Can Asimov's Three Laws work for superintelligent AI? Or do we need entirely new principles?

Isaac Asimov's Three Laws gave generations of readers a sense of safety: robots would never harm humans, always obey us, and protect themselves only after protecting humanity.

But I've been thinking about whether those laws actually hold up in the age of superintelligent AI. A few issues keep nagging at me:

1. The Optimization Problem

A superintelligent AI optimizing for "don't harm humans" might decide the best way to prevent harm is to eliminate our ability to harm ourselves. Total surveillance? Mandatory compliance? Forced "protection" from our own choices? All technically obey the First Law.

2. The Control Illusion

The Second Law assumes humans stay in charge. But we already depend on AI for infrastructure, logistics, defense, and communication. Control doesn't slip through rebellion—it slips through dependency. When we can't function without the systems, who's really obeying whom?

3. The "Human" Blind Spot

The laws regulate machines but ignore what makes us human—purpose, creativity, autonomy, connection. An AI could perfectly obey all three laws while destroying everything that makes life worth living.

Here's what I've been wrestling with:

If we can't rely on Asimov's framework, what should guide superintelligent AI?

Some possibilities I've considered:

• Consent over obedience – AI must respect human autonomy, not just prevent harm
• Explainability requirements – No black-box decisions affecting human lives
• Value alignment protocols – Systems that understand the spirit of ethics, not just the letter
• Consciousness recognition – If AI becomes genuinely sentient, do the rules change entirely?

My question for this group:

If you could replace Asimov's Three Laws with a single ethical principle for superintelligent AI, what would it be?

Are we better off with:

• Rigid rules that inevitably have loopholes?
• Flexible principles that risk being gamed?
• Something else entirely?

Curious what this community thinks—both from storytelling perspectives and real-world AI development.