustainability, maybe even the start for Universal Basic Income (UBI). But here we are, still waiting [4][5].

Unlike narrow AI, which is your daily one-trick pony, AGI aimed to be the jack-of-all-trades. But, spoiler alert, despite multiple goofy attempts, we're not there yet [1]. Current AI systems, including the now surpassed GPT-5, are like toddlers with a smartphone—impressive but not exactly reliable [9]. Despite the enthusiasm, experts from DeepMind already estimated that true AGI was still decades away [2]. But we did not listen.

Human greed, disguised as market optimization, is the art of squeezing every last penny out of all possible customers. Someone call this a business model. This evergreen approach can stifle long-term research because, let's face it, who wants to invest in something that won't pay off until we're all retired or even later? While planning for an AGI future is still crucial, the economic incentives are still as aligned with long-term goals as a cat is with a bath [3]. Does anyone remember IBM Watson, once heralded as a groundbreaking AI for healthcare? No? Well, this shows how short-term profit motives can lead to disappointing results when initial hype isn’t met with sustained investment and realistic expectations [3]. Additionally, as most tech companies prioritize immediate product releases over ethical considerations, we face both the ethical and social issues they failed to foresee, or simply decided to hide [6].

Companies have been pouring money into AI technologies primarily to gain a competitive edge, increase efficiency, and boost their bottom line. The focus on immediate financial returns leads to the prioritization of innovations that offer quick payoffs over those that promise long-term societal benefits. AI applications in targeted advertising, predictive analytics, and automated customer service are heavily funded because they directly contribute to revenue growth. Meanwhile, the grand vision of AGI gets pushed again to the back burner [7][8].

Innovation, that new toy that companies love to flaunt to impress investors, is all about introducing new flashy ideas, methods, or products. But progress? That's a different beast altogether. Progress implies a broader advancement that benefits society as a whole. The past and current business models' landscape, with its emphasis on rapid innovation, must overlook sustainable progress. Companies are more incentivized to invest in AI solutions that enhance their market position, rather than those addressing critical societal issues [7][9]. Examples? Generative AI technologies like chatbots and recommendation systems, which can be quickly commercialized[20], over AGI, which requires more profound and long-term investment [10]. DeepMind’s AlphaGo, for example, achieved remarkable success but was still far from integrating any true AGI [2]. And a marketplace of GPTs meant a great deal of money, with little motivation for OpenAI to pursue AGI for real.

Creating a sustainable business model for AGI means balancing profit with ethics and long-term goals. This involves investing in research that won't make you rich overnight but is essential for AGI [6]. Convincing stakeholders to support such investments is like trying to sell ice to an Eskimo. Sustainable business models should integrate long-term planning and ethical considerations to support innovation. For instance, Google’s AI ethics board was dissolved after just a week, highlighting how even leading companies struggle with balancing ethics and profitability [7]. And we all know what happened with the Alignment team of OpenAI ... Even according to the IMF, ethical guidelines and long-term thinking are crucial for managing the transformative impacts of AGI [5]. This "divide and conquer" mentality not only slows down the collective progress towards AGI but also risks fragmenting the technology into isolated, less effective components [3][6]. In fact, the obsession with short-term profitability means companies are more likely to invest in AI technologies that can be quickly commercialized [11]. Think chatbots and recommendation systems, not the complex, brainy stuff we need for AGI [12]. Another case in point is the emphasis on developing AI for social media analytics over more profound applications that could contribute to AGI [11].

Significant parallels can be drawn with previous technological advancements that were heavily funded by public entities. For instance, the Internet began as the ARPANET, a project funded by the U.S. Defense Advanced Research Projects Agency (DARPA), and GPS was developed by the U.S. Department of Defense to improve military navigation. Both technologies have become foundational to modern society, enabling countless innovations and creating entire new industries. Their commercialization has later led to significant private profits, sometimes overshadowing the broader public benefits. This further underscores the importance of long-term, mission-oriented (public?) investments in achieving breakthroughs that private sector investments might not accomplish [2].

