Adversarial Learning

Adversarial Learning

By Joel GrusTechnology
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Adversarial Learning episodes

  • Episode 16: My Code of Ethics Will Forbid YAML

    Adversarial Learning is back!
    In this long-delayed episode (thanks, technical difficulties)
    we are joined by data scientist
    Schaun Wheeler to discuss our favorite topic, data ethics. Highlights include:

    * Schaun's Medium post "An ethical code can’t be about ethics"
    * Do we need a "Hippocratic Oath" for data science
    * How to hire data scientists who won't steal people's kidneys
    * Why Joel has a Values Mug
    * The Manifesto for Data Practices
    * Is this all secretly a competency problem?
    * Skin in the Game
    * Are data ethics issues really just business ethics issues?

    Please listen to it! 

    (More episodes coming soon!)

    50 min
  • Episode 15: Could You Rephrase That As An Ethical Question?

    Our guest this week is data scientist for good
    Lisa Green. 

    Topics of discussion include

    • What is ethics 
    • Joel's previous life as a financial analyst and the ethical dilemmas therein
    • whether there's anything incriminating in Joel's Yahoo history
    • "identity theft" as a bullshit concept 
    • Google's corrupt bargain with the NHS
    • what the medical code of ethics actually says 
    • polycentric ethics
    • the difference between unethical and incompetent
    • what good a code of ethics does when the "ethical" problems are emergent from the choices of many people
    • that terrible article about the Seattle Nazi convention
    • neuroticism 
    • the Joel test 
    • vgr's bad tweet

    Please listen to it.

    1 hr 5 min
  • Episode 14: Totally Derivative

    Our guest this week is flashcard kingpin and former Partially Derivative co-host Chris Albon.

    Topics of discussion include

    • how good it feels not to have a podcast
    • machine learning flashcards
    • being a "natsec bro"
    • whether Chris would punch a Nazi
    • whether Chris would sexually harass a Nazi
    • whether "magister" is a good woke replacement for "master"
    • whether that Andrew Ng job posting is appropriate and whether any of us would apply for it
    • killing your heroes
    • having a day a week without social media
    • treadmill desks
    • Chris's next podcast
    • and somehow Joel gets going on Harry Potter

    Please listen to it.

    1 hr 8 min
  • Episode 13: Back to School

    It's Back to School time at Adversarial Learning!

    topics of discussion include

    • OUR SPONSOR: the Metis Demystifying Data Science Conference (at which Joel is speaking, please listen to it)
    • Sudbury education
    • John Holt
    • times tables
    • whether textbook piracy is the new stealing from the library
    • Neil Tyson's "In School" cycle of tweets
    • how to teach curiosity
    • why math is a "hard" skill and people skils are "soft" skills when factorizing matrices is easy and dealing with people is hard
    • whether and how our schools should be producing more data scientists

    Please listen to it.

    55 min
  • Episode 12: Data Science Myths
    Data scientist Vicki Boykis joins Joel and Andrew to variously debunk and rebunk common Data Science Myths. Is data the new oil? Do data scientists spend 80% of their time munging and cleaning data? What happens if you look in the mirror and say "data science" five times? And many, many, many more.
    Please listen to it.
    55 min
  • Episode 11: Data Conferences
    Andrew and Joel come out of hiatus to discuss data conferences: when to attend them, how to get your talk accepted, how to network, optimal heckling strategies, where to stay, and so on. Somehow they also end up talking about fidget spinners, the "objective" section on resumes, the right way to use LinkedIn, why Andrew doesn't think much of data science bootcamps, and why Joel can't convince any data science bootcamps to sponsor the podcast.
    Please listen to it.
    53 min
  • Episode 10: Stories of Degradation and Humiliation

    Friend of the podcast Tim Hopper joins us as we share stories of Very Bad Interviews we've been on. (As you probably expect, Joel has the most humiliating stories.)

    If you've ever gone on a terrible interview, listen and commiserate. If you've never gone on a terrible interview, listen and live vicariously.

    Halfway through, Andrew's Internet flakes out and his part stops getting recorded. Thanks to the magic of editing, you'll hardly even notice!

    1 hr
  • Episode 9: Owning a Planet

    Our guests this week are Curtis Yarvin and Galen Wolfe-Pauly, which means that our topic is Urbit ("a virtual city of general-purpose personal servers"). What is it?  Why is it? Is is a political project? And does it have anything to offer data science types?

    Curtis and Galen try to explain what Urbit is and answer Joel's objections, while Andrew keeps trying to tie everything back to ham radio.

    1 hr 7 min
  • Episode 8: On Flink

    Our guest this week is Trevor Grant (@rawkintrevo), an Open Source Technology Developer Evangelist (or similar) at IBM. We discuss how to be a high-energy public speaker, all sorts of weirdly-named Apache projects, the "my name is" meme, why Joel and Andrew don't like Jupyter-style notebooks, Voltron, and how to talk to your kid about "normies".

    Please listen to it.

    1 hr
  • Episode 7: Telling a Bot to Go Shove It

    Our guest this week is Juliet Hougland (@j_houg), data scientist and engineer at Cloudera. We discuss that bad Wired article about physics and software engineering, why Juliet knows so much about Urbit, censorship (Twitter and otherwise), dark patterns (LinkedIn and otherwise),
    and why none of us was savvy enough to start a social network for data people
    and raise $19M.

    1 hr 13 min

About Adversarial Learning

From the publisher's feed

@joelgrus and @akm talk about data, science, data science, Shingy, and whatever else they feel like