## Course Overview
* Audience: graduate students (or beyond) already engaged in research
- Not: undergrads
* General Goal: practice thinking about research, but not navel gazing
- No one-size-fits-all solution, but many methods
- Make explicit a lot of implicit understanding and know-how
* Concrete Goal: explore the boundaries of some research sub-area of interest to you
- Or even define a new sub-area
* Non-goals
- Not: to identify research that will maximize research paper output
- Not: to preordain a career path, or to say that one career path is better than others
* Diverse readings
- Across computer science: AI, cryptography, networking, programming languages, etc.
- Outside of computer science: philosophy, math, sociology, history, etc.
* Challenging
- Conceptually: will challenge you to think in new ways
- Practically: a consistent (not bursty) moderately-high reading and writing load
* I want to learn more from you than you learn from me
- Also: I'd like you to learn more from each other than you learn from me
- But most importantly: I'd like you to learn the most by yourself through the work
## Perspective
* Who am I to even be teaching this?
- I am not a senior faculty member
- I have an unusual background and set of interests
* I could not have taught this course even a few years ago
- My perspectives have changed
- My interests have changed
- The *world* has changed (most importantly)
* Missing subtitle of course: Crafting a Research Agenda in the post-X era
- where X = modern?
- where X = truth?
- where X = science?
- where X = ???
## No Method
* There is no one method to crafting a research agenda
* Don't believe everything ***you*** think
- Also don't believe everything you read, even from famous / eminent people
- But don't reject everything either
* Broken notion: craft a research agenda (or software project, or science experiment)
- Then do it
* New notion: craft a research agenda and then...
- You might throw out the whole agenda
- You might realize its premises were wrong, or goals were wrong, or techniques are ill-suited
- This is fine, and expected
* Why bother crafting an agenda, then?
- The *process* of crafting the agenda is key
- Eisenhower: "plans are worthless but planning is everything"
- Your agenda can frame a research space, influence others, bring in collaborators and resources
- It's ok if the document doesn't hold up with 20/20 hindsight; nothing does
* The public agenda and private agenda will be different
- Public agenda is what you might write in a vision paper
* Private agenda is a meta-agenda, with thoughts on "navigation"
- Goal is more of "how to navigate" rather than "charting the path from A to B"
- "Discover the road as you walk it"; you may not end up where you planned
- What are possible blockers/hurdles to this work? How do you test them, move past them?
- What are avenues to explore at each potential research crossroads?
- What are multiple hypotheses/ideas to consider for each sub-problem?
- What happens when something inevitably goes wrong?
- What are some possible unknown unknowns; how might they affect problem framing, the work process, the data sets used, etc.?
## "Normal" vs. "Revolutionary" Science
* Our goal is to go beyond "normal" science
- Aspire to "revolutionary" science
- However, "normal" science is needed for "revolutionary" science
* "Paradigm shifts" and "revolutionary" science are not solely major changes
- Both happen at many scales
- Impossible to categorize all research as strictly "normal" or "revolutionary"
* You will get plenty of practice doing "normal" science as a PhD student
- Here we aim to discuss something bigger
* Research trends in CS are like economic bubbles
- [Where is your research area in this chart?](https://en.wikipedia.org/wiki/Jean-Paul_Rodrigue#/media/File:Stages_of_a_bubble.png)
* The world _demands_ of us something beyond "normal" science at this very not-normal time
## Systems and Meta-systemicity
* Understanding research from a systems perspective
- Not: computer systems, but: conceptual and rational systems
- And moving beyond specific systems to a meta-systematic perspective
* We are told we operate in a world of rationality as researchers
- A fair bit of our discussion will be on why this is often not the case
* Research sometimes employs/requires meta-systematic thinking
- Thinking this way takes practice
* There is no clear line between systematic and meta-systematic thinking
- Lots of shades of gray, another theme we will discuss
- Key is to not get stuck in one way of thinking
## Doing, not just thinking, in a Community of Practice
* How to do good research can't be learned from a book
- Nor is thinking sufficient
- Nor is dreaming about grand results sufficient
- You must ***do*** it, *with others*; lots of hard work
- Not unique to research: many things are this way
* Example: Computational Agroecology
- I now do a fair amount of research on applying computing to sustainable agriculture
- I was trained in networking, but don't use any of it here
- I never formally studied the ostensible background topics: agriculture, sustainability, AI, etc.
- I learned the agriculture and sustainabiilty perspectives by doing, embedded in a community of practice (urban agriculturalists, mostly hobbyists but some professionals)
- I brought my own perspectives and techniques to bear
* You, and your work, get better through those around you
- Cultivate your community
## Advancement at the Limits of Understanding
* Just "doing" is insufficient; not all work is explicit or conscious
- Combination of conscious and subconscious work required
* Example: Wagner's cryptanalysis in the hot tub
* Example: ideas in the shower
* Easy to have false insights if you don't put in the work
- No shortcuts
* Hard to have insights without allowing room for the subconscious
- Fixating on rational, conscious methods is limiting
## Activities for the Semester, and Beyond
* Read widely, not just in the research literature
- The literature is a lagging indicator of where research is, sometimes as much as 4 years out of date (why?)
- You don't want to just read the "best" work
- Also: read what innovative researchers are themselves reading, so go find out
- Also: read very broadly, because you never know what might spark ideas
* Don't just read, talk with people
- The most cutting edge ideas are difficult to articulate in writing
- New ideas can come out through discussion rather than written dialogue
* Read technical *and* non-technical writing
- Read technical to learn new techniques for problem solving
- Read non-technical to consider new problems or problem framings or contexts
* Don't rely upon others to lay out a vision for you
- Point: You'll just be building their vision
- Counterpoint: don't just ignore everyone and do your own thing
- Synthesis: build a community of researchers around a common vision
* Take a lot of notes, not just of ideas but also of what you read
- Never know what ideas might connect
## Course Mechanics
* Create a new folder in the shared Google Drive folder in the format "Full Name -- CSCI 699"
- In this folder you'll put all your materials
* The first document you should now create in your folder is "Full Name -- CSCI 699 -- Responses"
- Clone the template doc and put it in your folder
- This is where you'll be writing reading responses, newest on top
- For each class date, should be heading for each class (notes taken in class discussion) and separate heading for reading responses
## Five Whys
* Ask why five times to try to get to root causes
- We'll apply this later
## Activity
* In groups of 4-5, discuss what "research" is. Do not look it up online, in a dictionary, etc.
- What is research *to you* ***in your experience***? (Not what you've been told it is, or read that it is, or think that it should be.)
- Ask each of the following five times about research: what? who? where? when? why? how?
- Take notes in your new document