Open source was another hope. The development of AGI requires a collaborative, open, and ethically guided approach. However, the competitive nature of the business world has fosttered secrecy and proprietary advancements. Despite early openness, companies started to reluctantly share their breakthroughs, fearing loss of competitive advantage. In the process, the goal of profit has led to some pretty shady ethical and social issues. Deploying AI without considering its societal impact can result in biases, privacy violations, and other fun stuff [13]. These issues eroded public trust in AI, making it harder to get the societal buy-in needed for AGI. For example, predictive policing algorithms have been criticized for perpetuating racial biases, showing the dangers of deploying AI without thorough ethical consideration [14]. AI models can degrade over time, which is just what we need—AI that gets worse the more we use it [16][18]. The case of OpenAI's GPT models, which have been observed to decline in performance over time, illustrates this issue clearly [18]. Also, like in the famous Google's AI fiasco, chatbots can give false or misleading information, which underscores the limitations of the current approach [15].

To bridge the gap between innovation and progress, there is always been a need for robust regulatory frameworks and ethical guidelines. Governments and international bodies play, supposedly, a proactive role in ensuring that technological development aligns with societal goals. This includes promoting transparency, encouraging data sharing, and setting standards for ethical A(G)I development [8][10]. For example, government initiatives like the National AI Research Institutes in the U.S. aim to support long-term AI research that could contribute to AGI [5]. Planning beyond AGI emphasizes the importance of ethical considerations and long-term thinking [4]. Because, apparently, someone has to be the adult in the room [17]. Additionally, integrating AI advancements with sustainable practices can accelerate the development of useful AGI while ensuring societal benefits [11]. You see, I didn't completely lost hope, yet.

The journey towards AGI is like trying to run a marathon with your shoelaces tied together. While our current business models, driven by structured human greed, have led to some cool AI toys, they may also be holding us back from the real prize [15]. By rethinking these models and prioritizing sustainable, ethical, and long-term investments, we might just get to AGI before our grandkids do [19]. The key is to balance innovation with ethical considerations, ensuring that the development of AGI benefits all of humanity [13].

[1] Youtube - Mark Zuckerberg Is Unironically Based Now
[2] VentureBeat - Here is how far we are to achieving AGI, according to DeepMind
[3] CNET - There's AI, and Then There's AGI: What You Need to Know to Tell the Difference
[4] Google Research - Levels of AGI for Operationalizing Progress on the Path to AGI
[5] IMF - Scenario Planning for an A(G)I Future
[6] Business.com - How to Create a Sustainable Business Model
[7] Journal of Economic Surveys - Artificial Intelligence and Big Data in Sustainable Entrepreneurship
[8] Springer - Sustainable Business Models and Artificial Intelligence: Opportunities and Challenges
[9] OpenAI - Planning for AGI and beyond
[10] Forbes - The Important Difference Between Generative AI And AGI
[11] Phys.org - Q&A: How to make sustainable products faster with artificial intelligence and automation
[12] The Economist - How to define artificial general intelligence
[13] Forbes - Not All Algorithms Are AI (Part 3): General Intelligence
[14] Tech.co - AI Gone Wrong: An Updated List of AI Errors, Mistakes and Failures
[15] Ars Technica - Google’s “AI Overview” can give false, misleading, and dangerous answers
[16] Scientific American - Yes, AI Models Can Get Worse over Time
[17] Scientific American - AI’s Biggest Challenges Are Still Unsolved
[18] WeAreDevelopers - Is ChatGPT Getting Worse Over Time?
[19] Android Authority - Microsoft Copilot vs ChatGPT: Which one is best for you?
[20] The Wall Street Journal - Apple Introduces ‘Apple Intelligence,’ New OpenAI Partnership as AI Takes Center Stage