CUMULATIVE INTELLIGENCE: THE POWER OF PROCESSING ACCUMULATED KNOWLEDGE
The Journey of Humanity’s Progress Has Brought Us to the Edge of Reality. Today, humanity is developing technologies that not only compete in terms of power, speed, and durability but also in “intelligence.”
With artificial intelligence (AI) technology, humanity is facing a groundbreaking reality: machines mimicking human intelligence, learning from human experiences (data), and adapting to new situations.
While the potential outcomes of this transformation dazzle humanity, artificial intelligence has a history almost as long as that of computers.
In 1947, British mathematician Alan Turing, known as the father of AI, used the term “machine that can learn from experience” in a speech at the London Mathematical Society. By 1955, the term “artificial intelligence” appeared for the first time in the proposal letter for the 1956 Dartmouth Conference, which is considered the first AI conference.
Although the idea that every aspect of learning or any characteristic of intelligence could be perfectly defined and simulated by a machine dates back to the 1950s, what distinguishes today is the sheer volume and diversity of data.
In this context, even though artificial intelligence is an established term, it is woefully inadequate in expressing the content and scope of the current paradigm shift. The technology we are facing is not “artificial” intelligence created to counter organic intelligence. Instead, it is a cumulative and collective intelligence that brings together everything humanity has accumulated over the years, allowing us to build on it without needing to repeat what has already been done. AI is either the data and knowledge accumulated by many systems and sensors created by human hands and minds or a model derived from it.
This cumulative and collective intelligence cannot exist and evolve without human effort and experiences. For example, if we examine AI search engines, we will see that the answers they provide result from models built on billions of lines of files, documents, and studies accumulated by humanity.
A similar situation applies to AI models that make sense of the data collected through sensors integrated into different types of civilian and military vehicles, drones, and aircraft. After all, it is humans who determine which data will be collected, how, and for what purpose.
Populist questions such as “Will the human race come to an end in the AI era?” and “Will humanity become slaves to machines?” position AI algorithms as an entity that aims to seize absolute control and is willing to commit any evil to achieve that goal.
Throughout history, including modern history, humanity has faced genocide many times. Unfortunately, in today’s world, certain societal groups are ostracized and exterminated based on ethnic, religious, linguistic, and other cultural differences. Entire societies can be wiped off the map in the pursuit of valuable resources.
Given this reality, I would advise those who see algorithms developed by humans as a threat to confront their prejudices within their societies and themselves rather than targeting technology. After all, what will determine the consequences of AI technology is who writes the algorithms and for what purposes.
The only reason AI technology is subject to populist, speculative, and manipulative debates is not the “killer robot threat.”
AI technology can transform actors with data collection capabilities into new power centers, even challenging national governments. The data collection capabilities of tech giants provide these companies with a power domain that can also be used for intelligence purposes. The self-reinforcing cycle in which tech giants gain more data collection and processing capabilities in the AI era leads to these companies growing uncontrollably. As a result, countries like the US and China, which aim to maintain or achieve hegemonic status, demonize each other’s tech giants. Meanwhile, third parties like the EU attempt to ensure that technology aligns with their values through regulations and seek to limit the power that can be derived from their citizens’ data.
While AI technology offers significant power to the home countries of tech giants, it is clear that this power can also affect the authorities of those countries.
The situation of tech giants being “too big” due to their control over personal data, which shaped the initial debates, could reach a different level with industrial data. This reality can be seen in the words of EU Commissioner Thierry Breton in February 2020: “We realize that we lost the first wave (the AI wave), the first battle, which was the war for personal data… The ‘good news’ is that the EU understands that the next battle will be over industrial data.”
Today, AI has become the foundation of many technologies, thanks to the significant progress it has made in recent years. When analyzing the potential impact areas of AI, almost all sectors of global trade and many different technologies appear on these lists. Health, finance, education, security, agriculture, e-commerce, cybersecurity, and personalized services are just a few examples that can be quickly listed.
Just as yesterday we used terms that seem meaningless today, like computer-assisted education, computer-assisted architecture, and computer-assisted tomography, tomorrow we will not define any field as “AI-assisted.” Just as computer technology has become a horizontal foundation, AI is on the verge of becoming the technological foundation for all forms of productization.
Given this reality, within the next three to five years, using AI technology will no longer be a choice or advantage. Not using AI technology will be tantamount to waiting for death in a vegetative state. Therefore, today AI has become a prerequisite not for competing but for staying in the game.
While standing against any populist debate that seeks to diminish the importance of AI technology, we must not ignore that AI poses risks and threats, such as:
- Becoming a tool of oppression by violating personal privacy,
- Distorting reality through applications like deepfake,
- Creating destructive effects by empowering disinformation operations,
- And reducing efforts to produce organic knowledge.
The prerequisite for mitigating these risks is to become one of the players in the AI market.
First, AI technology may not be the source of another success story for engineers who emerged from their garages to become tech giants. After all, AI requires not only competent expertise but also vast datasets and significant computing power. This requirement is becoming the primary challenge for researchers and entrepreneurs in the AI field and is one of the main reasons why various global initiatives in AI are absorbed by tech giants due to the need for resources.
Today, “shared resources” applications are gaining popularity in various areas, such as vehicles, work environments, and equipment. Instead of designing a new office from scratch and bearing the general overhead costs, companies can rent shared workspaces for specific periods. Or, instead of purchasing expensive equipment that will only be used a few times, companies can acquire it through shared use, paying only for the time it is used.
Reflecting this approach, AI-based ‘as a service’ offerings are making computing power more accessible through cloud computing services. Opening the computing power needed for AI to cloud-based shared use could potentially remove this technological foundation from the exclusive control of elites (tech giants, hegemonic governments, and powerful organizations).
It is worth noting that ensuring that AI data centers, which can only be established through high costs and intensive import activities, operate at full capacity or close to it throughout their operational lives is also a condition for the efficient use of national resources.
The widespread adoption of AI-based ‘as a service’ offerings, with their accessibility, cost-effectiveness, and scalability, is critical for allowing experts from different layers to contribute to technology. While emphasizing this potential outcome, I hope that AI data centers do not share the same fate as laboratories, which can become “showrooms” in the hands of a limited group.
While supporting the use of shared resources, we must also avoid ideas confined to shared spaces. Unfortunately, today, many experts and institutions are focused on continuously repeating the same ideas. Worse still, some expect to achieve the exact same results as the AI activities of tech giants, which have billions of dollars of economic power and decades-old foundations. These out-of-touch approaches should not be allowed to stifle creative ideas.
While data is the fundamental fuel of AI, achieving meaningful results does not always require access to information about what millions of people have liked, where they have been, and what they have searched for over decades. It should not be overlooked that even relatively limited data, gathered or produced for a specific purpose, can be sufficient to bring about many vertical products.
As AI becomes more prominent with its economic and strategic power, as governments offer millions of dollars in incentives to lead, and as existing elites have a significant head start in the race, focusing on populist debates, positioning technology as a sales-marketing element, and misinterpreting trends will have irreversible consequences. It is clear what must not be done to avoid being left out of the game.
As I conclude the second edition of “Staying in the Game” with this article, I would like to inform you that I am working on a new study focused on AI.
With the hope that game-changing new ideas will disrupt the monopolistic balance of the technology ecosystem…
Source: https://www.savunmatr.com/kumulatif-zeka-birikimi-isleyebilmenin-gucu/
