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
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