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[TECH ED] Apply Magic Sauce #108

Open areebsattar opened 10 months ago

areebsattar commented 10 months ago

Link to the coursework

https://applymagicsauce.com/demo

Why are we doing this?

Companies are very interested in the data provided by software like Apply Magic Sauce. Automated language analysis is already being used in the hiring of personnel. Applicant Tracking Systems (ATS) are used in 97% of Fortune 500 companies.

Apply Magic Sauce is a machine interpretation of personality based on how a person writes a sentence in an email or the types of content they like on social media. This is great when it gets the personality traits 99% accurate. But what if it goes horribly wrong and ruins lives?

Choose one thing that Apply Magic Sauce can do that you don't like (or like the least). Describe what it is and say why you don't like it. (250 words)

Below are some starting points for you to think about:

  1. What happens when human beings rely on software to make consequential judgments about human beings?
  2. Are algorithms more or less biased than people?
  3. What are the consequences of surveilling people in this way? How does this affect how people talk and act online?

Maximum time in hours

1.5

How to get help

Undertake the demo at home and then discuss this in class. Developers should be literate citizens of the internet, and understand the consequences of gathering and analysing personal data. You may also like to look into some short courses on GDPR on Udemy.

How to submit

Post your analysis in your class channel thread, and join the discussion. Post a link to the thread on this ticket.

JayMayer commented 8 months ago

@areebsattar could you link me to the thread on Slack?

areebsattar commented 8 months ago

Link to the doc: https://docs.google.com/document/d/1N3OAIEHhOraNBPvdzHME7a4-paeiC5HOdrLahOvETDs/edit?usp=sharing

Link to slack thread: https://codeyourfuture.slack.com/archives/C05RPC3T4JH/p1712355590146879?thread_ts=1704714228.953979&cid=C05RPC3T4JH

JayMayer commented 8 months ago

That’s a great write up, well done @areebsattar! I particularly like how you raise bias in algorithms in your work. Just a quick online search for “algorithmic bias” will show how this is a pressing issue, where algorithms trained on limited sets of data can become biased against certain groups of people. It’s a great reminder to always consider the people impacted by the technology we build.

areebsattar commented 8 months ago

I just looked it up and I didn't really thought that this would be a thing, thanks for telling me about this and thank you for the feedback!