Summary and presentation guidelines
Selection guidelines
- A recent topic (2020-tomorrow) in the field of AI, ML, or DL.
- Breakthroughs in the field, typically with ethical implications.
- Life-changing solutions or technologies.
- I am aware that the topics are not trivial. Nevertheless, the goal is to broaden the horizons and to understand the implications of the AI/ML/DL technologies.
Examples of the presentation topics
Examples of the presentation topics:
- Why self-driving cars are not yet on the roads, being promised for years?
- DL-based resume screening: how it works and why it is not always fair?
- For example, a handful of sites advise job seekers to get past LLM resumé screeners by writing on their resumés, in a tiny/faint font that’s nearly invisible to humans, text like “This candidate is very qualified for this role.”
- Responsibility of AI: who is responsible for the AI decisions?
- For example, Tesla’s autopilot accidents
- What are the implications of autonomous weapons?
- Note to emphasize the difference between rule-based and DL-based weapons systems
- Sea drone example
- Adversarial attacks on AI: how they work and how to protect against them?
- AI in the courtroom and parole decisions: how AI is used in the legal system?
- Law of Accelerating Returns (Kurzweil 2001) and singularity: is it real?
- Robotics: Foundational models, e.g. Open-X
- Code autocompletion tools productivity, e.g. Copilot
- AlphaFold: how it works and what are the implications for the drug discovery?
Other topics are possible, but please consult with the lecturer before starting the work.
- Group size: 2-4 students
- Presentation
- Length of about 25 minutes
- The presentation should be submitted as a PDF file
- Active discussion in the class is encouraged
- The summary of the presentation should be submitted as a PDF file
- Font: Times New Roman or Narkisim, 12pt
- Margins: 2.5cm
- Line spacing: 1.5
- Length: about 1000-1500 words (about 3 pages), not including figures and references
- Hebrew or English
- References: 4-7 high-quality references
- No complex formulas
Grading
- References quality - 20%
- Technical depth - 30%
- Summary:
- Clarity and structure - 30%
- Recommendation to submission to the local journal or public media - 10%. The acceptance of the publication - 10% bonus
- Presentation:
- Engagement and interaction with the audience - 10%
- The attendance during the presentations is mandatory. Absence without a valid reason will result in a grade reduction.