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Global executives and AI strategy for HR: How to tackle bias in algorithmic AI

IBM Journey to AI blog

In line with this trend, the New York City Council has enacted new regulations requiring organizations to conduct yearly bias audits on automated employment decision-making tools used by HR departments. As per the new law, noncompliant organizations may face fines ranging from no less than USD 500 to no more than USD 1500 for each violation.

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Bridging code and conscience: UMD’s quest for ethical and inclusive AI

AI News

As artificial intelligence systems increasingly permeate critical decision-making processes in our everyday lives, the integration of ethical frameworks into AI development is becoming a research priority. So, in this field, they developed algorithms to extract information from the data.

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Generative AI vs. predictive AI: What’s the difference?

IBM Journey to AI blog

What is predictive AI? Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes. These adversarial AI algorithms encourage the model to generate increasingly high-quality outputs.

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The importance of diversity in AI isn’t opinion, it’s math

IBM Journey to AI blog

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. These issues require more than a technical, algorithmic or AI-based solution. Consider, for example, who benefits most from content-recommendation algorithms and search engine algorithms.

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Cybersecurity AI Trends to Watch in 2024

Unite.AI

Ultimately, staying updated empowers enthusiasts to leverage the full potential of AI and make confident decisions in their professional and personal pursuits. AI-Powered Threat Detection and Response AI takes the lead in making the digital world safer.

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Everything You Need to Know About NYC’s Automated Employment Decision Tools (AEDT) Law

Dlabs.ai

In an era where AI and machine learning have streamlined everything, including hiring processes, the balance between efficiency and equity comes into question. With algorithms, machine learning, and statistical modeling defining who gets hired or promoted, are these decisions genuinely fair? What are AEDTs?

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Generative AI in the Healthcare Industry Needs a Dose of Explainability

Unite.AI

Mystery and Skepticism In generative AI, the concept of understanding how an LLM gets from Point A – the input – to Point B – the output – is far more complex than with non-generative algorithms that run along more set patterns. Additionally, the continuously expanding datasets used by ML algorithms complicate explainability further.