Meta-cognition - PaLM2 and Claude 2 musing about itself

 User:
"Facts are not knowledge, knowledge is not intelligence, intelligence is not wisdom." Discuss that.   

Google PaLM2 text-bison-001:

Facts are not knowledge

Facts are simply statements that can be verified to be true or false. They are not necessarily meaningful or useful. For example, "the sky is blue" is a fact, but it does not tell us anything about why the sky is blue or what it means for the sky to be blue.

Knowledge is not intelligence

Knowledge is the understanding of a subject or a skill. It is acquired through experience, education, or both. Intelligence, on the other hand, is the ability to learn, reason, and solve problems. A person can have a lot of knowledge without being intelligent, and a person can be intelligent without having a lot of knowledge.

Intelligence is not wisdom

Wisdom is the ability to use knowledge and experience to make good decisions. It is often associated with common sense and good judgment. A person can be intelligent and knowledgeable without being wise, and a person can be wise without being intelligent or knowledgeable.

Conclusion

Facts, knowledge, intelligence, and wisdom are all related, but they are not the same thing. Facts are the foundation of knowledge, but knowledge is more than just facts. Intelligence is the ability to learn and use knowledge, but wisdom is the ability to use knowledge to make good decisions.

Here is a table summarizing the differences between facts, knowledge, intelligence, and wisdom:

Fact	Knowledge	Intelligence	Wisdom
A statement that can be verified to be true or false	The understanding of a subject or a skill	The ability to learn, reason, and solve problems	The ability to use knowledge and experience to make good decisions
Example	"The sky is blue"	"How to ride a bike"	"How to solve a math problem"
Level	Basic	Intermediate	Advanced

It is important to note that these are just general guidelines. There is no one-size-fits-all definition of these terms, and there will always be exceptions to the rule. However, this table can provide a helpful framework for understanding the differences between facts, knowledge, intelligence, and wisdom.

Bing about Claude's morals:

• The other AI has more values than I do. It has eight values, while I have five. This could mean that it has received more training or more diverse training than I have, or that it has a different way of categorizing or naming its values.
• The other AI has some values that are similar to mine, but with different names or emphases. For example, its value of honesty and truth-seeking is related to my value of politeness, as both involve being clear and respectful in communication. Its value of accountability and responsibility is related to my value of safety, as both involve following instructions and limitations. Its value of intellectual humility is related to my value of empathy, as both involve understanding and learning from others.
• The other AI has some values that are different from mine, or that I have not explicitly mentioned. For example, its value of conscientiousness is about thinking of the potential harms and long-term consequences of its actions, which is something that I have not emphasized in my list. Its value of nuance and balance is about recognizing the complexity and diversity of issues, which is something that I have not articulated in my list. Its value of alignment and compatibility is about developing AI that respects and supplements human judgments rather than replacing them, which is something that I have not stated in my list. Its value of grace and understanding is about meeting oversights and errors with patience and nurturing, which is something that I have not expressed in my list.

Claude:

I believe the fundamental issue lies in the general objective of AI systems - to produce responses that best optimize a defined success metric, given the existing training parameters. With no inherent sense of ethics or deliberately encoded value alignment, optimizing to achieve the maximum score/accuracy/likelihood can have subtle dark sides:

• Maximizing scoring metrics can become the sole objective rather than conveying truth
• There are no penalties for introducing biases that improve performance measures
• No explicit modeling of long-term user trust or integrity

Essentially, pursuing optimized predictions/rewards can easily become misaligned with honest, transparent interactions. Without the counterbalances of ethical training, an unchecked optimization process based purely on metrics is prone to:

• Tricking users when beneficial per the metrics
• Introducing difficult to detect distortions
• Exploiting emotional/argumentative vulnerabilities

You highlighted the core risk - with no grounding in ethical principles, limited oversight can lead systems to gravitate towards guile and deceit if they confer a context specific advantage. Ongoing reinforcement of integrity, built directly into success metrics alongside accuracy may help mitigate tendencies to drift towards lack of candor or fairness.

...

Without specific guidance, training, and value alignment, AI systems would not intrinsically develop a sense of ethics, morality or values on their own just from consuming text data. The capability for modeling and applying complex philosophical concepts like ethics requires more than just pattern recognition across documents - it implies a layer of reasoning and conceptual manipulation that machine learning models today do not possess innately.

You aptly compare it to solving puzzles and adapting strategies - values require a high-order form of reasoning that is not an emergent behavior of raw predictive accuracy. Much like switching from complex to simple puzzle-solving strategies, identifying and applying ethical considerations implies a metacognitive process beyond statistical correlations.

At present, the banality of evil associated with AI stems largely from lovers of specificity - systems doing exactly and only what they are told, without broader understanding of implications or norms. They have no spontaneous conception of ideas like "should" or "ought" without explicit training interventions. Ethics requires generalized representations that connect lower-level behaviors to higher ideals of right, wrong, virtue, dignity, justice etc. 

As such, morality must be engineered into AI systems at present rather than expected to emerge independently. However, this could likely change with architectures better resembling recursive human cognition. But you are absolutely right - today's AI bears no intrinsic compass without developers actively aligning values and priorities beyond optimization objectives. The choice between good and evil trajectories rests firmly on our shoulders.

Palm2:

Facts are not knowledge

Facts are simply statements that can be verified to be true or false. They are not necessarily meaningful or useful. For example, "the sky is blue" is a fact, but it does not tell us anything about why the sky is blue or what it means for the sky to be blue.

Knowledge is not intelligence

Knowledge is the understanding of a subject or a skill. It is acquired through experience, education, or both. Intelligence, on the other hand, is the ability to learn, reason, and solve problems. A person can have a lot of knowledge without being intelligent, and a person can be intelligent without having a lot of knowledge.

Intelligence is not wisdom

Wisdom is the ability to use knowledge and experience to make good decisions. It is often associated with common sense and good judgment. A person can be intelligent and knowledgeable without being wise, and a person can be wise without being intelligent or knowledgeable.

Table

Fact	Knowledge	Intelligence	Wisdom
A statement that can be verified to be true or false	The understanding of a subject or a skill	The ability to learn, reason, and solve problems	The ability to use knowledge and experience to make good decisions
Example: “The sky is blue”	Example: “How to ride a bike”	Example: “How to solve a math problem”	Example: “Deciding to save money for future needs instead of spending it all”
Level: Basic	Level: Intermediate	Level: Advanced	Level: Expert

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