Dipatlisiso

Litokelo, mesebetsi, boikarabelo, le taolo ya AI, AGI, le di-agent — ho tloha disebedisweng, ho ea balekaneng, ho isa dihloohong tse ka bang teng nakong e tlang. Sena se kenyeletsa potso ya tshireletso e tlase ya boitshwaro: melawana efe e lokelang ho laola tshebedisano ya motho-le-AI pele dipotso tsa bomotho di rarolloa.

What AI systems may do with content: read, summarize, transform, retrieve, train, commercialize, redistribute. The AICR ruleset and the AICL-C content-licensing layer make these rights declarable and transactable.

Hore na AI e ka ithuta, ka botebo bofe, bakeng sa dipheo dife, le tlasa boikarabelo bofe. Ho baleha ha se ho ithutwa ho tsona; ‘ha ho a hanelwa’ ha se ‘ho ka ithutwa.’ AIRS le AILP di fetola tumello ya ho ithuta hore e be sepekthramo se ntseng se eketseha, se balehang ke mochini.

Kamoo di-agent di fihlellang disebaka tsa marang-rang, di-API, didatabase, mabokose a tsebo, le diteng tse lefellwang: boitsebiso, tumello, dikopo, tefo, tumello ya semmuso, direkoto tsa tshebediso, meeli ya tshireletso, le tshireletso kgahlanong le prompt injection.

What an Agent may DO once it holds tool or API capability, as distinct from what it may read or learn: action taxonomy, effect vectors, reversibility, blast radius, and multi-action composition risk. AARS gives content permission and action permission separate, independently-evaluable axes.

Who an Agent acts for, where its authority came from, whether it can hand that authority to another Agent, and how much of its internal state a verifier may demand. AADP separates principal from actor, bounds delegation to strictly narrow (never silently widen), and treats inspection as a bounded right, not an unlimited one.

Melawana ya taolo eo mechini e ka e fumanang mme ya e phethahatsa: llms.txt, di-manifest tsa /ai/, difaele tsa maano tsa /.well-known/, Disekema tsa JSON, di-token tsa laesense tse saenilweng, le mefuta ya direkoto tsa tlhahlobo. Sebaka sena ka bosona ke mohlala o sebetsang.

Moruo-le-dipolotiki wa AI le diteng: pay-per-crawl, meputso ya data, disefe tsa AI tsa naha, dikago tsa meputso ya baqapi, mmaraka wa data o arotsweng ka mekgahlelo, le kamoo boleng bo ntshitsweng tsebong ya setjhaba bo ka kgutlelang ho ba bo hlahisitseng.