World Congress 2023 Aug 11, 2023

The shadows that follow the AI generative models

Cheuk Ho

Stack Overflow restricted AI answers due to unpredictable hallucinations. Uncover the hidden operational vulnerabilities of LLMs and learn how to build robust ethical safeguards for your engineering team.

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#1 about 3 min

Introduction to generative AI and content warnings

An overview of generative AI models alongside content warnings regarding sensitive topics.

#2 about 2 min

Basics of generative AI and prompt interactions

How generative AI models process training data and user prompts to produce new content.

#3 about 4 min

Examples of generative AI applications in media and code

A look at AI-generated images, music, code, and project management tools.

#4 about 6 min

Evaluating the accuracy and correctness of generated content

The challenges of relying on AI for accurate technical answers and the risks of model hallucination.

#5 about 2 min

Security risks involving prompt injection attacks

How prompt injections allow users to manipulate model outputs similar to SQL injection attacks.

#6 about 3 min

Determining ownership and responsibility for generated content

The ethical dilemmas around assigning responsibility for copyright and inappropriate outputs in generated content.

#7 about 4 min

Addressing inherent biases in large language models

Examples of how training data perpetuates racial and gender biases in generated outputs.

#8 about 3 min

Harmful applications including deepfakes and non-consensual imagery

The illegal use of generative AI to create non-consensual imagery and fraudulent identities.

#9 about 2 min

Emerging regulations and cultivating careers in AI ethics

Current regulatory efforts and opportunities for professionals to engage with AI ethics initiatives.

#10 about 3 min

Audience questions on deepfake detection, regulations, and ethics

A discussion on detecting deepfakes, balancing regulations with startup innovation, and mitigating systemic biases.

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