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ITI Exam 4

Module 4:

Week 12:

  • DNS (domain name system) acts as a phonebook for the internet and translates domain names into IP addresses
  • The Stop Online Piracy (SOPA) Act and the PROTECT IP (PIPA) Act were passed to protect copyright work and combat online piracy. This bill gives copyright holders the right to take legal action if their work is taken without proper authorization. If someone made a website where people can watch free movies, the copyright holders can take this to court. The only concerns it raised was censorship and threats to Internet freedom
  • Dark patterns- when website or apps trick you into doing something you didn’t intend to do
  • Confirmshaming- emotionally manipulating a user into doing something that they would not otherwise have done

Week 13:

  • Sociotechnical design: market, norms, law, and architecture
  • Design thinking process has 5 steps:
  1. Empathize- understanding a problem and use of technology from another person’s perspective
  2. Define- analyzing interviews and data in order to solve and understand the problem
  3. Ideate- an idea or solution on how to solve the problem
  4. Prototype- create a prototype that solves the problem
  5. Test- assess and examine prototype to see if it works
  • User interface (UI) refers to the look and feel of a website page or product whilst user experience (UX) is the overall experience of the website or product

Week 14:

  • Machine learning, narrow AI, and machine learning intelligence
  • Intelligence- the ability to acquire and apply knowledge and skills. In this case, it’s the ability to learn.
  • AI (artificial intelligence)- the theory and development of computer systems able to perform tasks that normally require human intelligence
  • Machine learning (ML)- a branch of AI in which a computer generates rules and predictions based on raw data that has been fed into it. Ex) social media algorithm where a platform will recommend content that you’re likely to engage in
  • Amazon, Netflix, and other platforms use ML to predict user patterns based on previous data. This encourages users to buy more and invest more in content or products
  • Types of ML:

Descriptive ML: this is what is probably happening.

Predictive ML: this is what will probably happening

Prescriptive ML: this is what probably should happen

Supervised ML- labeling examples in a specific domain to teach AI to recognize patterns. ex) pattern of binge watching a movie/TV show on Netflix, the content you press the like button on, products added on your wish list, and what you label as good/bad.

  • Training shoes recommender system
  1. Training stage- take 80% of labeled data and instruct AI to look for certain patterns
  2. Testing stage- Remove labels of 20% to test the AI
  • Two errors: Problem of precision where images and labels in training data must be accurate, clear, and unambiguous. Problem of bias in which the pattern is biased and what makes something good or bad. It can give rise to discrimination
  • Futurism- study of social and technological advancement for the purpose of exploring how people will live and work in the future
  • 3 hockey stick problems: Population growth, GDP (gross domestic product) growth, linear, and technological advancements are not linear
  • Moore’s law- the number of transistors in an integrated circuit (IC) doubles about every two years. Gordon Moore is the co-founder of Intel in 1968
  • Exponential growth in people, goods, and computational power makes predicting the future difficult
  • Two types of AI that could destroy humanity: Narrow or weak AI refers to training in performing a specific task, can perform one thing well, and has a narrow scope of expertise. Generalized or strong AI refers to the ability to learn and adapt to new situations; can perform a wide range of tasks or near a human-like level. It can also understand and adapt to broad, complex, unanticipated experiences.
  • Instrumental convergence- an intelligent agent with unbounded but harmless goals can act in surprising and harmful ways. This can have unintended consequences such as human enslavement by AI and loss of jobs.