This presentation helps businesses trying to improve their workflows using crowdsourcing and specifically, Mechanical Turk. Improving human efficiencies and lowering costs.

1. amazon
web services
Crowdsourcing for
improving
Business Process
October, 2012 - Optimized for 1280x960 - © Amazon Web Services

2. _ Presented by
John Hoskins, hoskins @ amazon.com
Mechanical Turk, Amazon
[ Before we start
]
2

3. How does it
High Crowdsourcing work Examples
Level
Questions
Detail What is MTurk? How is it used
[ Our plan for today ]
3

4. [ ]
What is Crowdsourcing?
4

5. [ Crowd Labor Trends ]
5

6. 1. Crowdsourcing
6

7. [ Crowdsourcing:
Key Advantages ]
7

8. [ 1. Elastic Capacity ]
8

9. On and Off Fast Growth
Variable peaks Predictable peaks
[ Staffing Usage Patterns ]
9

10. On and Off WASTE Fast Growth
Missed
Variable peaks Opportunity Predictable peaks
[ Staffing Usage Patterns ]
10

11. On and Off Fast Growth
Variable peaks Predictable peaks
[ Usage Patterns:
Crowdsourcing ]
11

12. [ 2. On Demand Availability ]
12

13. [ ]
3. Pay as you go, for what you use
13

14. $ $
Lower costs Capital efficiency
Improve productivity Focus on your business
[ Business Benefits
of Crowdsourcing ]
14

15. 2. What is MTurk?
15

16. Marketplace for Work
_ Access to global workforce, on demand
_ Quality controls and workflow “building blocks”
_ Pay as you go, only when satisfied with results
_ Programmatic Access (API)
[ What is Mechanical Turk? ]
16

17. _ 500,000 Workers
_ 190+ Countries
[ Global Workforce
]
17 (as of Apr 19th, 2012)

18. 3. How it works
18

19. [ How it works ]
19

20. Highest
Performing
Average
MASTERS
Unknown
[ Mturk Workforce ]
20

21. Highest
Performing
Average
MASTERS Unknown
Your Custom
Workforce
[ Custom Workforce ]
21

22. Speed
Price
Accuracy
[ Balances & Levers
]
22

23. 4. How is it used?
23

24. Data Management Analysis/Research
_ Verification _ Sentiment
_ Entry & Collection _ Relevance
_ De-dupe _ Online Research
_ Algorithm Training
Content Management Annotation
_ Moderation (Photos, Content) _ Tagging
_ Transcription _ Classification
_ Localization/Translation
[ Common Use Cases ]
24

25. How can we assess relevance of
tweets in real-time?
How can we research and categorize
merchants in our database?
How can we verify accuracy of low
confidence OCR scans?
How do we build a dictionary to
categorize ads on the internet?
[ Examples ]
25

26. Categorization
Web Research
Transcription
Categorization and DeDupe
[ Examples ]
26

27. amazon
web services
http://www.mturk.com
John Hoskins, Mechanical Turk
hoskins@amazon.com
27