Internship - Computational Linguistics

Location: San Francisco, CA
Date Posted: 10-13-2017
Interested in language/writing/story telling? Interested in how beliefs are shaped and perpetuated? How fake news “sticks” to some people? Or perhaps you're just curious about how AI works and want to know more what all this hype around Machine Learning and Deep Learning is all about? Or maybe it's all of the above??
Look no further: now you can do all that AND get paid for it!

About Protagonist Technology

Protagonist Technology is not an ordinary analytics company, or an ordinary software startup. At the core of our unique solution is a rapidly emerging technology category called Narrative Analytics. This unique human-in-the-loop technology, where human analysts work in tandem with the most powerful artificial intelligence algorithms, goes beyond basic NLP techniques like sentiment analysis, text categorization, etc.

Narratives are underlying beliefs and attitudes that drive human behavior. In commerce, politics, and society, media voices are multiplying, facts are losing their currency, and narratives are filling the void to drive people’s attitudes and behavior. Global corporations and foundations contend with narrative challenges that pose great opportunity and also existential challenges to their business models. These organizations need new ways to change the conversation, build their brand and reputation, and understand and activate their customers. We are the only company to bring a robust data-driven solution to the analysis of narratives. Our growing customer list, including Citibank, HPE, Microsoft, Starbucks, WB, State Street Global Advisors, Mars, General Mills, Pfizer, Charles Schwab, PG&E, VMWare, The Gates Foundation, Rockefeller Foundation, and more, all provide validation to our unique approach. .

At Protagonist Technology we have 20 years of experience with qualitative (human) analysis of narratives and have deep in-house expertise of how to identify, analyze, structure and understand narratives in news and social media. We marry that qualitative expertise with deep expertise in NLP and machine learning (deep learning, LSTM, etc.), to bring scale, efficiency, and new insight to our long-standing methods. Through this process we deliver a more nuanced, complex and valuable set of insights to our customers than traditional NLP and analytics companies. This vast knowledge and background in narratives positions Protagonist Technology as a market and thought leader in this emerging category that delivers the richness of insight of traditional research, with the scale and efficiency of social media monitoring.
 

Role description

Perhaps the key element in powering these advanced machine learning algorithms, the “fuel” of the algorithms if you like, is vast amounts of qualitative training data. Training these AI methods is very much like training a human to perform a task; you need to demonstrate/give examples of the task...often many many times.
This role is for 3-4 human annotators who will by labeling large amounts of textual data (natural language texts, such as news articles, op-eds, blog posts, reviews, tweets etc.) help train our computational linguistic algorithms to perform those jobs automatically going forward. This will for any english major, or generally humanities students, be a unique opportunity to understand the foundations of the ongoing AI revolution (arguably the next industrial revolution our civilization faces). You will be given a solid overview in these techniques and have a chance to finally comprehend how AI technologies learn from humans, what their strengths and weaknesses are and what their potential pros and cons are.
You'll receive on-boarding training in how to label human natural language text in order to optimize for fast and accurate learning by the machine learning algorithms. Your goal, as well as ours, will be to help the machines understand human text the way us humans understand it. The underlying meaning and narrative of the text, beyond just syntax.
And yes, you'll certainly finally understand the difference between data science, machine learning and AI, as well as the difference between computational linguistics and NLP.

Requirements

  • Must have: Native fluency in/strong command of the English language
  • Must have: Computer literacy, must be able to sit in front of a computer screen for up to 8h/day
  • Must have: Available at least 20h/week for annotation work (physical presence in SF office at least 2 days/week)
  • Must have: Personal laptop
  • Preferred: Fast reader :-)
  • Preferred: Pursuing or completed degree in English literature, Social Science or any other Humanities subject

 
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