Issue #20 of The Two But Rule | Explore AI regulation with the All-In Podcast. Explore ideas for sandbox testing, AI watchdogs, and content signature filtering.
2) But, it would be easy for objectives to be disregarded by businesses overtime as they pivot to current market environmental conditions, to justify short-terminist opportunities or, as the case may be, satisfying the opinions of a new leadership team. BUT, an AI system trained on the historical data of the company can advise on how to satisfy these short-term commitments without contravening the objectives set by the company. AI systems trained on internal data are more likely to have intimate knowledge of the company's priorities and set the right course of action, eschewing the input from expensive external consultants. BUT, again the AI system could be biased to provide input that the senior leadership team want to hear, which amplifies 'confirmation bias'. SMART objectives should, therefore, be codified in an AI system that can assess whether a single decision or decision is likely to align with that objective on a realistic probability scale.
"As I understand it, Michael Borrelli, you are something of a scholar on new EU regulation changes regarding AI, yes?"
While I would never call myself an expert, I have a passion for regulation, law and related disciplines. As a risk-taking entrepreneur, knowing where the boundaries are - and how to remain within them - allows me to build a sustainable business.
AI & Partners helps firms subject to the EU AI Act build trustworthy AI as well as value-added services. We leverage our knowledge of the regulatory environment to empower them as regulatory structures can asphyxiate businesses at the critical early stage growth phase.
2) But, it would be easy for objectives to be disregarded by businesses overtime as they pivot to current market environmental conditions, to justify short-terminist opportunities or, as the case may be, satisfying the opinions of a new leadership team. BUT, an AI system trained on the historical data of the company can advise on how to satisfy these short-term commitments without contravening the objectives set by the company. AI systems trained on internal data are more likely to have intimate knowledge of the company's priorities and set the right course of action, eschewing the input from expensive external consultants. BUT, again the AI system could be biased to provide input that the senior leadership team want to hear, which amplifies 'confirmation bias'. SMART objectives should, therefore, be codified in an AI system that can assess whether a single decision or decision is likely to align with that objective on a realistic probability scale.
"As I understand it, Michael Borrelli, you are something of a scholar on new EU regulation changes regarding AI, yes?"
While I would never call myself an expert, I have a passion for regulation, law and related disciplines. As a risk-taking entrepreneur, knowing where the boundaries are - and how to remain within them - allows me to build a sustainable business.
AI & Partners helps firms subject to the EU AI Act build trustworthy AI as well as value-added services. We leverage our knowledge of the regulatory environment to empower them as regulatory structures can asphyxiate businesses at the critical early stage growth phase.
Check out our LinkedIn page: https://www.linkedin.com/company/ai-&-partners/.
Thank you, John.
Do you ever think the reverse can be true: innovation won't keep pace with regulation? (Think of a see-saw of momentum shifts.)
Indeed. Great read. +But, Unaligned entities that won’t regulate? Smaller nation states and the likes of Palantir?