The first time I imagined AI managing real money without asking for permission, one question immediately came to mind:
who decides when the AI is allowed to act?
🤔
That's the problem @NewtonProtocol wants to solve.
Their idea isn't to make AI smarter. It's to build an authorization layer that checks whether an AI's actions follow predefined rules before any assets move.
Since blockchains verify signatures not judgment that gap is worth paying attention to.
But crypto has taught me to be skeptical.
We've seen countless problems answered with another protocol, another validator set, another governance system, and another token.
Every new layer promises greater security, yet each one also expands the attack surface and adds complexity.
The incentives deserve equal attention. Users may receive better protection, but if this becomes core infrastructure, token holders, validators, and early supporters also gain from the network's growth.
Then comes the question that matters most: how decentralized is decision-
making if a relatively small group can still shape the rules behind authorization?
And when an AI makes the wrong move, who owns the mistake?
The model, the policy creator, the validators,
or the protocol?
Distributing computation is relatively easy.
Distributing accountability has always been the harder challenge and that's usually where the real test begins.
#newt $NEWT $TLM $HMSTR
who decides when the AI is allowed to act?
🤔
That's the problem @NewtonProtocol wants to solve.
Their idea isn't to make AI smarter. It's to build an authorization layer that checks whether an AI's actions follow predefined rules before any assets move.
Since blockchains verify signatures not judgment that gap is worth paying attention to.
But crypto has taught me to be skeptical.
We've seen countless problems answered with another protocol, another validator set, another governance system, and another token.
Every new layer promises greater security, yet each one also expands the attack surface and adds complexity.
The incentives deserve equal attention. Users may receive better protection, but if this becomes core infrastructure, token holders, validators, and early supporters also gain from the network's growth.
Then comes the question that matters most: how decentralized is decision-
making if a relatively small group can still shape the rules behind authorization?
And when an AI makes the wrong move, who owns the mistake?
The model, the policy creator, the validators,
or the protocol?
Distributing computation is relatively easy.
Distributing accountability has always been the harder challenge and that's usually where the real test begins.
#newt $NEWT $TLM $HMSTR