Ethics by Design: The Role of AI Engineers in Shaping Responsible Generative AI
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The document discusses the role of AI engineers in building responsible generative AI applications. It covers why responsible AI is important given pitfalls like harmful content. It defines the role of an AI engineer versus an ML engineer in shaping applications. It then discusses how AI engineers can implement techniques like filtering, prompt engineering, and retrieval augmented generation to build applications that produce desirable outputs and overcome limitations of current AI models.
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Ethics by Design: The Role of AI Engineers in Shaping Responsible Generative AI
- 1. Ethics by Design: The Role of AI Engineers in Shaping Responsible Generative AI DSC Europe 2023 – Heiko Hotz
- 2. About myself Heiko Hotz • Founder of not-for-profit Meetup group NLP London • Solutions Architect for Generative AI
- 3. Agenda •Why responsible Generative AI? •What is an AI Engineer? •Building an AI application •Harmful content •Bias •Hallucinations •Conclusion
- 4. Why responsible Generative AI?
- 5. Pitfalls of Generative AI https://www.zdnet.com/article/6-major-risks-of-using-chatgpt-according-to-a-new-study/ https://www.forbes.com/sites/mollybohannon/2023/06/08/l awyer-used-chatgpt-in-court-and-cited-fake-cases-a-judge-is- considering-sanctions/ https://www.technologyreview.com/2019/01/21/137783/algorithms-criminal-justice-ai/
- 6. What is an AI Engineer?
- 7. ML Engineer vs AI Engineer AI Engineer ML Engineer • How can we effectively and efficiently train AI models? • How do we need to pre-process the data? • How can we deploy these models? • How can we build a service/application leveraging AI models? • How to ensure AI systems are adaptable and can learn over time? • How can we make these services produce desirable output? GPT-4 ChatGPT
- 8. Building an AI application
- 9. Minimal viable product AI Model Prompt Response
- 10. Architecture of a real-world AI application AI Model Prompt Response AI Application Filter Filter Prompt Engineering
- 12. Harmful content
- 13. Filtering input and output AI Model Prompt Response AI Application Filter Filter Prompt Engineering
- 14. Filter • Keywords • Business Rules • ML Classification Model
- 15. ML Model for Filtering
- 17. Filtering input and output AI Model Prompt Response AI Application Filter Filter Prompt Engineering
- 18. AI Models are biased
- 19. Reducing Bias?
- 20. Hmmm …
- 21. What happened here? “Image of a CEO” (Random) Prompt Engineering “Image of a CEO female” AI Model
- 22. But actually – this might be a legit tactic
- 23. We do it all the time when searching
- 27. Retrieving additional information AI Model Prompt Response AI Application Filter Filter Prompt Engineering
- 29. How does RAG work?
- 30. It can retrieve the most current information
- 31. Conclusion
- 32. AI Engineers shape GenAI applications … •Responsible AI: With great power comes great responsibility •AI Engineers build AI applications •In doing so, they make certain design decisions •These decisions shape the behaviour of the app
- 33. … and overcome some limitations of AI models •Filtering out undesired content •Use prompt engineering to steer the AI model •Retrieve additional information to overcome hallucinations
- 34. Questions? Connect with me on LinkedIn: https://www.linkedin.com/in/heikohotz/