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RailsConf 2018: Human Powered Rails: Automated Crowdsourcing In Your RoR App by Andy Glass Machine learning and AI are all the rage, but there’s often no replacement for real human input. This talk will explore how to automate the integration of human-work directly into a RoR app, by enabling background workers to request and retrieve data from actual human workers. The secret is Amazon Mechanical Turk, a crowdsourcing marketplace connecting ‘requesters’ who post tasks with ‘workers’ who complete them. Attendees will learn how to automate the completion of human tasks (e.g. price research, image tagging, sentiment analysis, etc) with impressive speed, accuracy and scalability.
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In this talk at RailsConf 2018, Andy Glass discusses how to effectively create a human-powered API using Ruby on Rails in conjunction with Amazon Mechanical Turk (MTurk). The presentation begins with Andy's background and his experiences with programming that shaped his career. He then introduces the concept of MTurk as a marketplace for micro- tasks, linking requesters who need tasks completed with workers who perform those tasks. The talk covers several key points regarding integrating human input into applications quickly and efficiently: - **MTurk Overview**: MTurk provides a scalable and always-available workforce for various tasks such as image processing, data verification, and information gathering. - **Historical Background**: The name 'Mechanical Turk' comes from an 18th-century chess-playing machine that was revealed to be controlled by a human hidden inside. - **Use Cases**: Common applications for MTurk include data validation, price research, and training machine learning models. - **Practical Application**: Andy illustrates the process of using MTurk with a real-world example, designing a project to determine if certain Pittsburgh sandwiches contain fries. He discusses the setup process for requesting work from MTurk workers, including task descriptions and payment structures. - **Automation in Rails**: The importance of automating the MTurk process within a Ruby on Rails application is emphasized, explaining how background jobs can manage task submissions and data retrieval effectively. - **Adjudication Process**: To ensure accurate results, a system for adjudicating responses from workers is discussed, where conflicting answers can trigger further review from additional workers. - **Ethical Considerations**: The presentation addresses important discussions about the ethics of using MTurk, highlighting prevalent concerns regarding fair wages and the potential exploitation of low-cost labor from both U.S. and global workers. By the end of the session, Andy Glass encourages attendees to explore the possibilities of integrating human input into their applications through MTurk, inspiring curiosity about leveraging crowdsourced labor effectively in software development. He leaves the audience with a sense of achievement that through collaboration and effort, software developers can create impactful solutions that push their boundaries.
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