Winter Milestone 7
Due date (PST): 8:00 pm 28th Feb 2016 for submission, 12 pm 29th Feb 2016 for peer-evaluation.
This week, we will refine methods and systems proposed last week further:
- Youtube link of the meeting today: watch
- Winter Meeting 7 slideshow: coming soon...
- 1 Task Feed
- 2 Task Authoring
- 3 Open Gov and Design
- 4 Research Engineering
- 5 Submission
We have 3 goals for this week:
- Refining our system proposal. Please make comments directly on the google doc. We want to address any holes in our incentive compatible structure and make any concrete decisions regarding things like the # of workers that report time spent on a task before we start displaying it on the taskfeed.
- Design tweaks in order to capture and display the new information we need. This includes a task element to record the time a worker spent and small modifications to the taskfeed to display the rejection rate and effective wage. Please post low-fi or high-fi mocks to the #taskfeed channel.
- Engineering plan of action and division of work.
Michael's summary from last week's hangout:
We have aligned on a specific vision for a smarter, more informative task feed by incentivizing workers and requesters to share information they might not otherwise share, or not share accurately. There are three main components to this:
- Reputation. It shows more accurate reputation information, by influencing which workers get your future tasks (if you're a requester), and which requesters show up at the top of your feed (if you're a worker). The individual incentive: you get better workers, or better requesters, by reporting honestly. The global win: the reputation scores more directly reflect individual incentives. This is Boomerang as previously described.
- Hourly rate. The goal is to for the task feed to show an estimate of how much you'd make with each task (e.g., $9/hr). To do so, it asks workers who just completed the task to estimate how long it took them to do it. The individual incentive: it uses the worker's responses to build a model to estimate their effective hourly rate for all the other tasks in the marketplace. The global win: those workers' responses are used to produce estimates shown to all other workers.
- Rejection information. It shows the % of tasks for workers like you that get rejected, by influencing which workers get the requesters' future tasks based on rejection information. The individual incentive: the more of a worker's tasks a requester accepts, the earlier they get access to their future tasks. (This is a smaller effect than the reputation feedback above, but does have an impact.) This prevents "accept all submissions" degenerate behavior. The global win: workers can now see the % of tasks accepted for workers like them.
Boomerang: Incentivizing Information Disclosure in Paid Crowdsourcing Platforms
There is a massive amount of information necessary for a healthy crowdsourcing marketplace — for example accurate reputation ratings, skill tags on tasks, and hourly wage estimates for tasks — that is privately held by individuals, but rarely shared. We introduce Boomerang, an interactive task feed for a crowdsourcing marketplace, that incentivizes accurate sharing of this information by making the information directly impact their future tasks or workers. Requesters' ratings of workers, and their skill classifications of tasks, are used to give early access to workers who that requester rates highly and who are experts in that skill, so giving a high rating to a mediocre worker dooms the requester to more mediocre work from that worker. Workers' ratings of requesters are used to rank their high-rated requesters at the top of the task feed, and their estimates of active work time are used to estimate their hourly wage on other tasks on the platform.
The task feed hangouts from last week:
- Youtube link of the task feed meeting 1: watch
- Youtube link of the task feed meeting 2: watch
- Youtube link of the task feed meeting 3: [watch]
Michael's synthesized needs:
- to find new tasks that will maximize income (reduce uncertainty in payment, rejection, maximize certainty in what will be asked of me and how quickly I can do it)
- to find new tasks that fit my expertise profile
- to refind old requesters' new tasks, since I know I like them
- to identify tasks I can do on my own time
- to learn new skills
Our goal for this week is to converge on a single well-defined methods section. By the end of the week, we want to produce a very specific proposal detailing exactly what needs to be built/done in order to embark on our study. You all wrote a bunch of great proposals last week, and we want to extract the best ideas so that we can synthesize a single system design.
By Wednesday morning 9 am PST, read each of last week’s submissions on Meteor and write comments in an “I like / I wish” style. For example, “I like how your proposal explores at the motivation of workers to help requesters author their tasks” and “I wish your design accounted for workers with different level of experience.” Please leave your comments on the task-author ideas submitted, last week; via comments section on the meteor website.
On Wednesday from 8pm-10pm PST, @michaelbernstein will lead a hangout to synthesize these ideas and outline a single proposal. We will then take this outline and fill in any missing details during the rest of the week and create a single well-written systems section. RSVP here or watch here.
We will now be writing up a single Task Authoring Methods Proposal together here for the conference submission. Please pick a section (or create your own) in the doc below and start adding content!
Volunteer to be a requester
The taskauthoring folks are looking for a couple volunteers to create some tasks for three datasets we have. We give you the task and some example input/outputs, and you try to write a task interface in Mechanical Turk that will get workers to produce the right answers.
If you are interested, please ping @catherine.mullings
Open Gov and Design
Check out this week's meeting, and based on the open gov discussions here - create a mock, minimal design within Daemo. Think about questions like: how does it work as a system? how it would fit in Daemo? Like, walk us through. I’m a new worker on Daemo. What do I do? Am I already part of a guild? How do I get into one? How do I get work once I’m in one? What if the requester doesn’t like what I do? And how does all this solve the reputation problem?
You can use balsamic to give shape to your ideas. Design folks, come join and help move this effort forward.
This weeks main issues: #77 (this is a pretty big one), #660, #509
announce in #research-engineering that you are working on a particular issue and please let the others know about the progress of the issues you are working on (so that we don't do duplicate work). You are encouraged to work together.
For any questions ping @aginzberg, @dmorina, and @shirish.goyal on Slack #research-engineering
Create a Wiki Page for your Team's Submission (Open Gov and Design)
Create a wiki page with Balsamic designs and descriptions, for the Open Gov and Design part. If you have never created a wiki page before, please see this or watch this. Once you're done, post here: http://crowdresearch.meteor.com/category/open-gov
Comment I like/I wish for your Team's Submission (Task Authoring and Task Feed)
By Wednesday morning 9 am, finish commenting for task feed; by Wednesday evening 8 pm, finish commenting for task authoring. Make these comments on the meteor website.