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Good AI governance isnโt about doing everything fast. Itโs about understanding what matters before taking action. Most companies rush into AI governance by adding random rules, checklists, and risk assessments. But the smarter approach is to pause first and ask: - What AI systems are we actually using? -... show more
20,749 Aufrufe โข vor 4 Monaten โขvia X (Twitter)
14 Kommentare
map then move
Haha
hard agree with this take bro
Yes๐
now that harnesses are a thing, some of the gov needs to drift there. out-of-band file validation enables deeper checks --> lower fp/tn while not getting the agent slower. and fix one for a multi-agent.
which industry is getting hit hardest by ai regs rn - finance or healthcare?
Healthcare, I think. So much restrictions there.
AIใฌใใใณในใฎ้่ฆๆงใฏใๆฉๆใซ่กๅใใใใจใงใฏใชใใ่กๅใ่ตทใใๅใซไฝใ้่ฆใใ็่งฃใใใใจใงใใใฉใณใใ ใชใซใผใซใใใงใใฏใชในใใใชในใฏ่ฉไพกใ่ฟฝๅ ใใใใจใงAIใฌใใใณในใซๆฅใใงๅใ็ตใไผๆฅญใๅคใใงใใใ่ณขใใขใใญใผใใฏๆๅใซไธๅผๅธ็ฝฎใใไปฅไธใ่ใใใใจใงใ๏ผ - ็งใใกใๅฎ้ใซไฝฟใฃใฆใใAIใทในใใ ใฏไฝใงใใ๏ผ - ็งใใกใซ้ฉ็จใใใๆณๅพใ่ฆๅถใฏไฝใงใใ๏ผ - ๆใ ใๆฌๅฝใซๆฐใซใใใชในใฏใฏไฝใงใใ๏ผ - ็งใใกใฎใฏใฉใคใขใณใใๅฉๅฎณ้ขไฟ่ ใฏ่ชฐใงใใ๏ผ ใใฎๆ็ขบใใฎในใใใใในใญใใใใใจใๅพใงใในใฆใๅๆง็ฏใ็ถใใชใใใฐใชใใพใใใAIใฌใใใณในใฎใฌใคใคใผใซใคใใฆ่ฉณใใ็ฅใใใๅ ดๅใฏๆทปไปใใใใใญใฐใ่ชญใใงใใ ใใใ
The 'add more rules' trap is real. Every AI concern triggers a new policy layer until governance overhead costs more than the risk it was protecting. Better frame: instead of 'what could go wrong', start with 'what does good look like and what's the minimum required to enable it consistently'. Constraints should enable, not just restrict.
Agreed. But โunderstand firstโ has to become an executable governance structure. For agentic AI, understanding is not enough unless the system can prove: what the original intent was, what authority was granted, which agent acted, which tool action changed the world, what evidence supported it, and whether the outcome was accepted. That is why I define AI Agent Governance as a lifecycle problem. MPLP turns this into protocol objects, not just advisory language. Full framework: #AICompliance #AIGovernance #MPLP
That's a very well written article. The feedback loop is the most important layer and what keeps it all relevant. Teams adopt AI tools faster than governance can wrap controls around it
ๅคงๅใชใฎใฏใ่กๅใ่ตทใใๅใซไฝใ้่ฆใใ็่งฃใใใใจใงใใAIใฌใใใณในใฏๆฅใใงใในใฆใ่กใใใจใงใฏใใใพใใใใฉใณใใ ใช่ฆๅใใใงใใฏใชในใใใชในใฏ่ฉไพกใ่ฟฝๅ ใใไผๆฅญใๅคใใงใใใ่ณขใใขใใญใผใใฏใพใไธๅผๅธ็ฝฎใใใจใงใใใฉใฎAIใทในใใ ใๅฎ้ใซไฝฟ็จใใฆใใใฎใใใฉใฎๆณๅพใ่ฆๅถใ้ฉ็จใใใใฎใใใฉใฎใชในใฏใๆฌๅฝใซ้่ฆใใ็งใใกใฎใฏใฉใคใขใณใใในใใผใฏใใซใใผใฏ่ชฐใใใใฎๆ็ขบใใฎในใใใใในใญใใใใใจๅพใงใในใฆใๅๆง็ฏใใชใใใฐใชใใพใใใ
The companies that pause longest on governance are usually using it as cover to delay AI adoption entirely. There's a real difference between thoughtful risk assessment and institutional inertia dressed up as caution.
้่ฆใชใใจใฏไฝใ็่งฃใใใใจใใๆฅใใใใใใจใฏใใกใ
