The question of whether machines will become more intelligent than humans is a common one, with the definition of intelligence being key to the comparison. Computers have several advantages over humans, such as better memories, faster data gathering, continuous work without sleep, no mathematical errors, and better multitasking and planning capabilities. However, most AI systems are specialized for very specific applications, while humans can use imagination and intuition when approaching new tasks in new situations. Intelligence can also be defined in other ways, such as the possession of a group of traits, including the ability to reason, represent knowledge, plan, learn, and communicate. Many AI systems possess some of these traits, but no system has yet acquired them all.
Scholars have designed tests to determine if an AI system has human-level intelligence, such as the Turing Test. The term "singularity" is sometimes used to describe a situation in which an AI system develops agency and grows beyond human ability to control it. So far, experts continue to debate when—and whether—this is likely to occur. Some AI systems can pass this test successfully but only over short periods of time. As AI systems grow more sophisticated, they may become better at translating capabilities to different situations the way humans can, resulting in the creation of "artificial general intelligence" or "true artificial intelligence."
The history of artificial intelligence dates back to several milestones that highlight the advancement of artificial intelligence relative to human intelligence. These include the first autonomous robots developed by William G. Walter (1948-49) and the development of the Turing Test by Alan Turing (1950), which unearthed the thinking capabilities of machines. In 1951, Marvin Minsky and Dean Edmonds developed the first artificial neural network which gave birth to artificial intelligence. Artificial neural networks were first applied in Machine Learning by Arthur Samuel in 1959 and the first natural language processing program, ELIZA was developed. Artificial intelligence has since been applied in robotics, gaming, and classification.
The first AI robot, Shakey, developed in 1966, became the first intelligent robot to perceive its environment, plan routes, recover from errors, and communicate in simple English. A further advancement of AI was achieved in 1969 when an optimized backpropagation algorithm was developed by Arthur Bryson and Yu-Chi Ho, which enabled AI systems to improve on their own using their past errors. The introduction of the internet in 1991 enabled online data sharing which had a significant impact on the advancement of AI. Large companies such as IBM and Caltech subsequently developed AI controlled databases that includes millions of labeled images available for computer vision research. The publication of the AlexNet architecture is considered one of the most influential papers in computer vision.
In 2016, AI system AlphaGo, created by Google subsidiary DeepMind, defeated Go champion Lee Se-dol four matches to one. In 2018, Joy Buolamwini and Timnit Gebru published the influential report, “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,” demonstrating that machine-learning algorithms were prone to discrimination based on classifications such as gender and race. In 2018, Waymo’s self-driving taxi service was offered in Phoenix, Arizona. In 2020, Artificial intelligence research laboratory OpenAI announced the development of Generative Pre-Trained Transformer 3 (GPT-3), a language model capable of producing text with human-like fluency.
Dear Job Omweno ,
In a nutshell, the debate on whether machines can surpass human intelligence revolves around the concept of artificial general intelligence (AGI) versus artificial narrow intelligence (ANI). Currently, machines exhibit ANI, excelling in specific tasks like data analysis, pattern recognition, and even complex strategic games, outperforming humans in speed, accuracy, and consistency. These systems leverage vast datasets and sophisticated algorithms, such as deep learning and neural networks, enabling them to process information at scales and speeds unattainable by human cognition. However, AGI, which embodies the ability to understand, learn, and apply knowledge across a wide range of tasks, remains an aspirational goal. Achieving AGI would require machines to exhibit qualities such as self-awareness, emotional intelligence, and the ability to generalize learning from one domain to another, akin to human cognitive flexibility.
The potential for machines to surpass human intelligence also hinges on advancements in computational power, data availability, and the development of new algorithms that can mimic the intricate workings of the human brain, which may not be realized forever. Quantum computing, for instance, promises exponential leaps in processing capabilities, potentially enabling breakthroughs in AGI. Additionally, interdisciplinary approaches combining insights from neuroscience, cognitive science, and computer science are crucial for creating models that can emulate human thought processes. However, even with these advancements, the subjective nature of human experience, creativity, and ethical reasoning presents significant challenges. While machines may become extraordinarily proficient at tasks traditionally requiring human intelligence, the holistic and nuanced nature of human cognition may always set a distinct boundary that machines cannot fully transcend.
