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Risk Management for AI Chatbots

O'Reilly on Data

Welcome to your company’s new AI risk management nightmare. Before you give up on your dreams of releasing an AI chatbot, remember: no risk, no reward. The core idea of risk management is that you don’t win by saying “no” to everything. Why not take the extra time to test for problems?

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UK Government tests frictionless trade models with Ecosystem of Trust pilots

IBM Big Data Hub

The UK government’s Ecosystem of Trust is a potential future border model for frictionless trade, which the UK government committed to pilot testing from October 2022 to March 2023.

Testing 94
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Preliminary Thoughts on the White House Executive Order on AI

O'Reilly on Data

adversarial testing to determine a model’s flaws and weak points), and not a wider range of information that would help to address many of the other concerns outlined in the EO. Methods by which the AI provider manages and mitigates risks identified via Red Teaming, including their effectiveness.

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6 business risks of shortchanging AI ethics and governance

CIO Business Intelligence

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 145
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Digital Transformation: How To Protect Your Organization From Cyber Risk

Smart Data Collective

million —and organizations are constantly at risk of cyber-attacks and malicious actors. In order to protect your business from these threats, it’s essential to understand what digital transformation entails and how you can safeguard your company from cyber risks. What is cyber risk?

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What is Model Risk and Why Does it Matter?

DataRobot Blog

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111
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The Hidden Gem of Savings in the Software Delivery. And no, it’s not AI

CIO Business Intelligence

It will improve project management, help with requirements creation, assist developers with coding, cover the system with auto-tests, report defects, and improve deployment. These include security and data privacy concerns, low-quality data, reputational risks, and immature technology, to name a few.