Accusoft’s Post

Discover how AI automates the process, ensuring accuracy, efficiency, and compliance while keeping your data secure. Read the full blog to learn more about how AI is transforming PII redaction.

🔍 AI can solve data challenges—but it can create new ones too. This article nails the often overlooked first step - strong data management.     Before we get carried away with AI’s potential, let’s ensure privacy and compliance remain front and center - like they do with Zafer (AI)    #ai #enablingtrust #saferwithzafer

Veritas' Andy Ng discusses the importance of adopting proper data management practices to drive successful AI adoption. Read more in IT Brief Asia here. #Veritas #AI

A third of all user AI conversations on Wald.ai contain sensitive data. But, many users don’t realize how vulnerable their confidential data is when using AI Assistants. My latest article in Forbes unpacks the hidden risks and innovative solutions related to contextual data redaction. Writing this piece gave me the opportunity to illustrate how data redaction technology works and encourages businesses to implement contextual redaction mechanisms — rather than overlooking the issue or banning AI tools altogether. Check out the full article. Would love to hear your thoughts and perspectives in the comments!

Effective use of #AI depends on the proper management of data. This article argues that without robust data handling strategies, even the most advanced AI initiatives can falter. #data #GenAI #strategy

Our latest article.covering the growing Focus on synthetic data especially as our AI models need significant amounts of training data. The best data sets from a compliance standpoint are those that have been curated to match real life data sets without any actually using any real personal data sets. Synthetic data appears to promises this provided the process of creating these synthetic datasets is done right. in particular the risks of re-identification has to be reduced to negligible levels and where the synthetic data is sourced/modeled on actual personal data that the de-identification process is thorough and complete. PDPC’s proposed Syntheric data guide is a helpful and timely addition to the ongoing thinking in this area.

#CyberSurakshitSeries | 🚀 𝐀𝐈-𝐑𝐞𝐚𝐝𝐲 𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: 𝐓𝐡𝐞 𝐏𝐚𝐭𝐡 𝐭𝐨 𝐔𝐧𝐥𝐨𝐜𝐤𝐢𝐧𝐠 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 🚀 In today's data-driven world, effective #datamanagement and #governance are essential to harness the true potential of #AI. 💡 I wrote this article exploring how organizations can lay the foundation for #AI success by implementing robust #datastrategies, from ensuring #dataaccuracy and #compliance to empowering AI #algorithms, uncovering key components required for a future-ready business. #data #security #cybersecurity #information #security #LLMs #DataGovernance #DataManagement #DigitalTransformation #BusinessInnovation #CyberSecurityAwarenessMonth #CSAM #CyberSurakshitBharat #strESCON #ESCON StrategINK

#CyberSurakshitSeries | 🚀 𝐀𝐈-𝐑𝐞𝐚𝐝𝐲 𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: 𝐓𝐡𝐞 𝐏𝐚𝐭𝐡 𝐭𝐨 𝐔𝐧𝐥𝐨𝐜𝐤𝐢𝐧𝐠 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 🚀 In today's data-driven world, effective #datamanagement and #governance are essential to harness the true potential of #AI. 💡 This engaging article from Prateek Bhamri explores how organizations can lay the foundation for AI success by implementing robust #datastrategies, from ensuring #dataaccuracy and #compliance to empowering AI #algorithms, he uncovers the key components required for a future-ready business. Read complete article here: https://lnkd.in/gcYtnu66 #DataGovernance #DataManagement #DigitalTransformation #BusinessInnovation #CyberSecurityAwarenessMonth #CSAM #CyberSurakshitBharat #strESCON #ESCON StrategINK

SUMMARY OF MY WORK ON AI AUDITING DEVELOPED FOR THE EUROPEAN DATA PROTECTION BOARD (EDPB) Checklist for AI Auditing - Developed together with the team at Eticas AI - What you will find a) A detailed list of questions related to the governance, transparency and data management (including fairness, robustness, performance and traceability of AI processes and decisions) of AI systems and models b) An introduction to end-to-end, socio-technical algorithmic auditing (E2EST/AA) which allows auditors to capture issues that may occur during system training and data pre-processing and all the way to a system's recorded impacts in real-life scenarios. c) An introduction to the "moments" and "sources" of bias which visualize the multiple instances in which an AI system can incorporate and reproduce discrimination,  d) Clear links between GDPR (specifically Articles 5, 9, 13-15, 22, 24, 25 and 35) and AI applications e) A "model card" that can be used to document each audit and updated over time - Who should use the checklist Anyone involved in AI auditing/oversight, including #DPOs seeking to engage with #AI models and developers seeking to incorporate compliance requirements in AI development - What AI systems does it apply to: a) The checklist is optimized for recommender AI systems deployed in high-risk scenarios b) About 70% of the checklist questions are applicable to LLMs, but the formats, end users and impacts are different for recommender systems and LLMs https://lnkd.in/eYFcaT_k

Commentary: The use of AI can both solve and create challenges for the businesses that embrace it. To prepare for potential roadblocks, corporations should ensure that data is handled in compliance with industry expectations. https://lnkd.in/eRfnvuKM