Some papers about this question in different domains are linked for your response:
https://www.taylorfrancis.com/chapters/edit/10.1201/9781032648309-9/artificial-intelligence-machine-learning-cyber-ethics-future-world-wasswa-shafik
https://books.google.com/books?hl=en&lr=&id=wgkFEQAAQBAJ&oi=fnd&pg=PA33&dq=wasswa+shafik+artificial+intelligence&ots=nPdjWy3-bO&sig=bznclea_0feJAkHdqrK2X-FYyxU
https://www.igi-global.com/chapter/explainable-ai-exai-for-smart-healthcare-automation/346811
https://www.igi-global.com/chapter/artificial-intelligence-models-to-prevent-forest-fires/346719
https://www.igi-global.com/chapter/role-of-artificial-intelligence-in-the-agile-project-management/348485
I stand to be corrected,
Shafik
Dear Job Omweno ,
General Intelligence : Current AI systems, including the most advanced ones, exhibit narrow or specialized intelligence. They excel in specific tasks but lack the broad and flexible cognitive abilities of humans. Achieving general intelligence that matches or surpasses human capabilities is a significant challenge.
Whether or not artificial intelligence (AI) will be able to outperform human intelligence—and how soon that could happen—is a common question fueled by depictions of AI in popular culture. Key to this comparison is a clear understanding of "intelligence."
https://scienceexchange.caltech.edu/topics/artificial-intelligence-research/machines-more-intelligent-than-humans
Regards,
Shafagat
Job Omweno,
Let us narrow this conversation down to a narrow field of intelligence as evaluation criteria, such as the ability to do science.
Assume that AI can:
Even if it meets the criteria of 1-3, it still needs to do science and the limitation of time is a factor (it cannot speed up a chemical reaction at a certain temperature and with a specified catalyst). This puts a hard limit on how far ahead an AI can go above us. It cannot be what it is impossible to be. Also, while it can process data fast, deriving a new theory does not depend on speed. It depends on insight and even luck. Now let us define insight as the particular proficiency with the ideas, theories and concepts behind the subject of study(note that this influences "luck"). This would mean that 2-3 need to be mastered.
Assume that it covers all of the above, the physical activities are still time bound and do not guarantee that AI can be superior in processing scientific "knowledge". While this thought experiment does not preclude the possibility of AI becoming more intelligent, the points above are all based on assumptions that need to be fulfilled and they are a lot. It is also worth considering whether the assumption of those points being met are even possible with our current research practices. I do believe that none of the above assumptions are impossible in principle. But, in practice we are not going to fulfill them because the incentive to change our current AI development practices are not there.
As a final note, this reasoning applies to so called "superintelligence" which is in my opinion a myth that many people believe.
It may take some time for AI to reach human-level intelligence. Human intellect enables us to reason, solve issues, and come to conclusions. Numerous cognitive skills are needed, such as flexibility, social intelligence, and experience-based learning.
AI already answers a lot of these questions. All that's needed is for AI models to pick up innate human abilities like critical thinking and the ability to distinguish between different emotions and the situations that could trigger them.
These characteristics are ingrained in us from the moment we are born as humans. Our earliest memories of "happiness" are from too early a time. Throughout childhood, we also pick up critical thinking and emotional control, and we become aware of our "emotions" through our interactions with and experiences in the outside world. Significantly, the development of such intelligence in the human brain can take many years.
AI hasn’t acquired these capabilities yet. However, AI can most likely learn these characteristics just as quickly as humans can, if not more so. To build such qualities in AI models, we are still learning how to construct, train, and interact with them. The real concerns are not if AI will become as intelligent as humans, but rather when and how.
