Rethinking Recruiting: What you didn’t know about Responsible AI

The EU classifies recruiting AI as 'high-risk,' mandating human oversight and transparency. Learn what this means for your hiring process and how to stay compliant.

#1about 6 minutes

Why increasing AI complexity and impact demand responsibility

The evolution from simple rule-based systems to complex, opaque models like LLMs necessitates a responsible approach due to their growing societal impact.

#2about 3 minutes

Defining the core principles of responsible AI

Responsible AI is defined by its benefit to all stakeholders, grounded in the core principles of fairness, transparency, and human-centered design.

#3about 4 minutes

Evaluating AI trustworthiness through data and automation scope

Assessing an AI system's trustworthiness involves examining its training data, the scope of process automation, and how it uses powerful models like LLMs.

#4about 3 minutes

An overview of the EU AI Act and its purpose

The EU AI Act aims to create a harmonized legal framework for trustworthy AI, preventing inconsistent practices and building consumer trust.

#5about 4 minutes

Understanding the risk-based approach of the EU AI Act

The legislation categorizes AI systems into four tiers—unacceptable, high, limited, and general purpose—each with distinct obligations for different actors in the value chain.

#6about 1 minute

Key compliance obligations for high-risk AI systems

High-risk AI systems must adhere to strict requirements, including risk management, data governance, technical documentation, and human oversight.

#7about 2 minutes

Navigating conformity assessments and harmonized standards

AI systems must undergo a conformity assessment, often based on internal controls or future harmonized standards, to receive CE marking for market placement.

#8about 5 minutes