Satyen Dayal’s Post

🤖 AI Regulation: Can We Measure AI Power by the Numbers? As AI rapidly advances, regulators are grappling with a crucial question: How do we identify AI systems powerful enough to pose security risks? Key points from recent developments: 📊 The Magic Number: 10^26 flops (floating-point operations per second) ↳U.S. government now requires reporting of AI models at this threshold ↳California's proposed legislation uses this metric, plus a $100 million development cost 🌍 Global Approach: ↳EU's AI Act sets the bar at 10^25 flops ↳China is also exploring compute power as a regulatory metric 🧠 The Debate: ↳Supporters: It's the "best thing we have" to assess AI capability and risk ↳Critics: It's an arbitrary measure that could stifle innovation 💡 Alternative Views: ↳Some argue for more nuanced evaluations of AI capabilities ↳Others suggest focusing on societal impact rather than raw computing power 🔄 Evolving Landscape: ↳Regulations are designed to be adjustable as AI technology progresses ↳Smaller, more efficient models are challenging the relevance of flops as a metric The challenge: Balancing innovation with responsible AI development. As an industry, we need to contribute to this dialogue to ensure effective, fair regulation. Read more: https://lnkd.in/gwrdTkRA What's your take on measuring AI power? How should we approach AI safety? #AIRegulation #TechPolicy #AIEthics #FutureOfAI

Australia’s #financialservices regulator recently trialled an #artificialintelligence system and found that automation alone failed. Humans outperformed AI in the trial, highlighting the importance of augmenting rather than automating, the role of humans in the workforce. In this article Dr Emmanuelle Walkowiak, Affiliate at ADM+S and an #economist from RMIT University, explains why the trajectory of early-stage technology adoption is important, with her research showing organisations are often reluctant to revert technology changes once they are implemented. Read 👉🏼 https://lnkd.in/esZYFeyS

Great article. Governance models are critical to realize the promise of GenAI.  Sound governance models are absolute “must-haves” to overcome 5 big hurdles facing enterprise AI adoption -  1. safeguarding proprietary organizational data/IP, 2. overcoming bias due to flawed training datasets, 3. maintaining privacy of sensitive user information, 4. enabling model accuracy (eloquent responses from GenAI models do not necessarily mean they are factually accurate), and 5. improving prediction explainability (even if predictions are right, how AI models arrive at that those predictions will likely remain difficult to explain because of the way neural networks work). https://mck.co/3RBragz

Who will control the future of AI? «A democratic vision for artificial intelligence must prevail over an authoritarian one. That is the urgent question of our time. The rapid progress being made on artificial intelligence means that we face a strategic choice about what kind of world we are going to live in: Will it be one in which the United States and allied nations advance a global AI that spreads the technology’s benefits and opens access to it, or an authoritarian one, in which nations or movements that don’t share our values use AI to cement and expand their power?» - Sam Altman, co-founder and CEO of OpenAI says in its column to Washington post. https://lnkd.in/esfhbgzG What do you think is the likelihood of an authoritarian scenario developing in AI?

AI stands at the forefront of a global debate on innovation's role in society. Drawing from our 2024 Edelman Trust Barometer Supplemental Report: Insights for the Tech Sector, Satyen Dayal, MD of Technology, Edelman UK, explores the growing lack of trust in AI and highlights the barriers to its adoption. Read here: https://edl.mn/3yKlA5J

Gavin Newsom 's decision to veto AI regulation sends a strong message about the balancing act between innovation and governance. While fostering AI growth is crucial for technological advancement and economic benefits, it’s equally important to ensure responsible development. Regulations should be crafted in a way that doesn’t stifle creativity but rather enhances accountability, especially as AI systems become more integrated into everyday life. The challenge ahead will be finding that equilibrium, and this discussion is far from over. #AIregulations #Governance #Innovation https://lnkd.in/et3RtutT

How powerful is too powerful? Regulators are cracking down on AI by setting limits on computing power—U.S. rules now require AI models performing 100 septillion calculations to be reported! California is pushing for even stricter oversight to prevent misuse like cyberattacks or weapon creation. Some say these rules could hold back innovation, while others insist they’re essential as AI advances fast. 🧠💥 #AI #TechRegulation #ArtificialIntelligence #AIFuture https://lnkd.in/eJMvdb-Q

Sam Altman of OpenAI is touting democracy in The Washington Post but he gets the narrative wrong. Altman doesn't get democracy. Altman makes his case to do what he wants by saying that the United States will become the leader in AI by capitulating to industry. That somehow this will keep AI democratic. Wrong. What will make AI democratic won't be the tax benefits and subsidies to modern-day robber barons. We must embed representative governance into the information and computing ecosystems that surround and feed into AI. We can build #AI and a digital public sphere by/for/of #WeThePeople https://wapo.st/3WlBiw3

When it comes to AI regulation, how do we know when enough is enough? Recent proposals from the U.S. and California set strict guidelines based on computing power. While some argue this is necessary to prevent AI from becoming too powerful, others say the metrics don’t capture the full picture. What’s the right balance between innovation and safety? https://lnkd.in/gaJmkEyi #AI #Regulation #TechEthics #Innovation #Safety #AGJSystems 

When it comes to AI regulation, how do we know when enough is enough? Recent proposals from the U.S. and California set strict guidelines based on computing power. While some argue this is necessary to prevent AI from becoming too powerful, others say the metrics don’t capture the full picture. What’s the right balance between innovation and safety? https://lnkd.in/dE9_Yk_Z #AI #Regulation #TechEthics #Innovation #Safety #AGJSystems