CTDL1901 Science & Technology Written Assignment Video Guide

Neel Bagai
27 Oct 202406:22

Summary

TLDRThis video provides guidance on approaching the CTDL 1901 Science and Technology Written Assignment. The speaker encourages students to explore beyond the provided topics, conduct independent research, and consider both successful and failed cases in AI development. Using AI advancements as an example, the video highlights the importance of critical thinking and awareness of cognitive biases, such as survivorship bias. The speaker also suggests applying various biases to build a compelling argument and urges students to stay updated on emerging technologies. Overall, it stresses the value of curiosity and comprehensive research in crafting a strong assignment.

Takeaways

  • πŸ˜€ Explore beyond the assignment topics: While the assignment provides a starting point, you're encouraged to research and explore topics related to your personal interests in science and technology.
  • πŸ˜€ The thought process for the science and technology assignment is similar to that of the business assignment but focuses more on technological advancements.
  • πŸ˜€ Research is crucial: Use the source article as a starting point, but go out and find different perspectives and information to enrich your assignment.
  • πŸ˜€ AI development has made significant strides, especially in areas like generative AI for text and images, but still faces challenges in areas like video generation.
  • πŸ˜€ Video generation models, such as OpenAI's and Chinese company QuShow's offerings, still have limitations and underperform in many cases.
  • πŸ˜€ Survivorship bias in AI development: People often focus on successful AI projects like ChatGPT while overlooking the many failures that happened along the way.
  • πŸ˜€ Real-world examples of AI failures: Microsoft's Tay chatbot was shut down after 16 hours due to offensive behavior, and Google's Project Mina was shelved after failure.
  • πŸ˜€ AI failures provide valuable lessons: Despite their shortcomings, failed projects contribute to the improvement and success of future models.
  • πŸ˜€ Cognitive biases such as the representativeness heuristic and the framing effect can influence our perception of AI advancements.
  • πŸ˜€ Independent research and knowledge exploration are important not only for completing assignments but also for developing skills beneficial for future employment in a rapidly evolving world.

Q & A

  • What is the main similarity between the CTDL 1901 Science and Technology written assignment and the Business assignment?

    -The main similarity is the thought process involved in both assignments, where you are encouraged to explore topics of interest through independent research, going beyond the provided sources.

  • What is the key difference between the Science and Technology written assignment and the Business assignment?

    -The key difference is the content covered. In the Science and Technology assignment, the focus is on scientific and technological topics, whereas the Business assignment revolves around business-related subjects.

  • What should be the approach to choosing a topic for the Science and Technology assignment?

    -While the source article on the canvas is a good starting point, you are encouraged to explore topics beyond it based on your own interests. Researching new technologies and developments will enrich your understanding.

  • What is survivorship bias, and how is it relevant to the development of AI models?

    -Survivorship bias is the tendency to focus on the successful cases (like GPT and Claude) while overlooking the failures. This bias is common in AI development, where many AI models fail but only the successful ones are widely discussed.

  • Can you provide examples of AI failures that demonstrate survivorship bias?

    -Examples include Microsoft's Tay chatbot, which was shut down within 16 hours due to inappropriate behavior learned from users, and Google's Project Mina, which was shelved despite initial development.

  • How does the failure of AI models contribute to the development of future models?

    -Failures like Project Mina have contributed valuable lessons that informed the development of more successful AI models, such as Google's Gemma and Gemini, by highlighting what not to do.

  • Why is it important to consider failed AI models when discussing AI technology?

    -Considering failures provides a more balanced perspective on AI technology. It helps us understand the challenges, limitations, and reasons behind why certain AI models don't succeed, rather than just focusing on successful cases.

  • What other cognitive biases and heuristics could be explored in the Science and Technology assignment?

    -Besides survivorship bias, other cognitive biases and heuristics that could be explored include the representativeness heuristic, the framing effect, and others that influence our judgment of technologies.

  • How can researching new technologies benefit students in the Science and Technology field?

    -Researching new technologies helps students develop critical thinking and technical knowledge, which are valuable for future career opportunities, especially in a rapidly changing technological landscape.

  • What is the overall recommendation for students working on the Science and Technology written assignment?

    -Students should go beyond the materials provided on the course canvas, conducting their own research, and critically engaging with both successes and failures in technology to form a well-rounded argument.

Outlines

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Transcripts

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AI ModelsTechnology AssignmentGenerative AISurvivorship BiasFailure ExamplesResearch TipsScience TopicsAI FailuresInnovation TrendsTech Development