In the name of supporting people actually doing stuff:

• Scott’s IRB Nightmare comes from the circumstance of polling taking place within the context of privileged patient-provider interaction, which is covered by HIPAA, which requires somewhat stringent data handling. If you are not a doctor, and you're not asking your patients in the hospital, this does not apply to you.
• Yes, you are allowed to "just go out and ask a whole bunch of people stuff". People can, actually, give away whatever information they feel compelled to do so. People are allowed to enter (mostly) any trade. People are free to do stuff.
• For people <18, you need parental consent.
• There are, like, hundreds of tools to do this -both finding people, and nailing the questions. Google Survey samples currently best across US (specifically, it had predicted the 2016 election results successfully). This is good, if you have a specific hypothesis, that you want to ask from 1000++ people.
• The more quantitative you get, the less signal it carries, at higher precision. Survey & stats criticism generally comes from attempting to determine "things about humanity in general", which is also (somewhat) useful, but requires N > very large, and _very_ methodical sampling / experiment formulating / etc.
• Generate qualitatively, validate quantitatively. Vast majority of effort goes into actually locating the hypothesis. Before building a research thesis in your room, go out and do the simplest thing first. Talk with people, like, in-person. There's a learning curve prior to being able to formulate meaningful hypotheses.
• Ask yourself, what rent does answer to a specific question pays. What does it say of reality if it turns out to be A vs B? How does that interact with neighbouring things?
• And: what, specifically, do you wish to achieve here? Specifically, some qualitative answers to some of the questions above from Bay Area people, along with some synthesis, would be extremely informative (to me at least).
• A good starting point for this might be cultural anthropology, but instead of getting a book, here's an MVP: get a tape recorder,ask 50 of your friends the questions above, then put answers into a spreadsheet, and a synthesis into an lw post. This is extremely informative for eg measuring local shifts in the overton window, finding common ground (and grounds shifting); and is sorely missing.
• Why in-person? People who persistently fill out textareas on web pages are heavily biased in income, and mental illnesses; generally, people don't do that. Being in-person, you're raising the interview against personal reputation, which bridges the addressibility gap, and makes a much wider variety of people's voices accessible.
• To avoid pet-theory issue: Ask open-ended questions (eg the relating to job/ambition ones above are good). Don't lead, capture the raw stuff
• Do this simple thing first, prior to embarking on specific hypothesis formulation; and post the results!

For studies in the US, see this flowchart.

If the human subjects research isn't supported by the US Department of Health and Human Services, and isn't supported by an institution that holds an FWA, then the research isn't covered by regulations on human subjects research.

At a cognitive science lab at Stanford I worked in, it was quite common to run studies using Mechanical Turk.

Informal surveys are done literally all the time, by university undergrads, sensationalist news organizations, political organizations, businesses, etc.

If you want to publish somewhere, you'll need to follow their rules. If you're using or establishing some sort of business or medical relationship with those surveyed, there are restrictions on how you can do that. Targeting or collecting data on under-18 humans in many jurisdictions is restricted, and I don't know what it takes. If you're calling or texting people, there are rules there too. The rules seem to be ignored a lot of the time, especially for informal one-time small-scale uses.

The bigger problem I see is validity of study, and representative-ness of sample. The sample topics you give all seem to be about counting or quantifying something within a population. Most of your work will be in defining the population you're trying to measure and figuring out how to get a wide-ranging evenly-distributed sample of responses within that population.

The other "most" of your work will be in figuring out how to get the data that actually tells you anything. There's a lot of individual variance in the topics given, and a lot of ambiguity in what results of any concrete test would show.