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AI Governance, Trust & Transparency
Resources on AI governance, trust and transparency, including regulations ... Read more »
US Intelligence Community Publishes Guidelines for AI Security Activities and Analytics
As Artificial Intelligence and Machine Learning (AI/ML) solutions proliferate, it is a foregone conclusion that they are an integral component of national security and intelligence operations. Not just for the worlds of finance, healthcare, and online commerce ... Read more »
Systemic Bias in Financial Services_ Fixing a Growing AI/ML Problem
As computational analytics, including Artificial Intelligence and Machine Learning (AI/ML), gain greater traction and an almost essential status in the processing of massive volumes of data, their ubiquity and often inherent predilection for incorrect outcomes have brought both skepticism and distru ... Read more »
PPP Distribution Inequities: How AI Solutions Can Eliminate Bias
No doubt, given the COVID-19 pandemic, there are tough times for everyone, both personally and professionally. Enough said. Those businesses deemed non-essential and already operating on a fiscal shoestring remain in more dire straits than ever. ... Read more »
Trusted AI in Healthcare: Avoiding the Risks of Black Box AI Solutions
Spending on Artificial Intelligence (AI) is expected to more than double from $35 billion in 2019 to $79 billion in 2022, according to IDC forecasts, reflecting the enormous potential societal benefits of AI. Yet broad adoption of AI systems will not come from the benefits alone but from the ability ... Read more »
Consumer Lending and Credit: Tackle Business Risks from AI
The key regulatory issues in consumer lending and credit – fair lending, consumer notification and reporting, and unfair, discriminatory or abusive acts or practices – have implications for various AI business risks. Institutions should get ahead of the issue and tackle AI business risks head-on ... Read more »
Implementing AI Trust in Customer Experience
In 2019, Ovum conducted a market survey and analysis among customer experience (CX) managers and customer-facing employees regarding the current state of their company AI strategies as well as future plans and visions ... Read more »
AI In Model Risk Management: AI’s Unique Characteristics and Operating Model Impacts
Banks will need to evolve and industrialize their MRM functions in the world of big data and AI since AI based models pose unique challenges in terms of business risk management ... Read more »
The Case for Transforming Model Risk Management: Prepare for AI Business Risks
Banks will need to evolve and industrialize their MRM functions in the world of big data and AI since AI based models pose unique challenges in terms of business risk management ... Read more »
Why Bias is Interwoven with Several Other Dimensions of Trusted AI
At CognitiveScale, we have grouped the key aspects of building and deploying trustable AI solutions under 5 pillars, representing 5 major types of Risks that Businesses face if these aspects are not properly addressed while employing AI technologies ... Read more »