Remove Accountability Remove Government Remove industry standards
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Ethically Leveraging AI – Forbes Business Council Insights

Real Blue Sky

.” Bryant’s contribution focused on the importance of establishing good governance. Ethically Leveraging AI Requires Governance Effective and ethical use of AI hinges on robust governance structures which integrate interdisciplinary expertise to navigate complex ethical considerations.

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Establishing an AI/ML center of excellence

AWS Machine Learning

Organizations across industries face numerous challenges implementing generative AI across their organization, such as lack of clear business case, scaling beyond proof of concept, lack of governance, and availability of the right talent. What is an AI/ML CoE?

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Charting the Future of Trust & Safety at TrustCon 2024

24-7 InTouch

Setting Standards: Establishing unified industry standards guides AI governance, promoting transparency, accountability, and ethical deployment across sectors. Bias Mitigation: Alignment between trust and safety protocols and AI development prevents biases in AI models, promoting fairness and inclusivity.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Consider your security posture, governance, and operational excellence when assessing overall readiness to develop generative AI with LLMs and your organizational resiliency to any potential impacts. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

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Top Benefits of ID Document Verification for Financial Services

CSM Magazine

Validating identification documents is an everyday part of the financial services industry. It comes into play when performing different financial services like opening bank accounts and approving loans. It’s crucial for ensuring encrypted transactions and preventing fraudulent behaviors.

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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. All these capabilities are built to help multiple lines of business innovate with speed and agility while governing at scale with central controls.

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Trends to Improve Your Contact Center in 2024

Calltools

When someone calls, your system can review the account’s history to address them by name and offer services that match their frequent needs. Social Responsibility Research from McKinsey shows that brands grow 8% more over a five-year term when they embrace environmental, social, and governance (ESG) initiatives.