CrowdConf Brainstorm page

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Use this page to discuss the best practices reading we did not have time for in class, and brainstorm questions and topics that we might present as a class at the CrowdConf Future of Work Conference next week.

Crowdsourcing (Human Computing) is one of the most promising technologies, which has already been successfully in many different areas (Examples: X-Prize, 99designs, Amazon Mechanical Turk) and we believe has a huge potential for the future. It has the potential to significantly shape and change the way the labor market works. That said, it also creates challenges which need to be addressed and we are happy to have the opportunity to discuss with you, how technology could be leveraged to solve some of these challenges:

  • (1) Preserving Confidentiality in Complex Tasks. As the best practices document notes, some tasks require worker exposure to proprietary information. The Best Practices mention contracts as a way of dealing with this issues. Do we think that contractual relationships can assuage companies' fears of workers disclosing propriety information? Does the sheer volume (and potential geographical spread) of workers on a given task make enforcing such an agreement impossible?
    • Is there a way the technology can account for this problem?
    • Could the problem be solved potentially by drafting specific tasks to specific information, the disclosure of which would make the individual who divulged the info identifiable?
    • What are the costs of drafting such complex contracts?
  • (2) Feedback Mechanisms and Dispute Resolution. The Best Practices suggests that workers and companies use a feedback mechanism in good faith. The Best Practices document suggests that the crowd-sourcing platform should facilitate easy payment and provide a forum for dispute resolution.
    • Could the technology facilitate a cyber dispute-resolution forum? (What if the dispute-resolution process was, in turn, crowd-sourced?!).
    • Could the platform have a rating system that suggested a fair rate based on the type of tasks requested? There could be a "survey" that each employer fills out before submitting the task, which would calculate a suggested rate. Perhaps it could be based off of past rates, as tracked by the platform operator? (Does Amazon's "recommended" technology do this in a different form already?)
    • Is there any way to use technology to prevent abuse of feedback systems, or at least encourage people to use the feedback system in good faith?
    • Have platforms set up features to facilitate the creation of online worker unions? (See SECTION BELOW for more questions on Online Worker Unions)
  • (3) Disclosure. The anonymity of cyber-space and the possibility to divide a large project into a a large number of small tasks so that the ultimate product is unidentifiable raises a number of ethical concerns. Have companies, clients and platforms alike, explored setting up or mandating an ethical commission investigating these concerns? What about a voluntary code of conduct created and agreed on by the industry as a quality management system to prevent black sheep from ruining the reputation of the entire industry in case of misconduct and as a preemptive action towards governmental regulation? --> How do you prevent a private-run "Manhattan Project" implemented through crowdsourcing and sold to the highest bidder?



Follow-Up Questions / Further discussion points

  • Online Worker Unions. Crowdsourcing's success is dependent on finding ways to engage its labor pool, whether it be through offering money or gamesque points. However, as mentioned in class and in the best practices document, there are many ways for these laborers to become dissatisfied with their work, whether it be through a lack of transparency, stress, low wages, etc. Is there a potential for a crowdsourcing labor movement in response to these dissatisfactions? As an inherently digital workforce, these individuals' attempts to share discontents and act upon them are facilitated by their familiarity with and access to online communities. However, how far will this unity go? Do you feel that workers will only offer critiques of certain employers to others or could there be the formation of unions and similar entities in the crowdsourcing world?
  • Overlap of legal frameworks. Some countries have a state pension fund that is financed by a tax deducted from a worker's salary. How are these legal requirements adhered to in the realm of crowd-sourcing? How is the location/jurisdiction of the worker determined? If the company's location is chosen, how measures are taken for the worker to have access to that respective legal system?
  • Compensation. Crowdsourcing appears to rely on monetary compensation, a gamelike points system, or personal gratification to motivate people to participate in these tasks. Which of these compensation forms is the most effective in ensuring a large labor pool and the best results for employers? Which (if any) of these forms will be the most prominent system of compensation in the future and which do you think would be the most ideal compensation structure for crowdsourcing in the future?
  • Mobile Online Devices. Mobile and closed platforms with constant connection to the Internet have been supplanting sedentary workplaces in popularity.. How has crowdsourcing taken advantage of this change or has it struggled to do so? What advantages/challenges do these mobile devices offer workers, employees, and crowdsourcing agencies?
  • Recommendation System / Performance Tracking. It seems like sharing information about workers as suggested in the Best Practices document is a bit invasive for my taste, and perhaps something would have to be written into workers' contracts to explicitly allow this type of information sharing? (I'm not exactly what sure this law would implicate, but I seem to remember that when a potential employer calls a jobseeker's former employers, the employers can only share information that the person worked there, but can't reveal performance evaluations, etc.) Perhaps it's just me, but I'd feel more comfortable if companies enabled performance-tracking software, but didn't go so far as to share it with all other similar companies. (Question from Jenny)

