Editing Algorithmic Power and Justice (section)

== <span style="color: #FFFFFF;">Understanding</span> ==
Algorithmic power is understood through '''Invisibility''' and '''Scale'''.

'''1. The Myth of Neutrality''':
Many people believe that "Math can't be racist."
* But if you train an algorithm on 50 years of data from a biased court system, the algorithm will "Learn" that bias.
* It's like a mirror: if the world is broken, the algorithm's "Reflections" (its decisions) will also be broken.

'''2. Weaponized Math (Scale)''':
When a human judge is biased, they only affect a few hundred people.
* When an algorithm is biased, it can affect **millions** of people instantly across an entire country.
* This is what Cathy O'Neil calls a "Weapon of Math Destruction" (WMD)—a system that is widespread, mysterious, and destructive.

'''3. The "Due Process" Problem''':
If a human judge denies you a loan, you can ask "Why?" and argue against them.
* If an algorithm denies you, the answer is often: "The computer said so."
* Without "Explainability," it is impossible for a citizen to defend themselves against a machine.

'''The 'Fairness Paradox'''': There are many different mathematical definitions of "Fairness." It is often impossible to satisfy all of them at the same time. You have to "Choose" which type of justice you value most, which is a political decision, not a math one.
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