Text Analytics

Text Analytics: NLP for Social Good

IMPORTANT NOTE: The course will take place in accordance with the adjusted schedule and modalities for the summer term (Covid-19 pandemic effects). Thus, the below dates are subject to change.

Seminar kick-off on 23.04, time slot will be announces in moodle.

Course Description

Natural Language Processing (NLP) technology has seen tremendous advances in the past few years. These advances have greatly expanded the field in the academic and industry fields, but the application of this technology to social good has lagged behind. This seminar will explore how to use modern artificial intelligence, in particular, NLP, to tackle problems of “social good”: how can we use state of the art technology to solve problems in healthcare, disaster management, ethics, and public policy?

Teaching Staff

  • Prof. Dr. Iryna Gurevych
  • Ivan Habernal, PhD
  • Kevin Stowe, PhD

Office hours

TBD

Literature

Will be announced during the seminar.

Timetable

The first sessions will consist of introductory lectures to cover the basics of machine learning methods for NLP tasks. We will then cover applications pertraining to “social good”: producing positive outcomes, responsible AI, and public policy. The program for the remainder of the seminar will be determined according to the number of participants and will answer the following questions:

  • How can we leverage NLP technology to solve social problems?
  • What ethical considerations are necessary for this technology? How do privacy, bias, fairness, and equity affect AI solutions?
  • How can we use NLP to improve public policy making across a variety of domains?
  • What public policy is necessary to ensure the advancement fair, effective, and equitable NLP solutions?