Engineering TED Talk: Computer Science in Social Justice

Columbia Engineering: TED TALK

Engineering and social justice: Computer Science

1st speaker: Julia Hirschberg

  • Identification of hate speech (friend vs. stranger hate speech)
  • AI then and now:
    • Original goal: create machines with human intelligence in reasoning, NLP, robotics, vision (machines that can replace humans)
    • Today AI has applications to many areas: healthcare, education, entertainment, sustainability, transportation, and commerce
    • But, rather than replication/replacing human intelligence, the term “collaborative AI” is becoming popular–how can AI help humans, not replace them
  • More positive contributions of AI:
    • Virtual reality to study, treat, and simulate autism traits
    • Snapchat recently helped over 400,00 new voters register to vote
    • New predictive model for disaster relief, smart agriculture, medicine delivery, and education in developing countries
    • Ai remove bias from judging for 2020 olympic gymnastics
    • AI can provide electronic strike zone in baseball and many other sports
    • Computer vision techniques helping customers choose makeup colors by matching their picture to one of 40 shades → fashion & computer science
  • AI faces many challenges:
    • Self-driving cars are not yet safe
    • AI are taking over people’s jobs
    • AI can invade privacy and create & circulate fake news
    • Deep learning systems perpetuate biases of the data they are trained on (MT, job search, face recognition)
      • Face recognition: dark faces are gorillas or just do not appear
    • Machine translation in pronominally gender-neutral languages’ pronouns: Doctors and programmers are men; nurses and homemakers are women
    • Software that warns people using Nikon cameras when the person they are photographing seems to be blinking tends to interpret asians as always blinking
    • Facebook ads have targeted particular genders or ethnicities for jobs, excluding women and ethnic minorities
  • AI software is being used to make serious decisions on:
    • Loan-worthiness
    • Emergency response
    • Medical diagnosis
    • Job candidate selection
    • Parole determination
    • Criminal punishment
    • Educator performance
    • ^often without user awareness of its limitations

2nd speaker: Kathy McKeown

  • Objective: develop a system to automatically detect aggression and loss in social media posts by gang-involved  youth
    • Challenges: size of labeled dataset
    • Domain-specific language
    • Context critical

3rd speaker: Dr. Shih-Fu Chang

  • Experts believe the increased use of social media among gang-involved youth may be an important factor in the uptick in gang violence in cities across America
  • Imagine a world where social media yields clues that identify risk and protective factors for gang violence and prevent the use of firearms
  • Some projects he is working on:
    • Image processing/AI/computer vision to understand gang violence
    • Visual search technology for fighting online human trafficking: try to understand illegal information on the dark web, used by 200+ law enforcement agencies or NGOs to locate victors or identify groups engaged in human trafficking