Homework 3 (Spring 2019)
Answer the following prompts in a maximum of 10 pages (excluding references) in JDF format. Any content beyond 10 pages will not be considered for a grade. 10 pages is a maximum, not a target; our recommended per-section lengths intentionally add to less than 10 pages. This length is intentionally set expecting that your submission may include diagrams, drawings, pictures, etc. These should be incorporated into the body of the paper.
If you would like to include additional information beyond the word limit, you may include it in clearly-marked appendices. These materials will not be used in grading your assignment, but they may help you get better feedback from your classmates and grader.
Question 1: ~2 pages
In the lectures, we use two analogies to discuss analogical reasoning: the analogy between solar systems and atoms, and the analogy between storming a castle and zapping tumors.
Another common example of analogical reasoning involves comparing the inner workings of brains, including their neurons and action potentials, with the inner workings of ant hills, including their tunnels and ants.
Research this analogy a bit: Googling “human brains and ant hills” will get you enough results to go on. Then, develop a simple model of each of these systems. Then, discuss what analogically may transfer from one model to the other: at what level of abstraction can we draw an analogy between ant hills and human brains? Finally, briefly comment philosophically on how far that analogy can be taken: is an anthill conscious? Why or why not?
Question 2: ~2 pages
Peruse the papers from the first conference on AI, Ethics, and Society. Select two papers (but do not select Bobbie Eicher’s paper; we will discuss that separately). First, summarize the first paper. Note the ethical questions that the paper raises, the methodology it uses to explore them, and the conclusions at which it arrives. Then, determine with which of the conclusions you agree and disagree, and justify your decision. Finally, brainstorm the follow-up ethical questions that should be asked, and the methodologies that might be used to explore them.
Then, repeat those steps for the second paper you selected.
Question 3: ~2 pages
Below is a partial list of academic conferences related to artificial intelligence. Select two papers each from a different conference. Both papers should be recent (last three years or last three meetings of that conference).
First, summarize the first paper. Note the major contributions of the work. Explain what you found interesting about the paper. Then, evaluate the potential weaknesses of the study: what are possible other explanations for its findings, or what other methodologies or experiments should be employed to further evaluate the work? Finally, hypothesize what should come next from that research.
Then, repeat the steps above for the second paper.
Here is the list of conferences we recommend choosing from. If you find another peer-reviewed AI-related conference, you may use a paper from it instead. In most cases, you can find either the actual proceedings from the conference web site, or you can find a list of paper titles. Searching those paper titles on Google Scholar will usually take you to the full paper.
- Association for the Advancement of Artificial Intelligence (AAAI): 2018, 2017, 2016
- Innovative Applications of Artificial Intelligence (IAAI): 2018, 2017, 2016
- AI in Education (AIEd): 2018, 2017, 2015
- Intelligent User Interfaces (IUI): 2018, 2017, 2016
- Artificial Intelligence and Interactive Digital Entertainment (AIIDE): 2018, 2017, 2016
- International AAAI Conference on Web and Social Media (ICWSM): 2018, 2017, 2016
- AAAI Conference on Human Computation and Crowdsourcing (HCOMP): 2018, 2017, 2016
- Intelligent Tutoring Systems (ITS): 2018, 2016, 2014
- Artificial Intelligence in Medicine (AIME): 2017, 2015, 2013
- Principles Knowledge Representation & Reasoning (KRR): 2018, 2016, 2014
- Intelligent Virtual Agents (IVA): 2018, 2017, 2016
- Association for Computational Linguistics (ACL): 2018, 2017, 2016
- Neural Information Processing Systems (NeurIPS): 2018, 2017, 2016
Question 4: ~2 pages
Over the last several weeks, you’ve completed several questions and projects related to artificial intelligence. One of our goals for this class is to give you room to explore the areas of AI that are most interesting to you as well. Regardless of whether we accomplished that, there are probably additional topics you may have wanted to explore or questions you think would be worth answering.
Toward that end, first brainstorm what you believe this class should ask in the future. First, write three questions you think would be worth including in future assignments. A minimum of one of these questions should be closely tied to the course’s lecture material, like HW1-Q1, HW2-Q1, HW2-Q2, and HW3-Q1. A minimum of one of these questions should touch on ethics in AI, like HW1-Q2, HW1-Q3, HW2-Q3, and HW3-Q2. The third question can be whatever you want; it could be similar to HW1-Q4, HW2-Q4, or HW3-Q3, or it could be completely different. Focus especially on what kinds of questions you would have liked to see your classmates answer.
Second, brainstorm a potential new project track for this class. A project track would be three projects in the same general topic area. They could build on each other explicitly, like the current projects, or they could be more spiritually related. We intended this semester, for example, to have an NLP Track, which would have three projects: one on sentiment analysis of course reviews, one on plagiarism detection, and one on designing a chatbot. Name the track, and describe what students would do for each project in the track. Note especially that we prefer projects that have some sort of objective measurement to them, like the number of Raven’s problems answered correctly or the number of plagiarized assignments correctly identified.
Note that while an ulterior motive behind this question is feedback and ideas for us to improve the course in the future, we are primarily interested in how this class has equipped you to look at the field of AI as a whole through an analytical lens. We’d like to know that you cannot just answer interesting questions about AI, but also ask them yourself.
Complete your assignment using JDF, then save your submission as a PDF. Assignments should be submitted to the corresponding assignment submission page in Canvas. You should submit a single PDF for this assignment. This PDF will be ported over to Peer Feedback for peer review by your classmates. If your assignment involves things (like videos, working prototypes, etc.) that cannot be provided in PDF, you should provide them separately (through OneDrive, Google Drive, Dropbox, etc.) and submit a PDF that links to or otherwise describes how to access that material.
This is an individual assignment. All work you submit should be your own. Make sure to cite any sources you reference, and use quotes and in-line citations to mark any direct quotes.
Late work is not accepted without advanced agreement except in cases of medical or family emergencies. In the case of such an emergency, please contact the Dean of Students.
Your assignment will be graded on a 20-point scale coinciding with a rubric designed to mirror the question structure. Make sure to answer every question posted by the prompt. Pay special attention to bolded words and question marks in the question text.
After submission, your assignment will be ported to Peer Feedback for review by your classmates. Grading is not the primary function of this peer review process; the primary function is simply to give you the opportunity to read and comment on your classmates’ ideas, and receive additional feedback on your own. All grades will come from the graders alone.
You receive 1.5 participation points for completing a peer review by the end of the day Thursday; 1.0 for completing a peer review by the end of the day Sunday; and 0.5 for completing it after Sunday but before the end of the semester. For more details, see the participation policy.