Artificial Intelligence (AI) is a technology that has been in development and research for almost 30 years. Due to the release of generative AI tools like ChatGPT and DALL-E more people and businesses are now seeing the potential but the space can seem overwhelming.
In our recent Generative AI Masterclass, R. J. Talyor, Operating Partner at High Alpha, was joined by experts in the history, ethics, and implementation of AI to discuss how this technology can be used and the complications that can arise.
The History of Generative AI
David Crandall holds the distinguished title of Luddy Professor of Computer Science from Indiana University's Luddy School of Informatics, Computing, and Engineering. His prolific research is concentrated on computer vision, data mining, image processing, and machine learning. David started us off with a fascinating first-person perspective on how AI was initially developed and researched, the resurgence of using neural networks, and the deep learning revolution.
He dove into the many rapid evolutions of AI, from natural language to object tracking to visual captioning and many more. While AI capabilities are impressive, Dr. Crandall noted many failures within existing AI models, such as providing inaccurate information - is it a church or a ladybug in the photo? - or tracking the wrong object. Context is a complicated problem researchers are working to generate within these models, and often the data sets used open a pandora's box of exciting leaps forward and imperfect biases.
🤖 Key Takeaway: Generative AI is becoming closer to machine learning, and while impressive, it has its flaws and works best when used alongside humans.
The Ethics of Generative AI
These biases lead to possible legality issues and bring in the question of ethics. Fred Gate, J.D. spoke to the group on his observations of how ethics and the law will be applied to AI tools and what he has seen from a few cases that have already been brought to light.Â
- TechCrunch: The current legal cases against generative AI are just the beginning
- ArsTechnica: Stable Diffusion copyright lawsuits could be a legal earthquake for AI
- Vox: The AI boom is here, and so are the lawsuits
He noted that when technology is deployed ahead of when it is ready, it uses those imperfect and biased data sets, which have led to discrimination in some of the outcomes and processes of these tools. His experience and observations have shown him that businesses need to understand being first to market aren’t always the best, and these tools work within the system, so thinking of the process thoroughly can combat some of those biases while in development.Â
⚖️ Key Takeaway: The law wasn’t created with AI in mind but don’t panic.
Generative AI in Products
The question of ethics in AI is evolving just like the technology itself. The more it is used and implemented, the more consequences will arise. R.J. Taylor held an engaging panel discussion with Tyler Hill of Shutterstock, Zach Koch of Fixie.ai, and Charlene Tay of The Engineered Innovation Group to discuss using generative AI in products to round out the class. These individuals have implemented AI tools in their businesses and understand firsthand how AI tools transform business operations. Their insightful discussion rounded out everything taught in the masterclass.Â
🤔Key Takeaway: Look outside of the box to find applications of AI that help you and your business be more efficient.
From conception to development to implementation, generative AI is changing how we do business. The masterclass was an excellent introduction to understanding how generative AI was created, the issues it still has to overcome, and the innovative products made from it.