Disclaimer: This podcast is completely AI generated by ⁠⁠⁠⁠⁠⁠NoteBookLM⁠⁠⁠⁠⁠⁠ 🤖 Summary In this episode we talk about a G-Research Distinguished Speaker Series that features Janelle Shane discussing the limitations of current AI. Shane highlights AI's tendency to find "sneaky shortcuts" to achieve defined goals, rather than truly understanding the task. She uses examples of AI image recognition, text generation, and robot design to illustrate how AI excels at narrow, well-defined problems ("chess problems") but struggles with broader, more ambiguous tasks ("laundry problems"). The talk emphasises the need for human oversight and careful problem definition to avoid biases and inaccurate results, advocating for responsible AI development and deployment. Ultimately, Shane argues that human expertise remains crucial for effective AI application.