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# Fall 2024 Course Review: EECS 496
2024-12-21
Course Title: Major Design Experience — Professionalism
Rating: 2/5
EECS 496 takes the form of guest lectures. Almost every week a different
speaker would take the floor. Some are boring. Some are great. The lecture
topics are (taken from course schedule):
- Introduction
- Interview Essentials
- Startups
- Achieving Financial Fitness
- Investments
- Project management
- Respect in the Workplace
- Venture Capital
- Intellectual Property: Trademarks, patents, and copyrights
- Introduction to Ethics (I missed this lecture because Whitfield Diffie
gave a talk earlier)
- AI and Ethics: Trust, Cooperation, and Society
- Technology and Public Policy
## Honorable Mentions
### Venture Capital
You didn't expect me to compliment a venture capitalist, did you? Well,
"recovering venture capitalist", as Brendan Richardson describes himself.
He's a funny guy. He wasn't defending VC. He was roasting it, mercilessly.
Quote unquote:
> True of False?
> The reputation of Venture Capitalists as selfish, arrogant, greedy jerks
> is DESERVED?
> TRUE!!
His talk almost caused me to have sympathy toward VCs. Takeaways:
- A VC's job is nearly impossible
- Like spotting a future Olympics champion in kindergarten
- Most startup companies fail
- Most VCs fail
- Most of the money VCs throw into startups isn't theirs, but that of much
bigger companies ("Limited Partners") like foundations or insurance
companies
- Because most startups fail, those who succeed must generate explosive
returns (10x, 100x, you name it)
And that's why, according to Richardson, VCs sleep like babies, in that
they wake up every two hours and cry.
Still though, VCs cannot be acquitted of their crimes against humanity and
the environment.
Lesson learned: I could never be a VC.
### AI and Ethics
Ben Kuipers doesn't believe in the singularity. Machines aren't gonna team
up and kill us either. As of 2024 (hi archaeologists), when a machine
kills someone, it is not because it wants to; it's because it wasn't aware
that it's about to kill someone. Like the Waymo that dragged a pedestrian
down under. Nobody thought it could happen, but it did. And there wasn't
a section of code, or a part of the model, that dealt with this scenario.
Kuipers argues that, by the time an AI faces the trolley problem, it's
already too late. If a car on autopilot is driving on a narrow street, and
it can either kill a pedestrian or the passenger — the debate should not
be about whom to kill, but about why the fuck didn't the car slow down in
the first place.
### Technology and Public Policy
Molly Kleinman believes public policy is necessary, no matter what the
techbros say. When a technology is said to be for the "public good",
a good question to ask is always "but _whose_ public good?"
A lot of modern innovations be like:
\> create cool technology
\> look inside
\> biases
One example she used was the speeding cameras in Chicago citing more
tickets in Black neighborhoods. The root cause was that roads there were
often wider so drivers had less incentive to slow down. Infrastructure
issue.
### Respect in the Workplace
Taj Williams, DEI person at CSE, talks about allyship. Allyship is when
you're in the majority but support minorities.
Me, being in several minorities, believe this should be one of the first
lectures, not the seventh. If it were, I wouldn't have called EECS 496 the
"torture lecture".
## Dishonorable mentions
These are the lectures that made me coin "torture lecture".
### Investments
He starts from the importance of paying off credit card debt. Forty
minutes later he's talking about real estate investment. My brother in
christ that's quite a leap
I asked him if he considers real estate investment ethical under current
social circumstances, when homeless people exist. He was kinda upset and
I did not ask any further.
### Achieving Financial Fitness
I wasn't planning to retire in the US, but now I know how 401(k) works so
thank you I guess??
## Assignments
- Elevator pitch: Try to sell myself to an employer at a career fair
- Budget: Figure out how much I'm gonna earn and spend when I get a job
- Executive summary: Try to convince that my MDE (473) project has
a market and is profitable (it's not)
- Microaggressions: Try to deal with bigots in the workplace with
Direct/Delay/Delegate/Distract
- Op-Ed: Write an op-ed about a technology that raises an ethical concern,
and another to argue that the concern isn't so threatening
I was deducted two points from the Microaggressions assignment because
I forgot to include a "Generative AI statement", which, if it did exist,
would say "nope". I don't have a problem with the deduction, I'm just mad
that I can't even write an assignment without doing a captcha.
## Verdict
Overall experience is Not Good™. I took this course only because I had to.
I sure am glad there exist a few good lectures to justify it.
Although most of the knowledge didn't immediately come to use, it might
prove helpful some time in the future.
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