Top 10 Quotes – Weapons of Math Destruction

Weapons of Math Destruction – Cathy O’Niel

O’Niel earned a Ph.D. in Mathematics at Harvard and taught at Bernard College before moving the private sector finance and data science. Her overall theme is summed up in the conclusion: Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide (p 204)

1) Justice cannot just be something that one part of society inflicts upon the other.

p 96

The good news…. is that once thousands of security cameras in our cities and towns are sending up our images for analysis, police won’t  have to discriminate as much (p 101)

2) People had deliberatly weilded formulas to impress rather than clarify

We must avoid this at all costs. This created noise in the silicon valley bubble. If you can’t explain something in simple English, you probably do not understand it well enough. p 44

3) Algorithm – an opinion formalized in code

Algorithms, like processes and culture, must adapt to fit the needs of the human-centric goals they strive to achieve. p 53

4) The trouble was that the rankings were self-reinforcing

When discussing US News collegiate rankings. Low rankings caused less alumni donations and lower applications. The ranking was destiny. p 53

5) young children and adolescents of parents working unpredictable schedules or outside standard daytime working hours are more likely to have inferior cognition and behavioral outcomes

Clopenings must be done away with. Human time must not be optimized as a commodity. p 129

6) The problem is not the US News model but its scale. It forces everyone to shoot for exactly the same goals, which creates a rat race – and lots of harmful unintended consequences

Algorithms are almost never to be applied on global scales. It is generally better to focus on scale where data is rich and insightful to helping local neighborhoods and communities. p 58.

7) In a system in which cheating is the norm, following the rules amounts to a handicap

p 63

 

8) In our largely segregated cities, geography is a highly effective proxy for race

Exclude geography from value-judgments or risk harming groups of humans based on race. p 87

9) Hackathon

The goal of such events is to bring together hackers, nerds, mathematicians, and software geeks and to mobilize this brainpower to shine light on the digital systems that wield so much power in our lives p 91

10) While looking at WMDs, we’re often faced with a choice between fairness and efficacy.

if we don’t wrest back a measure of control, these future WMDs will feel mysterious and powerful. They’ll have their way with us, and we’ll barely know it’s happening. P 173.

 

My point is that oceans of behavioral data, in the coming years, will feed straight into artificial intelligence systems. And these will remain, to human eyes, black boxes. Throughout this process, we will rarely learn about the tribes we “belong” to or why we belong there. In the era of machine intelligence, most of the variables will remain a mystery. Many of those tribes will mutate hour by hour, even minute by minute, as the systems shuttle people from one group to another. After all, the same person acts very differently at 8am and 8pm.

 

 

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