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How Safe Is Safe Enough?

Red-Teaming and Risk Evaluation for LLMs

As AI technology moves beyond the proof-of-concept stage, it’s time to dig deeper into its power and limitations. Whether you're a model builder, app developer, or part of the AI community, this session will equip you with a clear, risk-based approach to identifying and addressing concerns about model safety and bias.

Webinar 6 November 17:00 CET

How Safe Is Safe Enough?

Red-Teaming and Risk Evaluation for LLMs

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Webinar 6 November 17:00 CET

Toloka's topic:

How Safe Is Safe Enough?
Red-Teaming and Risk Evaluation for LLMs

Date:

6 November

17:00 CET

Where:

Online

Speakers from Toloka:

Ilya Kochik

VP of Business Development

Alexander Borodetskiy

VP of Growth,
Responsible AI

Toloka's topic:

How Safe Is Safe Enough?
Red-Teaming and Risk Evaluation for LLMs

Date:

6 November

17:00 CET

Where:

Online

Speakers from Toloka:

Ilya Kochik

VP of Business Development

Alexander Borodetskiy

VP of Growth,
Responsible AI

Toloka's topic:

How Safe Is Safe Enough?
Red-Teaming and Risk Evaluation for LLMs

Date:

6 November

17:00 CET

Where:

Online

Speakers from Toloka:

Ilya Kochik

VP of Business Development

Alexander Borodetskiy

VP of Growth,
Responsible AI

Overview

In this session, we will guide you through evaluating the safety and biases of GenAI models. Whether you're a model builder, app developer, or industry regulator, this session will equip you with a clear, risk-based approach to identifying and addressing key safety concerns.. Here's what you can expect:

A bit of theory: Why AI safety matters, an overview of safety methods, and key safety evaluation techniques.

DIY guide: How to create your own safety policy, evaluate fairness and biases, and when to apply red-teaming.

What to assess: Major risk categories, user and model intents, and critical scenarios to watch for.

Speakers

Ilya Kochik

Toloka

VP of Business Development

Alexander Borodetskiy

Toloka

VP of Growth,
Responsible AI

Register