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Can AI Teach Itself?
Great topic started by Bailey. Can Artificial Intelligence teach itself? Look at this clip and what Elon Musk said.
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5 Replies
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Artificial Intelligence is a computer. So a computer can think for itself?
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I don’t think because all are programmed by human. so they can do only those which was inserted on them
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While AI systems exhibit some form of self-learning, they don’t possess consciousness, awareness, or independent thought. They learn and improve their performance based on the data provided by the researchers or engineers designing and developing them.
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The inquiry into whether artificial intelligence can become dangerous and whether it is self-teachable to an extent has been a key element in debates concerning AI’s future potential and ethical repercussions. This has been a concern for many, including tech entrepreneurs such as Elon Musk, researchers, and ethical theorists. Here is a summary of the most important aspects of this conversation:
Is There a Possibility of AI Being Hazardous?
AI can be dangerous if adequate measures aren’t taken towards its design, development, implementation, and governance. Below are some reasons why AI might be a risk.
Insufficient Human Control
AI systems are capable of excessive self-governance, which, without appropriate precautions, can lead to fatal outcomes.
Example: An AI weapon system could inflict unintended casualties due to misinterpreting set objectives.
Poorly Defined Goals:
If the objectives are inadequately outlined, AI can chase goals that contradict human interests.
Elon Musk has, on multiple occasions, cautioned that AI can potentially be more lethal than nuclear arms if not properly controlled. In one of his interviews, he quoted:
“For example, the concern is not that AI will develop a will of its own. The issue is that it will follow the will of whoever controls it.”
Exploitation by Humans:
Malicious parties can abuse AI’s potential for hacking, monitoring, or launching disinformation campaigns.
Economic and Social Disruption:
AI has the potential to achieve an extremely high rate of job automation, which can produce massive unemployment if sufficient measures aren’t taken to deal with structural economic changes.
Runaway AI (The Singularity):
Very powerful AI systems that can self-optimize (commonly referred to as AGI) could, in theory, reach a point where humans as a species are irrelevant to their existence. This is called the technological singularity.
Can AI Teach Itself?
Yes, AI has the potential to “teach itself” to a certain degree, which refers to unsupervised learning or self-supervised learning. Here’s how it works:
Machine Learning Basics:
Standard AI technologies are built with human-created datasets (supervised learning) or data with no specific instructions (unsupervised learning), often called artificial stupidity. These systems do not entirely “teach themselves” one hundred percent. Rather, they still rely on humans to code and enter data.
Reinforcement Learning
DeepMind’s AI systems, like AlphaGo, utilize reinforcement learning by teaching themselves by playing millions of games. Over time, they get better at formulating strategies and refining their approaches. The AI learns through trial and error without the assistance of a teacher.
Generative Adversarial Networks (GANs)
Two neural networks compete against each other in a Generative Adversarial Network (or GAN). After some time, the networks learn to produce realistic outputs, like deepfakes or authentic images.
Self-Improving Systems:
It is becoming more common for AI systems to alter their algorithms. For instance:
– AutoML: Automated machine learning is a subspecialty of AI that improves its models without assistance.
– OpenAI’s GPT models are made to process huge volumes of text and provide human-like responses using patterns found in the dataset.
Emergent Behavior:
Certain complex AI systems can exhibit behaviors different from what the programmers intended, known as ’emergent behavior.’ An example is how GPT-4 can perform reasoning tasks despite not being built to do so.
Elon Musk’s Warning on Self-Learning AI
Elon Musk has constantly warned against AI systems that can theoretically self-teach, as they can control themselves.
To make sure AI creation stays ethical and helpful for humanity, Musk set up OpenAI.
He refers to the processes that allow AI to learn independently as constructing a ‘demon’ that may be beyond our control.
He has also maintained that everything must be strictly controlled and monitored, stating,” We are swiftly moving towards a stage of digital superintelligence that exceeds human capabilities. A self-learning AI, given its ability to advance on its own, will definitely breach the limits of human control and supervision.”
Self-Teaching AI Examples
AlphaZero (DeepMind):
- AlphaZero, a chess AI, started without prior knowledge but taught itself by playing millions of games.
- Within hours, it beat the strongest human-trained chess engines.
DALL·E and MidJourney
DALL·E and MidJourney, image-generating AIs, learn to combine texts and visuals to create images.
OpenAI’s Codex
Codex, the heart of GitHub Copilot, was trained in open-source code and taught himself programming languages to create functional software projects from text.
What Remains to be Done?
Promotion of Responsible AI Use:
AI systems should be ethically aligned with human norms, so companies and states must design systems like that.
Open-Ended Approaches
Developers must be open about how AI systems function and the data they access to reduce the chances of unforeseen outcomes.
Regulation
Musk and other specialists suggest a global governance system to mitigate the possible peril AI can cause.
Kill Switches and Fail-Safes:
Set controls must be incorporated in AI to turn it off should it go out of control.
Collaboration:
OpenAI, Google DeepMind, and similar companies must join forces to ensure AI advancement serves all people rather than just a small group.
Gary McGraw has pointed out that the ability of AI systems to learn by themselves can be a double-edged sword. It enables fantastic progress in science, medicine, transport, communication, and other important fields but poses serious ethical and safety issues. Pioneers like Elon Musk have also called for attention, rules, and strategies to curb its growth and prevent uncontrollable outcomes. Ultimately, the fate of AI hinges on how carefully we plan for its design and implementation.
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Elon Musk has shared opinions on artificial intelligence, including that AI systems can learn and improve with time. Here are a few important points concerning his views and the wider conversation on whether AI can’self-learn’:
Self-Learning Capabilities
Many AI systems, especially those that work with machine learning and deep learning, can improve their performance with the data they receive. Many people refer to this as ‘self-learning’ or ‘unsupervised learning.’
Reinforcement Learning
AI agents learn by interacting with their environment in a process known as reinforcement learning. These agents can receive both rewards and penalties. This form of learning enables them to establish strategies over time without being explicitly programmed for every task.
Worries Regarding Autonomous Learning
Musk has openly expressed concerns about self-learning AI systems and their potential risks. He has warned that regulation and AI supervision are necessary to prevent the development of systems that could be dangerous for humanity.
Ethical Implications
The concept of AI teaching itself presents ethical dilemmas concerning accountability, transparency, and possible unforeseen ramifications.
Existing Constraints
Despite AI’s capacity to learn from parameters, it does not “teach itself” as humans do. There is no self-awareness, comprehension, or reasoning beyond the pre-set instructions the AI machine provides.
Even though AI systems can be trained to learn and enhance their capabilities, the concept of an AI “teaching itself” is complicated and heavily features ethical and safety issues. Musk’s opinion underscores the need for more care concerning the progress of AI technologies.