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Surviving crowdsourcing
 

Surviving crowdsourcing

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Community, collaborative, social. Will the language industry survive crowdsourcing? ...

Community, collaborative, social. Will the language industry survive crowdsourcing?
Presentation for the XXXIV IALB-ASTTI Conference "The World in Crisis – And the Language Industry?"
Geneva, 13-14 November 2009

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  • Full Name Full Name Comment goes here.
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  • Great paper Luigi! Is it possible to get a printable copy? I would like to have a bunch of PhD students in translation read that paper in a class where I will lecture, but it's pretty cumbersome to read on slideshare.
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  • My dangerous idea is that crowdsourcing could be accomplished by a lottery. See my Knol article entitled: Keystroke Lotteries: Typing for Tickets:

    http://knol.google.com/k/bruce-swanson/keystroke-lotteries-typing-for-tickets/2pwl4dkclsj3z/2?hd=ns#
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    Surviving crowdsourcing Surviving crowdsourcing Presentation Transcript

    • Community, collaborative, social: will the language industry survive crowdsourcing? Luigi Muzii
    • Thinking
      • We cannot solve problems by using the same kind of thinking we used when we created them.
    • Reminds you of anything?
    • The approach to crises
      • Conservative
        • Typical of the language services industry
          • Any change is a major change
          • Cut cost and reduce staff
          • Do more with less
      • Innovative
        • In products
          • Translation is a cost
            • VAS
        • In processes
          • Standards and interchange to build productive solutions
          • Specialized communities
          • Made simpler, lean, and parallel
    • GILT industry mantra
      • Cheaper, Faster, Better
        • Doing more with less costs more
          • Technology to increase volume and speed
            • Not enough good people in translation
              • Poor or no quality increase
              • Customer satisfaction decrease
    • Translation industry axioms
      • Quality
        • Fewer translators produce more consistent output
      • Assets
        • Are TM’s and glossaries assets? Have they ever been? Will they?
        • Assets carry some value
          • How can TM’s and glossaries be priced? Are they?
    • Main concerns
      • LSP’s
        • Ongoing commoditization
        • More free translation
      • ATA’s*
        • Global outsourcing
        • Crowdsourcing
        • Economic downturn
        • Certification by other entities
        • Machine translation
        • Increased competition for revenue streams
        • International expansion
        • Licensure
      * ATA Board’s globalization threats reported in the ATA Chronicle issue of June, 2009 by President Jiri Stejskal
    • Vendor management
      • The largest cost budget item
        • Hundreds or thousands of vendors
          • Technology & staff
        • Vendor quality assessment
          • Several vendor manager
            • Rotation for healthy relationships
    • Crowdsourcing
      • The act of taking a task traditionally performed by an employee or contractor, and outsourcing it to an undefined, generally large group of people or community in the form of an open call.
        • Jeff Howe
        • The Rise of Crowdsourcing, June 2006
    • Crowdsourcing in a nutshell
      • The (latent) wisdom of (online) crowds
        • Only the best professionals are supposed to answer call and team up
          • A passionate and motivated force of volunteers is needed
            • The work is not supposed to be done for free
    • The crowdsourcing process in eight steps Image by Daren C. Brabham
    • Reasons for crowdsourcing
      • To reach totally new markets
      • To better serve markets that are currently under-served
      • To increase the value of global brands by further engaging users
    • Famous crowdsourcers
    • Typical practice Customer MLV SLV 1 Language 1, region 1 TSP n Language n , region n SLV n Language n , region n TSP 1 Language n , region n TSP n Language 1, region 1 TSP 1 Language 1, region 1
    • Community, crowdsourced, and collaborative translation (CT3)
      • CT3 projects typically done on purpose-built software
        • Developing those systems is expensive
          • Effort could not be worth the investment
        • Community (social) translation not the same as crowdsourced translation
          • Non-profit translations
            • Made for the benefit of everyone
    • The problem with translators
      • Building a software infrastructure vs. paying translators
        • The translators’ skills are not worth spending
          • Amateurs collaborate to avoid “weird” translations
    • Crowdsourced translation
      • Multiple people in a collaborative workspace
        • Writing
          • Supply content to be translated
        • Terminology
          • Provide a terminology list up front
        • Translation
          • Stay involved in community interaction
          • Communicate everything upwards
          • Monitor progress
        • Review/Editing
          • Leverage group voting mechanisms for accuracy
            • Recognize and reward achievement
    • The end of TEP & fordism
      • Reduce, reuse, recycle
        • Reduce overhead
          • Eliminate duplicate and unproductive work
        • Reuse terminology and translation
          • Centralized TM’s and dictionaries
        • Recycle TM matches
          • Machine translation
      • Time adds up
        • Micro chunks
          • Efficient workload
            • Negligible individual time
        • No need for reviewers
          • X-checks to deliver high-quality translations
            • No further “improvements”
    • Crowdsourcing vs. Machine Translation according to Mojofiti
      • Crowdsourcing
        • Advantages
          • Free, abundance of knowledgeable human translators, 100% accurate translations, demonstrates an openness to the public
        • Disadvantages
          • Security measures must be in place, content accuracy reviews (especially from a cultural perspective), no full-time “staff” to count on
      • Machine Translation
        • Advantages
          • Fast time to market, machine translation servers can be used for a variety of applications, flexibility to change content as often as you wish
        • Disadvantages
          • Generally very costly (based on the number of “language pairs” and sometimes overall use), machine translations often leave out cultural references, evolving industry – no machine translation service has been able to promise 100% accurate translations, yet.
    • The perfect translation team
      • Experts and fellow translators coordinated by a project manager for information transfer
        • Error prevention
          • Doing right the first time every time
            • Education and training play different roles in a translator’s profile
              • Dissociate domain-specific knowledge from language skills and productivity skills
    • Concurrent Translation
    • Community Review
    • Quality
    • Issues
      • Crowdsourcing initiatives can be dangerous when cost is volume based
      • Tools for creating and updating content
        • One-fits-all internationalization strategy
      • Trust and authoritativeness of translators
      • Searchability and accessibility of reference material
      • Bootstrapping and incentives to participation
      • Ownership of material
      • Compensation
    • Pays…
    • Money matters
      • Gresham's law
        • Bad money drives out good
          • If translators are paid low it is hard to get qualified people
      • LSP’s share the same pool of resources
        • Testing freelancers is expensive and not reliable
          • Better to just do small test project
      • Shorten production and industry chains
    • The rise of “ freeconomics ”
      • In a competitive market, price falls to the marginal cost
        • In the translation industry, unit cost is close to zero and will continue to decline
      • Freemium
        • Some software and related services, some content
          • Free to users of basic versions
      • Cross-subsidy
        • Give away services to one customer while selling to another
          • Treat them as if they were free
      • Attention and reputation economy
    • What is your dangerous idea?
      • The history of science is replete with discoveries that were considered socially, morally, or emotionally dangerous in their time.
    • Thank you
      • [email_address]
      • Skype: luigimuzii
      • Blog: http://ilbarbaro.splinder.com
      • Twitter: http://twitter.com/ilbarbaro