Pinaki Ranjan Aich, CISA’s Post

"With AI use, innovation, and regulation confusion outpacing ratified standards, IT leaders are left to develop in-house approaches to mitigating AI risks, leaning on frameworks, tools, and their colleagues to get AI right." #AI #AIgovernance #ITtransformation

Big news in the realm of AI Governance! Massachusetts Institute of Technology (MIT) has just released a groundbreaking (and free) 'AI Risk Repository' tool, which allows a user to understand the scope of potential risks pertaining to the implementation and use of AI. The tool contains a database that contemplates over 700 different types of AI-related risks, populated using over 40 different AI risk frameworks as its source material, divided into various categories based on the source, type and manifestation of those risks. This will undoubtedly be a revolutionary tool that may influence global law and policy, particularly in the area of AI governance, and gives a fantastic impression of the breadth and depth of the AI risk profile generally, as well as the varied and nuanced ways in which legal, commercial and regulatory risk may permeate the AI lifecycle. I recommend that anyone with a keen interest in AI governance looks at this tool, as it will undoubtedly provide a great deal of value, especially when it comes to ideating about particular governance controls that an organisation may wish/need to implement in connection with its specific AI program.

New NIST guidance is here to help us build a safer AI future! 🤖 The #NIST AI Risk Management Framework provides essential tools for organizations to develop, deploy, and use AI responsibly. Key areas covered include: 🔘Valid and reliable AI systems 🔘Safe and secure AI operations 🔘Accountable and transparent AI governance 🔘Explainable and interpretable AI models 🔘Privacy-enhanced AI practices 🔘Fairness with mitigation of harmful bias Check out the full framework at https://lnkd.in/ewbtdTGF #AIethics #AIriskmanagement #trustworthyAI

The NIST AI Risk Management Framework (AI RMF) has released a new Generative AI Profile to help organizations manage risks from generative AI systems; here are the highlights: • Defines 12 key generative AI risks, including confabulation, data privacy, harmful bias, and information security • Provides suggested actions to govern, map, measure, and manage these risks across the AI lifecycle • Emphasizes pre-deployment testing, content provenance, and incident disclosure • Developed through public feedback and stakeholder consultations • Aims to promote trustworthy and responsible practices for generative AI This profile offers valuable guidance for organizations developing or deploying generative AI technologies. 🔗https://zurl.co/RNLT #AIRiskManagement #GenerativeAI #ResponsibleAI

𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐈 𝐑𝐢𝐬𝐤 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 𝐟𝐨𝐫 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 On July 26, the National Institute of Standards and Technology (NIST) published the #AI #Risk #Management #Framework: 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐏𝐫𝐨𝐟𝐢𝐥𝐞. 》This document is a companion resource to the AI Risk Management Framework (AI RMF 1.0) specifically for Generative AI, in line with President Biden's Executive Order 14110 on ensuring safe and trustworthy AI. 》The framework is designed for voluntary adoption by organisations that aim to integrate the principle of trustworthiness into the design, development, and evaluation of AI products and services. 》The ‘profile’ is tailored for Generative AI, detailing how to implement the AI RMF functions, categories, and subcategories according to an organisation's needs, risk tolerance, and resources. 》The framework helps organisations manage AI risks effectively, aligning with their strategic goals and adhering to legal and regulatory standards. 》This profile addresses risks common across various sectors, particularly those associated with large language models and cloud-based services. 》The document highlights new and intensified risks linked to Generative AI technologies. 》It offers a set of suggested actions for organisations to govern, map, measure, and manage these identified risks throughout the AI lifecycle. Follow Remy Takang Arrey, CAPA, LL.M, MSc.

Organisations are increasingly adopting AI technologies, leading to a need for directors and boards to understand the governance requirements for ethical and informed AI use. While AI offers productivity gains, it also poses risks from misuse and failures. Boards face challenges in implementing oversight systems and gaining visibility into AI use. Resources like A Director's Guide to AI Governance aim to help directors seize AI opportunities while mitigating risks. The Australian Government is considering regulations to support safe AI deployment.

AI's rapid growth brings challenges and opportunities. Sid Nag from Gartner warns, "AI is such a runaway train and everybody is trying to make a buck off it." Companies prioritize governance to harness AI for growth while managing risks: https://bit.ly/3OTWne2 #GartnerIT #AI #Governance #Innovation

Want to document AI assessments under the EU AI Act? Read on 👩🏫 Documenting AI assessments under the EU AI Act involves a structured approach to recording your evaluation and compliance efforts related to AI systems, especially those the Act classifies as high-risk. In fact, documentation demonstrates compliance with regulatory requirements, enhances transparency and accountability, and supports ongoing monitoring and risk management of AI deployments. https://lnkd.in/dT5ezE4C #AIAssessments #AILaw #EUAIAct #Michalsons

AI's rapid growth brings challenges and opportunities. Sid Nag from Gartner warns, "AI is such a runaway train and everybody is trying to make a buck off it." Companies prioritize governance to harness AI for growth while managing risks. #GartnerIT #AI #Governance #Innovation

AI's rapid growth brings challenges and opportunities. Sid Nag from Gartner warns, "AI is such a runaway train and everybody is trying to make a buck off it." Companies prioritize governance to harness AI for growth while managing risks. #GartnerIT #AI #Governance #Innovation