(Sorry, forgot to log in, this is Erin) OK so to keep in mind what our goal is — we're supposed to put together some sort of agenda to talk about with the people who think about this day-in and day-out, and we have about half an hour? So it seems like we should try to focus in on a particularly compelling angle. The list above is good but can we prioritize? I really liked the point made in class last week that pointed out that if we can identify some sort of way for interesting technology to "fix" the "problems" that we see arising out of crowdsourcing, we'll have a much more receptive audience. Nothing jumps out at me from any particular section of the Best Practices document, but if we combine some of it maybe we can come up with something interesting?

  • Maybe combining some of the aspects of portability and reviews with the identity movement more generally would be interesting?
  • Frankly a lot of the best practices aren't super interesting in terms of the required technology — is there some other way to get them excited about a particular angle on something?
  • Is there a way to frame a problem that we're particularly concerned about that will speak to them? Don't mean to make this an "us-against-them" thing — but the way that technologists think about technology is a little different from the way that lawyers do, so we want to be able to frame the issue in a way that will resonate with the audience...
    • What about praising the technology (maybe have a few specific examples), but then asking them if they've met any resistance from, or thought about, any of the potential actors who may block or alter the technology's use? Have you (the technologist) talked with local/state/federal government? Have you discussed potential roadblocks with companies that will implement the technology?


Jenny here: I've been reading some blog posts on crowdsourcing, and one comment from a scientist (found in the comments section here: http://money.usnews.com/money/blogs/outside-voices-small-business/2009/01/27/using-social-media-and-crowd-sourcing-for-quick-and-simple-market-research ) got me thinking that scientific research and development could suffer if companies move from hiring a dedicated team of scientists to farming all of their scientific problems out to a crowdsourcing lottery payment system (ie, first one to do this gets all of this money; the others get nothing). Honestly, worst case scenario, we'd have even fewer people going into sophisticated scientific fields than we do now, because there wouldn't be any guarantee of a stable living, and I wonder if this could really hinder the development of solutions to scientific problems or if it would limit the scientific fields to scientists who are business-savvy enough to be connected to venture capitalists, etc. Either way, the outcome could be scary.

I'd be interested to hear from crowdsourcing experts about how they think crowdsourcing scientific problems affects the quality of scientific research, and if there could be any safeguards implemented to prevent the aforementioned problems from occurring (ie -- could the crowdsourcing community fund a dedicated pool of scientists, with extra prizes going to those who successfully complete R&D tasks, or would this go against the very core of the crowdsourcing movement?)

Case Study: oDesk (Rene)

  • I have used oDesk a lot of times over the summer to outsource smaller programming projects for my startup to developers, mainly in India and Southeast Asia. For those who haven't used oDesk, you post a job with a budget, oDesk workers apply for the job, you can interview them and then hire one; a small portion of the overall payment might be upfront, the rest is paid at completion of the project at discretion of the employer. oDesk has standard terms (NDA, etc.) to facilitate the transactions, but I have asked the developers I hired to sign additional documentation. The biggest issue is quality control; despite the fact that there is a rating system, it is quite difficult to evaluate whether someone is able to get a certain job done or not. I really like Jenny's question around recommendation systems / quality control as and extension of point (2) above and would like to hear what technologist have in mind to address this important challenge.
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