Joint Services’ Post

The Link Between Identity and Access Management (IAM) and AI Governance Identity and Access Management (IAM) and AI Governance may seem like distinct areas, but they are deeply interconnected. Both aim to ensure the secure, ethical, and trustworthy use of technology.  KYP

🚀 As AI continues to evolve, new challenges are emerging that directly impact your business. 🧐 Today, let’s talk about 𝐦𝐨𝐝𝐞𝐥 𝐢𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧. It is a type of machine learning attack where an attacker aim to extract sensitive information from the model’s output, such as instances of the training set. In a nutshell, model inversion allows attackers to reconstruct parts of your model's training data, putting your corporate secrets at risk. 🚨𝐖𝐡𝐲 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫 𝐭𝐨 𝐲𝐨𝐮? Because these attacks target your most valuable assets: your model. An attack can compromise: ⚠️ Your data confidentiality, which is crucial for user trust and compliance. ⚠️ Your competitive edge ⚠️ Your intellectual property To find more about the subject: Skyld.io So, how can you stay protected? And how do you think these threats will evolve? 👇 Share your thoughts in the comments!

Today I learnt about Governance, it's importance, challenges and issues when AI isn't regulated. Also I understood the AI TRiSM ( Trust, Risk and Security Management) and Gartner's AI-TRiSM and it's four pillars. I became aware about how vulnerable we are to AI if not checked and shadow AI and the 5 step paths to AI Governmence.

#Learning Alert Thanks Wasim M. for sharing. A good starting point. Some recommendations for improvement based on my experience, implementing and assessing AI systems- 1. Auditing principles of #AI data models to emphasize #ethical AI There is an adverse business impact, issues in #product #scalability and higher risk mitigation effort if #ethical AI development is not ensured 2. Auditing guidelines for trustworthy AI to ensure explainability of #AI Systems 3. Business impact as a cornerstone to #Risk Management and #AI Governance is unaccounted. #ISO42001 #trustworthyAI #EUAIAct

Random prediction: Experience espionage for AI data scrapping. Unethical training on proprietary art, design, and experience will create teams of people signing up for services just to capture what’s behind the paywall or password protected experience. Other than an Air gapped server at home is there any way to protect your digital universe from the machine. If you share that data out , there is no way that I see today of it not going through a company that can “abstract it” into training material. I think there is going to be a bright future for whomever creates the user friendliest on prem or on device , controllable point to point encryption. I used to use voltage but it creates so much friction in the experience. The red pill or blue pill choice is getting harder and harder by the day.

the latest McKinsey report on gen AI adoption offers some interesting insights. here are some that were brought to my attention: - businesses finally woke up and aren't scared to throw budgets into expanding their toolset with fresh AI stuff (or even in R&D) - gen AI seems like a game-changer even for conservative industry like supply chain & logistics - people are still worried about accuracy issues, IP and cybersecurity risks  - effective risk management and strategic implementation are key to adoption AI successfully. if you were thinking about how AI can leverage your operations, this report might come in handy. worth a read (link in a comment below).

🔐 How does a fast-moving startup deliver tailored insights while protecting personal #data and complying with regulatory requirements? Hear how Immuta helps AstrumU® balance #datasecurity with efficient, ethical access and use to deliver personalized recommendations to students, educators, and employers with #AI and #ML. https://bit.ly/3VDg0uQ

Effective management of artificial intelligence (AI) is vital for fostering digital trust. It encompasses effective governance, risk management, transparency, safety, and proactive communication, all of which contribute to a trustworthy environment where users can confidently engage with AI technologies. Studies have shown that increased transparency can enhance trust in AI, as users feel more informed and secure about the technology they are engaging with, conversely research shows that consumers will not engage with an organisation that is unclear on how AI is being used in digital product and/or service delivery. This personal/workforce development pathway will enable you/your teams to understand how and why effective management of AI helps to build and maintain consumer trust and confidence in an organisation. Eight courses, typically completed over a 6-12 month period including: ✅ Digital Trust Professional® (DTP®) Foundation Certificate ✅ Digital Trust Professional® (DTP®) Risk Management Foundation Certificate ✅ Certified ISO 31000 Risk Manager ✅ Digital Trust Professional® (DTP®) Secure by Design Foundation Certificate ✅ NIST Cybersecurity Professional® (NCSP®) Foundation Certificate ✅ Certified ISO 42001 Lead Implementer ✅ Certified ISO 42001 Lead Auditor ✅ Artificial Intelligence Practitioner Certification (AIP) Further details: https://lnkd.in/e8B6DaTF #digitaltrust #digitaltrustprofessional #digitaltrustcollective

#GenerativeAI Models- Opportunities & #Risks for #Industry & Authorities- Key #insights from Federal Office for Information Security (BSI) report ✅ #GenerativeAImodels are capable of performing a wide range of #tasks and learn %patterns from existing #data during #training and can subsequently and represent an opportunity for #digitalization. ✅ the use of generative AI models introduces novel #IT #securityrisks that need to be considered for a comprehensive analysis of the #threat landscape in relation to #ITsecurity. ✅ companies or #authorities using them should conduct an individual risk analysis before integrating generative AI into their workflows. ✅ #LLMs generally generate linguistically correct and convincing text and are capable of making statements on a wide variety of topics. This can create the impression of a #human like performance, leading to excessive #trust in the statements and the performance of the models (so-called #automation bias). ✅ #Developers and operators should provide sufficient information to enable users to make informed assessments of a model's suitability for their use case. Information about risks, implemented countermeasures, remaining residual #risks, or limitations should be clearly communicated. #LLMs #GenAI #Artificialintelligence #AI #AIrisk #Cybersecurity #RiskManagement #Bigdata #FinTech #Finserv #Regulation #Regtech #AIgovernance #Suptech #AIBias #AItrust #AIEthics Mike Flache Tony Moroney Francesco Burelli Panagiotis Kriaris Dr. Martha Boeckenfeld Prof. Dr. Ingrid Vasiliu-Feltes Imtiaz Adam Alex Jimenez Spiros Margaris Nicolas Babin Nicolas Pinto Sam Boboev Segundo Ramos Dan Feaheny Enrico Molinari Dr. Khulood Almani🇸🇦 د.خلود المانع Eveline Ruehlin Franco Ronconi Amitav Bhattacharjee Dr. Debashis Dutta https://lnkd.in/gnFx5biq

#GenerativeAI Models- Opportunities & #Risks for #Industry & Authorities- Key #insights from Federal Office for Information Security (BSI) report ✅ #GenerativeAImodels are capable of performing a wide range of #tasks and learn %patterns from existing #data during #training and can subsequently and represent an opportunity for #digitalization. ✅ the use of generative AI models introduces novel #IT #securityrisks that need to be considered for a comprehensive analysis of the #threat landscape in relation to #ITsecurity. ✅ companies or #authorities using them should conduct an individual risk analysis before integrating generative AI into their workflows. ✅ #LLMs generally generate linguistically correct and convincing text and are capable of making statements on a wide variety of topics. This can create the impression of a #human like performance, leading to excessive #trust in the statements and the performance of the models (so-called #automation bias). ✅ #Developers and operators should provide sufficient information to enable users to make informed assessments of a model's suitability for their use case. Information about risks, implemented countermeasures, remaining residual #risks, or limitations should be clearly communicated. #LLMs #GenAI #Artificialintelligence #AI #AIrisk #Cybersecurity #RiskManagement #Bigdata #FinTech #Finserv #Regulation #Regtech #AIgovernance #Suptech #AIBias #AItrust #AIEthics