The topic of whether machines will eventually surpass human intelligence is both fascinating and provocative, inviting a multifaceted discussion. Intelligence, in this context, is a complex and often subjective concept. As noted, computers have numerous advantages including superior memory capacity, speed, error-free calculations, and continuous operation. However, human intelligence remains unparalleled in its generality — our ability to adapt, use imagination, and employ intuition to tackle novel and unforeseen problems.
AI systems are predominantly specialized, excelling in specific tasks such as playing chess or diagnosing diseases. This specialization contrasts sharply with the human capacity for general intelligence. While certain AI systems might possess traits linked to intelligence like reasoning, learning, and communication, no system to date encompasses all these attributes simultaneously.
The Turing Test, conceptualized by Alan Turing, is often cited in discussions of machine intelligence. It evaluates a machine's ability to exhibit intelligent behavior indistinguishable from that of a human. Some AI systems have passed this test in limited and controlled scenarios, but true artificial general intelligence (AGI) remains elusive. AGI denotes a machine's ability to understand, learn, and apply knowledge across a wide array of tasks, akin to human cognitive capabilities.
The notion of the "singularity," where AI surpasses human control and understanding, is a contentious topic among experts. Predictions about its arrival vary widely, and while some view it as imminent, others remain skeptical. This unpredictability stems from the incremental yet profound progress in AI, marked by milestones where machines perform tasks previously thought exclusive to human ingenuity.
The historical trajectory of AI illustrates its gradual ascent. Starting from the early development of autonomous robots by William G. Walter in the late 1940s, to the conceptualization of neural networks and the creation of pioneering AI systems like Shakey in the 1960s. These milestones reflect the field's growth and the increasing sophistication of AI technologies.
Recent advancements further underscore AI's progress. Google DeepMind's AlphaGo defeating Go champion Lee Se-dol, Waymo deploying self-driving taxis, and OpenAI's release of GPT-3 showcase AI's impressive capabilities. Yet, these examples also highlight the ongoing challenges and ethical considerations, such as the biases identified in machine-learning algorithms by researchers like Joy Buolamwini and Timnit Gebru.
In summarizing the future landscape of AI and human intelligence, it is critical to balance optimism with caution. AI's potential to enhance human life is immense, but so are the ethical and societal implications. Continuous dialogue and rigorous research are essential to navigate this evolving field, ensuring that advancements in AI contribute positively and equitably to society. The journey toward AGI and beyond will undoubtedly reshape our understanding of intelligence, challenging us to redefine our expectations and ethical frameworks around this transformative technology. Reasoning and learning are key, can an AI demonstrate by itself Fermat's Theory? can demonstrate Unified field Theory or can it reject it? There is no discussion if it can learn all the books in the world, but how will treat contradictory knowledge, like different religions books.
Despite that the question lacks from a solid meaning, an AI can play better chess than any human, work more hours than any human, keep working practically for eternity, drive better than any human, talk all 26 languages, understand more languages than almost any human, if a computer can work more and better than you (because for some people will be that case) , can work more than you, play chess and Go better than you, can you say it is not more intelligent than you? How can you say is not better than you, more intelligent than you if in almost all the activities that matters in a society a machine is better than you? Is that the real question? Is it even a question? I think the problem is the question, not the answer, you cannot have a meaningful answer without a meaningful question.
Definitely. Because human brain has its own limitations. And all brains are not equal. Machines on the other hand, can overcome this limitations.
they definitely can. to personally verify this, it is enough to click on the TV remote control for 5 minutes
Hello everyone,
While AI has the potential to match human intelligence in various ways, the true extent of its capabilities will largely depend on advancements in quantum computing. Human intelligence encompasses not only factual knowledge but also creativity, emotional understanding, and intuition—qualities that current AI models can mimic but not fully replicate. While computers excel at memory and data processing, humans uniquely apply imagination and intuition to novel situations. The concept of ‘artificial general intelligence’ aims to create machines that surpass human abilities, but achieving this remains an ongoing challenge.
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